research on football betting

• How To Research For a Football Bet: 5 Things To Look For

Building a successful strategy for football betting can be a real challenge. Even if you do manage to achieve it, this doesn’t mean you will just place bets and collect your winnings. Constant effort is required and there are certain steps in the preparation for each bet that just can’t be ignored.

How to Study Football Betting

The research before each football match is the key to success, as it’s the only way to get a good evaluation of what’s to be expected.

Depending on the markets you choose, there might be plenty of details, but the basis remains the same most of the time.

Let’s cover the aspects of how to analyse football matches for betting. They won’t instantly make you a winner, but it’s a huge step in the right direction.

1. Check the Performance of Both Teams Over a Long Period

This is an obvious step and yet, somehow plenty of people underestimate its importance. The long-term performance of both teams involved is the best way to get a good idea of their average performance. There is a reason the legendary Bill Shankly once said: “form is temporary, class is permanent”. Certain bookies like bet365 will under-price a well known team, just because punters assume they’ll win. Sometimes a side like Man Utd may always struggle away to Sunderland, but the bookies don’t reflect this in their odds – they want to suck people in that just jump on the big named teams.

The exact time frame depends on what you are looking for, but the minimum should be around a couple of months or even a year. This will give you a good start and a platform to build on when you go into more details later.

The important questions here are how does the team perform in terms of goals scored, goals conceded, playing home or away (depending on the game), results against teams similar to the next opponent and many more valid points that should be considered.

2. Check the Short-Term Trends

After you have a good understanding of the bigger picture, it’s time to dig deeper and see what is the current shape of both teams. As we know, confidence is key in football and certain players can look like world beaters one day and like Sunday league amateurs the next. That makes short-term trends extremely important.

Take a look at the last 5-10 games of each team, this should be enough to show you what to expect. Once again, stats such as goals scored, goals conceded, average possession and form of the best players are the things you should be looking for. It’s a good idea to actually read a short match report for each of the games in case you haven’t watched them. You never know if a team was just unlucky with some near misses, wonder goals conceded or referee mistakes.

3. Team News Is Essential

Almost every punter out there knows that you should check the list of suspended, injured and doubtful players. The problem of most people is that they don’t fully evaluate the influence of the absentees. A certain player can be badly missed against certain opposition and easily compensated against another. For example, a team missing its best centre back could struggle against an attacking-minded opponent and do well against a side that prefers to sit back.

WhoScored.com has a great section in their match previews that highlights current injuries and suspensions

Of course, you should also take a look who’s going to replace the missing players. How did their subs perform the last time they played? Are they just bench-warmers or squad players that get enough minutes to be in good shape? Those questions and many more need to be answered.

There is another aspect that is often ignored. The schedule of both teams is essential, as nowadays the number of games played per season demands rotation. This is especially true for the English Premier League due to the lack of a winter break. Check the last couple of games of each team and what’s coming next. It should give you a good idea if the manager will start his strongest line-up or try to rotate a bit.

4. Previous Meetings Between the Two Teams

The next step would be to check how both teams performed against each other in the past. The last couple of games are the most telling, but the historical data shouldn’t be underestimated. Certain fierce rivalries such as the North London Derby between Tottenham and Arsenal, for example, has its own rules and the game often does not depend on form as much.

There is another important thing you might notice – certain teams or even certain players sometimes have a good streak against a specific opposition. Plenty of examples can be seen in the English Premier League where Sunderland is on a great streak against the local rival Newcastle in the past couple of years. The Magpies are also the favorite opponent for Arsenal’s striker Olivier Giroud who is scoring against them on a regular basis.

5. Listen to the Experts

Nowadays, you can find so many opinions on the Internet that could be pretty overwhelming. Most of them would just confuse you and can’t contribute much to your analysis. Still, there are certain experts that could be useful. Whether is successful punters or well-known journalists, there are people who are good at analyzing and predicting football matches.

We don’t recommend you to directly copy someone else’s opinion, but taking your time to read a preview is not a bad idea. Seeing a different perspective could confirm your own expectations or show you an angle you might have missed.

List of Soccer Analysis Websites

After we went through the most important steps you have to take in your preparation, it’s time to list some useful websites that can help you in this regard. Most of them will provide you the necessary data:

SoccerStats.Com

Oddsportal.com.

One of the best free odds comparison services in the business. You will find the best prices for almost any football match out there. It has all the important markets and then some more. On top of that, there are plenty of stats, betting tools, a reliable live score service and even tipsters who provide picks. It’s pretty much the full package.

The OLBG community is probably the biggest when it comes to betting. The platform has many useful features including free tournaments with real prizes, hundreds of successful tipsters and much more. One of the best things is that it’s not limited to football only, so you could check it for other sports as well.

Make your list of things to look for when betting on football

Consider this article as your starter pack for how to bet on football . It’s not enough, but it’s a pretty solid beginning. We strongly encourage you to build on it by finding your own ways for an even better evaluation of the matches you are willing to bet on. Also, there are so many reliable websites and services out there, that you should spend some time checking what can be useful to you.

Mike has over 14 years of experience with online sports betting, having used countless online betting sites. Mike previously provided football betting tips on goals and corners in Facebook groups before starting his own betting website. A huge football fan, Mike has been writing betting guides and football betting advice for years.

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Understanding Football Odds: A Beginner’s Guide to Successful Betting

Football betting is a popular pastime that adds excitement to the sport. However, for beginners, understanding betting odds can be a daunting task. This guide aims to demystify football betting odds, covering the different types—fractional, decimal, and moneyline—and providing examples to help you read and use them effectively.

What Are Betting Odds?

Betting odds represent the probability of an event happening and determine how much you can win if your bet is successful. They are a crucial part of betting, helping you understand the potential return on your investment.

Types of Betting Odds

There are three main types of betting odds: fractional, decimal, and moneyline. Each format is used in different regions and has its own way of representing the probability and potential payouts.

Fractional Odds

Fractional odds, commonly used in the UK and Ireland, are expressed as a fraction (e.g., 5/1 or 7/2). The number on the left (numerator) represents the potential profit, while the number on the right (denominator) represents the stake.

Odds of 5/1 mean you can win $5 for every $1 you bet.

If you bet $10 at 5/1 odds and win, your total payout would be $60 ($50 profit + $10 stake).

Decimal Odds

Decimal odds are popular in Europe, Australia, and Canada. They are expressed as a decimal number (e.g., 2.50 or 3.00), which represents the total payout, including the original stake.

Odds of 2.50 mean you will receive $2.50 for every $1 you bet.

If you bet $10 at 2.50 odds and win, your total payout would be $25 ($15 profit + $10 stake).

Moneyline Odds

Moneyline odds, also known as American odds, are used primarily in the United States. They can be positive (+) or negative (-).

Positive moneyline odds indicate how much profit you will make on a $100 bet.

Negative moneyline odds indicate how much you need to bet to make a $100 profit.

Odds of +300 mean you will win $300 for every $100 you bet.

Odds of -150 mean you need to bet $150 to win $100.

How to Read Betting Odds

Converting Odds to Implied Probability

Understanding the implied probability behind betting odds can help you gauge the likelihood of an event happening. Here’s how to convert each type of odds into implied probability:

Fractional Odds: Implied Probability=DenominatorNumerator+Denominator×100Implied Probability=Numerator+DenominatorDenominator ​ ×100

For odds of 5/1, the implied probability is 15+1×100=16.67%5+11 ​ ×100=16.67%.

Decimal Odds: Implied Probability=1Decimal Odds×100Implied Probability=Decimal Odds1 ​ ×100

For odds of 2.50, the implied probability is 12.50×100=40%2.501 ​ ×100=40%.

Moneyline Odds:

For positive odds: Implied Probability=100Positive Odds+100×100Implied Probability=Positive Odds+100100 ​ ×100

For negative odds: Implied Probability=Negative OddsNegative Odds+100×100Implied Probability=Negative Odds+100Negative Odds ​ ×100

For odds of +300, the implied probability is 100300+100×100=25%300+100100 ​ ×100=25%.

For odds of -150, the implied probability is 150150+100×100=60%150+100150 ​ ×100=60%.

Practical Examples of Betting on Football

To bet on football successfully, it’s important to understand how to apply these odds in real-world scenarios. Let’s look at a few examples.

Example 1: Premier League Match

Imagine a Premier League match between Liverpool and Manchester United . The odds might be presented as follows:

Liverpool to win: 2/1 (fractional), 3.00 (decimal), +200 (moneyline)

Manchester United to win: 3/2 (fractional), 2.50 (decimal), +150 (moneyline)

Draw: 5/2 (fractional), 3.50 (decimal), +250 (moneyline)

If you bet $20 on Liverpool to win at 2/1 odds and they win, your payout would be $60 ($40 profit + $20 stake). Similarly, betting $20 on a draw at 3.50 decimal odds would yield a payout of $70 ($50 profit + $20 stake).

Example 2: Champions League Match

Consider a Champions League match between Barcelona and Bayern Munich with the following odds:

Barcelona to win: 2.20 (decimal), 6/5 (fractional), +120 (moneyline)

Bayern Munich to win: 1.75 (decimal), 3/4 (fractional), -133 (moneyline)

Draw: 3.30 (decimal), 23/10 (fractional), +230 (moneyline)

If you bet $50 on Bayern Munich at 1.75 odds and they win, your total payout would be $87.50 ($37.50 profit + $50 stake). Betting $50 on a draw at +230 moneyline odds would result in a payout of $165 ($115 profit + $50 stake).

In both examples, the potential return varies based on the type of odds and the amount wagered. Understanding these differences helps you make more informed decisions when you bet on football.

Tips for Beginners

Start Small and Learn

As a beginner, start with small bets to get a feel for how betting works. This approach minimizes your risk while you learn.

Research Teams and Players

Knowledge is power. Researching teams, players, and their current form can provide valuable insights and improve your betting decisions.

Compare Odds

Different bookmakers offer varying odds for the same event. Compare odds across multiple platforms to find the best value for your bets.

Use Betting Tools

Many online betting sites offer tools and calculators to help you understand potential payouts and implied probabilities. Utilize these resources to make informed bets.

Manage Your Bankroll

Set a budget for your betting activities and stick to it. Avoid chasing losses and bet only what you can afford to lose.

Understanding football betting odds is fundamental to becoming a successful bettor. By grasping the different types of odds—fractional, decimal, and moneyline—and knowing how to read and apply them, you can make more informed decisions and improve your chances of winning. Remember to start small, do your research, and always bet responsibly. With these tips, you’ll be well on your way to navigating the exciting world of football betting.

Story originally appeared on Mountain West Wire

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BettingStats.org - Football predictions and Free Soccer Stats

Looking for a comprehensive website for all your football betting statistics and tips? Look no further than BettingStats.org! Our website is designed to provide gamblers with everything they need to make informed betting decisions, all in one convenient location.

At BettingStats, we know that time is money, which is why we created our website to save you hours of research every day. With our user-friendly design and detailed football stats, you can easily access high-quality and valuable information, without having to spend hours scouring the internet for the data you need.

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First and foremost, our football stats can help you gain a better understanding of each team’s strengths and weaknesses. By analyzing factors like goals scored and conceded, as well as shots on target and possession, you can identify trends and patterns that may influence the outcome of a match.

Our stats can also help you make smarter betting decisions by providing you with valuable insights into each team’s performance in various markets. For example, by analyzing a team’s over/under stats, you can get a better sense of whether they tend to play high-scoring or low-scoring matches.

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Sports Betting

This article provides insights into the increasing interest in sports betting and its connection to consumer behavior, demographics, and personality traits. Understanding these dynamics is essential for businesses seeking to engage with this growing market.

• The increasing popularity of sports betting, driven by prominent platforms like FanDuel and DraftKings, is explored through data from the 2023 Prosper Media Behavior and Influence (MBI) study, encompassing 17,159 adults aged 18+.
•  Two key questions were asked in the study: “Do you gamble on sports?” and “Do you play fantasy sports?” Responses were categorized as regularly, occasionally, or never.
• 31.7% of respondents engage in sports gambling (regularly or occasionally), while 27.2% participate in fantasy sports, with a substantial overlap of 22.7% doing both.
• Within these categories, 71.7% of sports gamblers also play fantasy sports, and 83.4% of fantasy sports participants also gamble on sports.
• Approximately 40% of the 2023 MBI study population resides in states where online sports betting is illegal, despite substantial legal concerns, especially in large states like California and Texas.
• Historical data reveals a steady increase in sports gambling, particularly in recent years, while fantasy sports participation has remained relatively stable.
• In 2023, 42.1% of males reported gambling on sports compared to 21.5% of females, with both genders showing growth over the past three years, albeit at different rates.
• Demographic characteristics reveal higher sports gambling rates among Gen-Z, Millennials, and males, with connections to various occupations and a slight advantage for those with higher education.
• A classification regression tree (CRT) analysis identifies segments with high sports gambling rates, with age, gender, income, marital status, and ethnicity being significant predictors.
• Viewership patterns indicate that gambling on sports is related to specific sports categories, with minor sports and women’s sports exhibiting greater relative interest among gamblers. Additionally, sports bettors are more likely to engage in sports-related activities, favor alcoholic beverages, and display specific personality traits, including high extraversion and lower grit, demonstrating a distinct consumer profile.

Forward By Dr. Larry DeGaris, Executive Director, Medill Spiegel Research Center, Northwestern University

“Legalized sports gambling is the endgame. One-day fantasy delivers a similar fan experience to gambling, so I expect the current database of customers would provide a good foundation for sports gamblers.” I said this in 2015 when I was interviewed for the Bloomberg article “Daily Fantasy Sites Seen Positioned for Jump to Sports Gambling.”

This interview came on the heels of NBA commissioner Adam Silvers’s 2014 NYT op-ed, “Legalize and Regulate Sports Betting,” advocating legalizing sports betting; I knew it was just a matter of time before sports betting was legalized nationwide and DraftKings and FanDuel were planting the seeds.

Fast forward to 2023, and DraftKings and FanDuel are dominating the sports betting market while big sports brands like Fox and big gaming brands like MGM struggle or fail. I thought it was a good strategy. I didn’t realize how good.

The sports betting market highlights the value of customer data. DraftKings and FanDuel’s market domination is based on their customer data strategy. They bet that fantasy players, especially daily fantasy players, would be the most promising market for sports betting. As sports betting became legal in more states, they were ready. It was a big bet and a big win.

Similarly, brands are placing big bets on Retail Media Networks. The strategy is the same. As we enter the cookie-less world, customer data will become more valuable. That’s no fantasy.

More recently, Fanatics is getting into the sports betting game with its acquisition of Pointsbet, betting that its database of fans will help them compete where others have fallen short. I’m not sure I like the odds. Let’s reverse engineer DraftKings’s and FanDuel’s winning strategy. Martin Block’s nifty little sports betting paper shows us the way.

The relationship between betting on sports and playing fantasy sports is very high. The two groups are almost identical. Unlike the years it took Amazon to build a customer database, DraftKings and FanDuel had theirs built before sports betting became legal. As more states legalized sports betting, they were ready. That initial advantage has been difficult for other entrants to overcome.

Having a database of sports fans doesn’t measure up to a targeted list of fantasy sports players. Similarly, I reckon Fanatics has a great database of fans passionate about their teams, which likewise wouldn’t translate well to betting.

Digging deeper, we see the underlying mechanisms of sports betting and outline a path forward. DraftKings and FanDuel won the first round, but it ain’t over ‘til it’s over.

The women’s market in sports tends to be underserved in general because fan populations are more likely to be male. The difference in degree mistakenly is equated with a categorical difference. Sports bettors are more likely to be male, but there are a lot of women betting on sports.

Sports betting companies have been active as sponsors of sports properties. But sports betting is a fan activity and, as Martin points out, there are many product categories that index high for sports bettors. Creating a brand partnership strategy using sports betting as a platform could bring another revenue stream.

Sports bettors are highly social and competitive. That’s the underlying link between fantasy and betting. Fantasy was a natural connection for sports betting in that respect, but if sportsbooks can innovate ways to connect fans who weren’t playing fantasy, they can gain an entry point. What do you talk about when your team is having a bad year? This week’s parlays. Sports betting is a social experience for fans. Sports betting companies can create a social infrastructure for fans to interact, as they’ve done with fantasy leagues.

The story highlights both the importance and limitations of customer data. Customer data tells you who. Traditional market research can help understand the why.

We should keep this in mind as we watch retail media grow. First-party customer data is tremendously valuable but limited without a deeper understanding of shopper experiences and identities.

By Dr. Martin Block, Professor Emeritus, Northwestern University, Retail Analytics Council

Interest in sports betting is increasing with the publicity that FanDuel and DraftKings have recently enjoyed. To better understand sports betting data from the annual Prosper Media Behavior and Influence (MBI) study collected in January of 2023 (n=17,159) of adults 18+ is analyzed. Two questions were asked: “Do you gamble on sports?” and “Do you play fantasy sports?” Both questions were supplied with answer options of regularly, occasionally, and never. Table 1 shows the proportion of the sample that gamble on sports combining regularly and occasionally at 31.7%, and those playing fantasy sports at 27.2%. There is substantial overlap between gambling and fantasy sports, with 22.7% reporting both. Of those who gamble, 71.7% say they also play fantasy sports. Of those who play fantasy sports, 83.4% say they also gamble. Not all respondents say they gamble and play exclusively online. Of those who say they gamble on sports, 66.0% say they also gamble online. Of those who play fantasy sports, 84.1% say they also play fantasy sports online.

The legality of online sports betting has also been a topic of interest. Using FanDuel’s map of states where the service is legal, Table 2 shows that approximately 40% of the population as represented by the 2023 MBI are in states where it is not legal. Two big states, California and Texas are among the states where it is not legal. It should be noted that in states where it is not legal, the proportion is slightly higher than in states where it is legal. The difference, despite the very large sample sizes, is not statistically different. Legalizing online sports betting appears to have little influence.

The gambling and fantasy sports questions have been asked in the MBI for several years. Table 3 shows the trends over the last eight years for gambling, playing fantasy sports, and playing video games. Playing video games has slowly increased over the years but is showing a slight decline in 2023. Gambling on sports has steadily increased, especially in recent years. Playing fantasy sports has remained almost perfectly flat.

Considering just the last three years, as shown in Table 4 illustrates the recent growth, especially for 2023. It also shows a comparison of gambling by gender. In 2023, 42.1% of males reported gambling on sports compared to 21.5% of females. The average annual growth rate for males over the three years is 3.9%, compared to 4.0% for females.

Table 5 shows some differences by various demographic characteristics and the breakdown by regularly and occasionally gambling on sports. Looking at the characteristic variables by themselves, it appears that sports gambling is highest among Gen-Z, Millennials, and males. There seems to be strong connections to occupation, especially business owners, professionals, salespersons, workers, students, and military. All these occupations have a social component. There is also a slight advantage for higher or more education.

Identifying the Sports Bettor

Using a classification regression tree (CRT) to predict gambling on sports allows for the identification of consumer segments that have high rates of gambling on sports. Table 6 shows the results of such analysis and the important predictor variables. The most important predictor, by far, is age. This is followed by gender, income, family size, marital status, ethnicity, and population density. The model itself is reasonably strong, predicting a bettor 73.7% of the time using 10-fold cross-validation.

The tree itself identifies the segments as terminal nodes, as shown in Table 7. The highest node, those under 44, male, incomes over $106.5K, and married report 81.2% betting on sports and comprise 5.3% of the total population of adults. Slight older, ranging from 44 to 51, report 67.7% betting. Under 51, males, over $1065k   and are single (never married) report 60.9% and comprise 1.6% of adults. Males under the age of 51 with incomes between $53k and $106K living in an urban area report 64.0%, and males in suburban and rural areas report 50.6%. Males under the age of 51 with incomes less than $53K, who are non-white report 51.1% gambling on sports and comprise 6.3% of the total population. These are all the male segments above 40% of sports gambling.

The female side of the tree shows non-white with a family size of four or more at 45.3%, comprising 5.4% of the total sample. Non-white females, with a family size of less than four, and younger than 36 report 40.0% gambling and comprise 4.0% of the total sample. Among the older segments are males earning over $53K, aged 52 to 55, reporting 49.6% gambling, and African American males earning under $53K, aged 52 to 63, reporting 44.9% gambling.

Sports Program Viewing

Respondents were asked if they regularly viewed 12 different sporting events. To establish a pattern, the 12 were factor-analyzed (principal component) as shown in Table 8. The viewing patterns are arranged in three groups labeled “major,” which includes the NFL, college football, and other team sports of broad interest. The analysis shows that those who report viewing the NFL are also likely to watch college football. The second group, labeled “minor,” includes professional tennis and golf and have a narrower level of interest and are not thought of as team sports. The third group is labelled “women’s” for woman’s sports..”

Relating the viewing to gambling on sports is shown in Table 9. Overall, 73.2% of adults report viewing at least one of the categories of sports programming. The NFL is viewed by 38.4% of adults, followed by college football, major league baseball, and the NBA. Sports betting is certainly related to viewing, as in the case of the NFL, where 46.1% of the viewers compared to 34.7% of the viewers do not gamble, providing a gambling index of 120.1. The major sports have an average index of 150.7, minor sports have an average index of 176.9, and women’s sports have the highest average index of 189.8. Minor, less team-oriented sports, and especially women’s sports, are of greater relative interest to gamblers.

Weighting sports betting by regular viewing demonstrates the relative interest in the sports category, as shown in Table 11. The NFL overall leads sports betting activity, followed by the NBA, college football, major league baseball, and college basketball. All these categories are team-oriented and of broad interest.

Those who report gambling on sports are more likely to engage in a variety of sports-related activities, as shown in Table 12. Engaging in online fantasy sports and online gambling index at almost double. Sports on the radio and smartphones are higher than regularly watching sports on TV. Fox Sports indexes higher than ESPN.

Respondents were also asked about 31 different leisure activities, which are compared to reported gambling on sports, as shown in Table 13. The highest indexing activity is playing team sports. Also high are very active categories such as tennis and snow skiing. Social activities, such as tailgating and going to gambling resorts, bars, and sporting events are also high. The image of sports betting is being social, interested in competition, and physically active. On the other hand, those indexing low is generally passive and perhaps a bit more solitary, reporting activities such as watching TV, surfing the internet, crafting hobbies, and reading books. Those activities are indexed at nearly the same (not shown) as going shopping, online communities, and travel.

Product Consumption

Consumption of alcoholic drinks is commonly associated with viewing and gambling on sports. Table 14 shows this to be true as most categories of drinks index at almost double among those that gamble. The lowest index is wine.

Average monthly product spending is collected monthly, with the categories rotating across different months. The data from the monthly surveys (average n=7,500) needs to be integrated with the annual MBI, which is done using decision tree equations from available demographic variables common to both the monthly and MBI studies. Shown in Table 15 are the average reported household monthly spending across a variety of product categories. The months are taken from 2022 prior to the 2023 MBI. The averages include zero if the respondent reports no spending in that category. The highest indexing category is sporting goods, followed by men’s clothing and both fast food and full-service restaurants. It is worth noting the home improvement spending indexes highly note the characteristics of the sports gambler. Smartphone and grocery spending is almost the same. Overall, those who gamble on sports spend more on average than those who do not.

Personality

Several personality measures were also collected in the MBI including the five-factor personality inventory commonly referred to as OCEAN, grit, and impulsiveness. The personality inventory used by Prosper in the MBI is taken from the short-form version developed by the Gosling Laboratory at the University of Texas. The five factors include:

• Extraversion: Extraversion is characterized by excitability, sociability, talkativeness, assertiveness, and high amounts of emotional expressiveness. People who are high in extroversion are outgoing and tend to gain energy in social situations. People who are low in extroversion (or introverted) tend to be more reserved and must expend energy in social settings.
• Agreeableness: This personality dimension includes attributes such as trust, altruism, kindness, affection, and other prosocial behaviors. People who are high in agreeableness tend to be more cooperative, while those low in this trait tend to be more competitive and even manipulative.
• Conscientiousness: Standard features of this dimension include high levels of thoughtfulness, with good impulse control and goal-directed behaviors. Those high on conscientiousness tend to be organized and mindful of details.
• Neuroticism: Neuroticism is a trait characterized by sadness, moodiness, and emotional instability. Individuals who are high in this trait tend to experience mood swings, anxiety, moodiness, irritability, and sadness. Those low in this trait tend to be more stable and emotionally resilient. This trait is sometimes inversely reported as “emotional stability.”  The Prosper database uses the “emotional stability” terminology.
• Openness: This trait features characteristics such as imagination and insight, and those high in this trait also tend to have a broad range of interests. People who are high in this trait tend to be more adventurous and creative. People low in this trait are often much more traditional and may struggle with abstract thinking.

Table 16 shows a comparison of sports gamblers by the five personality traits. All five are statistically different. The biggest differences are gamblers are more competitive and more extravagant with less impulse control. Gamblers also have higher sociability, are more traditional, and are less likely to think abstractly. They are also more emotionally stable and resilient.

A non-cognitive predictor of success in life, such as grit, like having a clear inner compass that guides all your decisions and actions. Grit is defined as the disposition to demonstrate perseverance and passion for long-term goals (Angela Duckworth, Grit: The Power of Passion and Perseverance , Scribner, 2016). Passion is a deep, enduring knowledge of what you want. Perseverance is hard work and resilience. All three predictors are expressed as a five-point scale, with higher values being stronger on the characteristics developed from a series of five-points. Prosper used the short-scale version.

Again, shown in Table 16 is the comparison of sports gamblers. All the differences are statistically different. Gamblers have lower overall grit, meaning they are less oriented toward long-term goals. The biggest difference for gamblers is lower passion, that is knowledge of what they want. Gamblers are higher in perseverance.

Impulsivity, as measured by agreement with the statement “Live for today because tomorrow is so uncertain,” also demonstrates a difference among gamblers, as shown in Table 17. Gamblers are much more likely to strongly agree with the statement and, conversely, strongly disagree. This reinforces the lack of long-term orientation among gamblers.

The Prosper Media Behavior and Influence study from January 2023 unveils the rising interest in sports betting, emphasizing the convergence of sports gambling and fantasy sports. The analysis explores demographic predictors, revealing age, gender, income, and marital status as key factors influencing sports betting engagement. Furthermore, the study uncovers correlations between sports program viewing, personality traits, leisure activities, and product consumption, painting a comprehensive picture of the diverse profile of sports gamblers.

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Betting Academy: How to research football bets

Before becoming a Sports Journalist for Free Super Tips, Aaron spent three years studying Sports Journalism at the University of Sunderland while taking in the Black Cats' 'glory years' under Martin O'Neill. Now back in Northern Ireland he turns niche stats into predictions for FST, while he's one of the few people on this island who is equally comfortable at Windsor Park and the Aviva.

When you’re placing a football bet, you want to be up on all the key statistics and information before you place it. You don’t want to back a team in terrible form or one missing their best player, so research is key.

Having shown you how to sign up with a bookie , now we’re going to run through all the key things to consider before you back a bet.

What information should I look out for?

Modern football is analysed from every angle possible, so the key thing isn’t finding data about the beautiful game, it’s knowing what to look for.

First things first, you’ll want to know the latest team news before you place a bet on a game. You may want to back a team on a hot streak, but would you still have faith in them if they were missing their star player or set to heavily rotate their side?

As well as we can track a team’s fortunes across a season, modern sides have deep squads and rotation is just a fact of life these days. That makes team news the first stop for bettors.

What to look for when placing a match result bet

Once you’ve checked the team news, results are next up. While statistical analysis of football has gotten much more complicated over the years, it’s always worth looking at the form of both sides.

Next up you want to check the home and away results of both sides. No matter what league you check, home advantage becomes clear over the course of a season. On top of that, 12 months without fans in stadiums also showed that home support is an important factor to consider.

A team could have a strong overall record, but sometimes there can be a massive gap between results at home and away. Most divisions will feature at least one team who earn around 70% of their points at home, while you can also sometimes find that outlier team who are better on the road.

What else should I watch out for?

One good thing to check is how teams fare against opponents from certain sections of the table. You might find a team in form who have lost all their clashes with the top six. Alternatively, you might see a seemingly inconsistent team who have a great record against the bottom five or six.

Expected Goals data is a dividing issue with football fans but it’s a useful thing to check to see how creative a team is. Often xG will highlight teams who are playing well but not getting results, or vice versa. That’s a good way for you to find some good betting value, so it’s not something to avoid.

What to look for when placing a goals bet

Goals can be an important factor in match result betting too, given that a team who tend to draw a blank in front of goal aren’t going to be your go-to winners. However, you’re more likely to track a team’s scoring form for a both teams to score or match goals bet.

Many sites also track the percentage of a team’s games which have seen both teams score, while you’ll want to take a look at recent scoring form too. You may want to back two of the league’s leading scorers, but it’s worth checking one of them hasn’t gone off the boil of late.

What else do I need to know?

Before you start betting, it’s important to be aware of the dangers around gambling. We are committed to responsible gambling and want to ensure that you remain in control of your gambling and keep it safe and enjoyable.

For more information around safer gambling and the problems to watch out for, you can see our guidelines here .

Now you know what statistics to look for, but how do you know where to look? See the best free betting resources the internet has to offer in our complete guide .

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How to Research for a Football Bet: 5 Things to Look for

Jonny Vito / January 2, 2024

Creating a winning football betting strategy might be difficult. Even if you do succeed, it does not mean you will simply receive your earnings. It is critically important to do things right in order to get profits out of your online games betting . But how does that work in practice?

Monetize Your Football Bets

You will hardly be able to monetize your bets without proper research and preparation. And there are several details to keep on your radar depending on the markets chosen. Let’s be more specific and go over the research process.

#1 — Examine the Long-Term Performance of Both Teams

This is a straightforward step; yet many people underestimate its significance. The long-term performance of both teams is the best approach to determine their average performance. Certain bookmakers may under-price a well-known team simply because punters believe they would win. Sometimes a team like Manchester United struggles away to Sunderland, but the bookmakers don’t reflect this in their odds because they want to pull people in who only bet on the big names.

The specific time range depends on what you’re searching for, but it should be at least a couple of months, if not a year. This will provide you an excellent foundation to build on when you delve into further detail later. The crucial questions here are how the team performs in terms of goals scored, goals allowed, playing at home or away (depending on the game), results against teams comparable to the next opponent, etc.

#2 — Examine the Short-Term Trends

After you’ve grasped the overall picture, it’s time to go deeper and determine the current condition of both teams. As we all know, confidence is everything in sports, and some players might appear to be world beaters. That’s why short-term patterns are particularly essential.

Take a look at each team’s recent 5-10 games; this should be enough for you to understand what to expect. Again, metrics such as goals scored, goals surrendered, average possession, and form of the greatest players should be considered. It’s a good idea to read a short match report for each of the games if you haven’t already; it is the best way to bet on football .

#3 — Read Team News

Almost every punter understands that you should look at the list of suspended, injured, and questionable players. A team that is without its top center back, for example, may struggle against an offensive opponent yet do well against a club that tends to sit back.

Of course, you should consider who will fill in for the injured players. How did their substitutes fare the previous time they appeared? Are they simply benchwarmers or squad players who receive enough minutes to stay in shape? These and other questions must be addressed.

Another point is frequently overlooked. The schedules of both clubs are critical as the number of games played per season presently necessitates rotation. So check out each team’s previous few games and what’s coming ahead. It should tell you if the manager will start his strongest lineup or try to rotate it.

#4 — Watch Prior Matches of the Two Teams

The next step would be to look at how both teams have done in their previous matches. The most recent games are the most revealing, but recent statistics should not be overlooked. Another thing you may notice is that particular teams or even certain players may have a strong streak against a specific opponent. Plenty of instances can be seen in the English Premier League, where Sunderland has been on a roll over local rival Newcastle in recent years. The Magpies are also a favorite opponent of Arsenal striker Olivier Giroud, who regularly scores against them.

#5 — Pay Attention to the Experts

Nowadays, there are so many different points of view on the Internet that it may be overwhelming. Most of them will merely confuse you and add little to your analysis. However, there are certain professionals who may be valuable. There are those who are adept at evaluating and forecasting football matches, whether they are successful punters or well-known journalists.

We don’t advocate exactly copying someone else’s viewpoint, but reading a preview isn’t a terrible idea. Seeing things from a fresh viewpoint may support your own assumptions or reveal a new angle you were unaware of.

Bet and Win

Proper research will put you closer to the long-awaited football bets. So take your time and arm yourself with the key data for your next football betting session.

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Open Access

Peer-reviewed

Research Article

A statistical theory of optimal decision-making in sports betting

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Dept of Biomedical Engineering, City College of New York, New York, NY, United States of America

• Jacek P. Dmochowski

• Published: June 28, 2023
• https://doi.org/10.1371/journal.pone.0287601
• Peer Review
• Reader Comments

The recent legalization of sports wagering in many regions of North America has renewed attention on the practice of sports betting. Although considerable effort has been previously devoted to the analysis of sportsbook odds setting and public betting trends, the principles governing optimal wagering have received less focus. Here the key decisions facing the sports bettor are cast in terms of the probability distribution of the outcome variable and the sportsbook’s proposition. Knowledge of the median outcome is shown to be a sufficient condition for optimal prediction in a given match, but additional quantiles are necessary to optimally select the subset of matches to wager on (i.e., those in which one of the outcomes yields a positive expected profit). Upper and lower bounds on wagering accuracy are derived, and the conditions required for statistical estimators to attain the upper bound are provided. To relate the theory to a real-world betting market, an empirical analysis of over 5000 matches from the National Football League is conducted. It is found that the point spreads and totals proposed by sportsbooks capture 86% and 79% of the variability in the median outcome, respectively. The data suggests that, in most cases, a sportsbook bias of only a single point from the true median is sufficient to permit a positive expected profit. Collectively, these findings provide a statistical framework that may be utilized by the betting public to guide decision-making.

Citation: Dmochowski JP (2023) A statistical theory of optimal decision-making in sports betting. PLoS ONE 18(6): e0287601. https://doi.org/10.1371/journal.pone.0287601

Editor: Baogui Xin, Shandong University of Science and Technology, CHINA

Received: December 19, 2022; Accepted: June 8, 2023; Published: June 28, 2023

Copyright: © 2023 Jacek P. Dmochowski. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data is available at https://github.com/dmochow/optimal_betting_theory .

Funding: The author received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The practice of sports betting dates back to the times of Ancient Greece and Rome [ 1 ]. With the much more recent legalization of online sports wagering in many regions of North America, the global betting market is projected to reach 140 billion USD by 2028 [ 2 ]. Perhaps owing to its ubiquity and market size, sports betting has historically received considerable interest from the scientific community [ 3 ].

A topic of obvious relevance to the betting public, and one that has also been the subject of multiple studies, is the efficiency of sports betting markets [ 4 ]. While multiple studies have reported evidence for market inefficiencies [ 5 – 11 ], others have reached the opposite conclusion [ 12 , 13 ]. The discrepancy may signify that certain, but not all, sports markets exhibit inefficiencies. Research into sports betting has also revealed insights into the utility of the “wisdom of the crowd” [ 14 – 16 ], the predictive power of market prices [ 17 – 20 ], quantitative rating systems [ 21 , 22 ], and the important finding that sportsbooks exploit public biases to maximize their profits [ 13 , 23 ].

Indeed, the decisions made by sportsbooks to set the offered odds and payouts have been previously analyzed [ 13 , 23 , 24 ]. On the other hand, arguably less is known about optimality on the side of the bettor . The classic paper by Kelly [ 25 ] provides the theory for optimizing betsize (as a function of the likelihood of winning the bet) and can readily be applied to sports wagering. The Kelly bet sizing procedure and two heuristic bet sizing strategies are evaluated in the work of Hvattum and Arntzen [ 26 ]. The work of Snowberg and Wolfers [ 27 ] provides evidence that the public’s exaggerated betting on improbable events may be explained by a model of misperceived probabilities. Wunderlich and Memmert [ 28 ] analyze the counterintuitive relationship between the accuracy of a forecasting model and its subsequent profitability, showing that the two are not generally monotonic. Despite these prior works, idealized statistical answers to the critical questions facing the bettor, namely what games to wager on, and on what side to bet, have not been proposed. Similarly, the theoretical limits on wagering accuracy, and under what statistical conditions they may be attained in practice, are unclear.

To that end, the goal of this paper is to provide a statistical framework by which the astute sports bettor may guide their decisions. Wagering is cast in probabilistic terms by modeling the relevant outcome (e.g. margin of victory) as a random variable. Together with the proposed sportsbook odds, the distribution of this random variable is employed to derive a set of propositions that convey the answers to the key questions posed above. This theoretical treatment is complemented with empirical results from the National Football League that instantiate the derived propositions and shed light onto how closely sportsbook prices deviate from their theoretical optima (i.e., those that do not permit positive returns to the bettor).

Importantly, it is not an objective of this paper to propose or analyze the utility of any specific predictors (“features”) or models. Nevertheless, the paper concludes with an attempt to distill the presented theorems into a set of general guidelines to aid the decision making of the bettor.

Problem formulation: “Point spread” betting

For positive s (home team favored), the home team is said to “cover the spread” if m > s , whereas the visiting team has “beat the spread” otherwise. Conversely, for negative s (visiting team favored), the visiting team covers the spread if m < s , and the home team has beat the spread otherwise. The home (visiting) team is said to win “against the spread” if m − s is positive (negative).

Denote the profit (on a unit bet) when correctly wagering on the home and visiting teams by ϕ h and ϕ v , respectively. Assuming a bet size of b placed on the home team, the conventional payout structure is to award the bettor with b (1 + ϕ h ) when m > s . The entire wager is lost otherwise. The total profit π is thus bϕ h when correctly wagering on the home team (− b otherwise). When placing a bet of b on the visiting team, the bettor receives b (1 + ϕ v ) if m < s and 0 otherwise. Typical values of ϕ h and ϕ v are 100/110 ≈ 0.91, corresponding to a commission of 4.5% charged by the sportsbook.

In practice, the event m = s (termed a “push”) may have a non-zero probability and results in all bets being returned. In keeping with the modeling of m by a continuous random variable, here it is assumed that P ( m = s ) = 0. This significantly simplifies the development below. Note also that for fractional spreads (e.g. s = 3.5), the probability of a push is indeed zero.

Wagering to maximize expected profit.

Consider first the question of which team to wager on to maximize the expected profit. As the profit scales linearly with b , a unit bet size is assumed without loss of generality.

Corollary 1 . Assuming equal payouts for home and visiting teams ( ϕ h = ϕ v ), maximization of expected profit is achieved by wagering on the home team if and only if the spread is less than the median margin of victory .

A subtle but important point is that knowledge of which side to bet on for each match is insufficient for maximizing overall profit. The reason is that even if wagering on the side with higher expected profit, it is possible (and in fact quite common, see empirical results below) that the “optimal” wager carries a negative expectation. Thus, an understanding of when wagering should be avoided altogether is required. This is the subject of the theorem below.

It is instructive to consider the conditions above for typical values of ϕ h and ϕ v . When wagering on the home team with ϕ h = 0.91, positive expectation requires the spread to be no larger than the 0.476 quantile of m . When wagering on the visiting team, the spread must exceed the 0.524 quantile. This means that, if the spread is contained within the 0.476-0.524 quantiles of the margin of victory, wagering should be avoided . Practically, it is thus important to obtain estimates of this interval and its proximity to the median score in units of points .

The result of Theorem 2 is reminiscent of the “area of no profitable bet” scenario described in [ 28 ]. Whereas the latter result is presented in terms of outcome probabilities estimated by the bettor and the sportsbook, Theorem 2 here delineates the conditions under which the sportsbook’s point spread assures a negative expectation on the bettor’s side.

Optimal estimation of the margin of victory.

Theorem 3 . Define an “error” as a wager that is placed on the team that loses against the spread. The probability of error is bounded according to : min{ F m ( s ), 1 − F m ( s )} ≤ p (error) ≤ max{ F m ( s ), 1 − F m ( s )}.

The result of Theorem ( 8 ) provides both the best- and worst-case scenario of a given wager. When F m ( s ) is close to 1/2, both the minimum and maximum error rates are near 50%, and wagering is reduced to an event akin to a coin flip. On the other hand, when the true median is far from the spread (i.e., F m ( s ) deviates from 1/2), the minimum and maximum error rates diverge, increasing the highest achievable accuracy of the wager.

Optimality in “moneyline” wagering

Corollary 4 . Define an “error” as a wager that is placed on the team that loses the match outright. The probability of error in moneyline wagering is bounded according to : min{ F m (0), 1 − F m (0)} ≤ p (error) ≤ max{ F m (0), 1 − F m (0)}.

Notice that optimal decision-making in moneyline wagers requires knowledge of quantiles that may be near 0 (if ϕ v ≫ ϕ h ) or near 1 (if ϕ h ≫ ϕ v ). More subtly, the required quantiles will differ for matches that exhibit different payout ratios. For example, a match with two even sides will require knowledge of central quantiles, while a match with a 4:1 favorite will require knowledge of the 80th and 20th percentiles. The implications of this property on quantitative modeling are described in the Discussion .

The moneyline wagering considered in this section is a two-alternative bet that is popular in North American sports. In European betting markets, the most common type of wager is the three-alternative “Home-Draw-Away” bet where there is no point spread and the task of the bettor is to forecast one of the three potential outcomes: m > 0, m = 0, or m < 0, each of which are endowed with a payout (see, for example, [ 26 , 29 , 30 ]). Clearly the the probability p ( m = 0) will be non-zero in this context. As a result, the methodology here, which models m by a continuous random variable, cannot be straightforwardly applied to the case of the Home-Draw-Away bet. The extension of the present findings to the case of multi-way bets with discrete m is a potential topic of future research.

Optimality in “over-under” betting

The following two results may be proven by replacing m with τ , ϕ h with ϕ o , and ϕ v with ϕ u in the Proofs of Theorems 1 and 2, respectively.

In the special case of ϕ o = ϕ u , one should bet on the over only if and only if the sportsbook total τ falls below the median of t .

Define F t ( τ ) as the CDF of the true point total evaluated at the sportsbook’s proposed total. The following corollary may be proven by following the Proof of Theorem 3.

Corollary 8 . Define an “error” in over-under betting as a wager that is placed on the “over” when t < τ or on the “under” when t > τ. The probability of error is bounded according to : min{ F t ( τ ), 1 − F t ( τ )} ≤ p (error) ≤ max{ F t ( τ ), 1 − F t ( τ )}.

Empirical results from the National Football League

In order to connect the theory to a real-world betting market, empirical analyses utilizing historical data from the National Football League (NFL) were conducted. The margins of victory, point totals, sportsbook point spreads, and sportsbook point totals were obtained for all regular season matches occurring between the 2002 and 2022 seasons ( n = 5412). The mean margin of victory was 2.19 ± 14.68, while the mean point spread was 2.21 ± 5.97. The mean point total was 44.43 ± 14.13, while the mean sportsbook total was 43.80 ± 4.80. The standard deviation of the margin of victory is nearly 7x the mean, indicating a high level of dispersion in the margin of victory, perhaps due to the presence of outliers. Note that the standard deviation of a random variable provides an upper bound on the distance between its mean and median [ 31 ], which is relevant to the problem at hand.

To estimate the distribution of the margin of victory for individual matches, the point spread s was employed as a surrogate for θ . The underlying assumption is that matches with an identical point spread exhibit margins of victory drawn from the same distribution. Observations were stratified into 21 groups ranging from s o = −7 to s o = 10. This procedure was repeated for the analysis of point totals, where observations were stratified into 24 groups ranging from t o = 37 to t o = 49.

How accurately do sportsbooks capture the median outcome?

It is important to gain insight into how accurately the point spreads proposed by sportsbooks capture the median margin of victory. For each stratified sample of matches, the median margin of victory was computed and compared to the sample’s point spread. The distribution of margin of victory for matches with a point spread s o = 6 is shown in Fig 1a , where the sample median of 4.34 (95% confidence interval [2.41,6.33]; median computed with kernel density estimation to overcome the discreteness of the margin of victory; confidence interval computed with the bootstrap) is lower than the sportsbook point spread. However, the sportsbook value is contained within the 95% confidence interval.

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( a ) The distribution of margin of victory for National Football League matches with a consensus sportsbook point spread of s = 6. The median outcome of 4.26 (dashed orange line, computed with kernel density estimation) fell below the sportsbook point spread (dashed blue line). However, the 95% confidence interval of the sample median (2.27-6.38) contained the sportsbook proposition of 6. ( b ) Same as (a), but now showing the distribution of point total for all matches with a sportsbook point total of 46. Although the sportsbook total exceeded the median outcome by approximately 1.5 points, the confidence interval of the sample median (42.25-46.81) contained the sportsbook’s proposition. ( c ) Combining all stratified samples, the sportsbook’s point spread explained 86% of the variability in the median margin of victory. The confidence intervals of the regression line’s slope and intercept included their respective null hypothesis values of 1 and 0, respectively. ( d ) The sportsbook point total explained 79% of the variability in the median total. Although the data hints at an overestimation of high totals and underestimation of low totals, the confidence intervals of the slope and intercept contained the null hypothesis values.

https://doi.org/10.1371/journal.pone.0287601.g001

Aggregating across stratified samples, the sportsbook point spread explained 86% of the variability in the true median margin of victory ( r 2 = 0.86, n = 21; Fig 1c ). Both the slope (0.93, 95% confidence interval [0.81,1.04]) and intercept (-0.41, 95% confidence interval [-1.03,0.16]) of the ordinary least squares (OLS) line of best fit (dashed blue line) indicate a slight overestimation of the margin of victory by the point spread. This is most apparent for positive spreads (i.e., a home favorite). Nevertheless, the confidence intervals of both the slope and intercept did include the null hypothesis values of 1 and 0, respectively. The data for all sportsbook point spreads with at least 100 matches is provided in Table 1 .

Regular season matches from the National Football League occurring between 2002-2022 were stratified according to their sportsbook point spread. Each set of 3 grouped rows corresponds to a subsample of matches with a common sportsbook point spread. The “level” column indicates whether the row pertains to the 95% confidence interval (0.025 and 0.975 quantiles) or the mean value across bootstrap resamples. The dependent variables include the 0.476, 0.5, and 0.524 quantiles, as well as the expected profit of wagering on the side with higher likelihood of winning the bet for hypothetical point spreads that deviate from the median outcome by 1, 2, and 3 points, respectively.

https://doi.org/10.1371/journal.pone.0287601.t001

The distribution of observed point totals for matches with a sportsbook total of τ = 46 is shown in Fig 1b , where the computed median of 44.45 (95% confidence interval [42.25,46.81]) is suggestive of a slight overestimation of the true total. Combining data from all samples, the sportsbook point total explained 79% of the variability in the median point total ( r 2 = 0.79, n = 24; Fig 1d ).

Interestingly, the data hints at the sportsbook’s proposed point total underestimating the true total for relatively low totals (i.e., black line is below the blue for sportsbook totals below 43), while overestimating the total for those matches expected to exhibit high scoring (i.e., black line is above the blue line for sportsbook totals above 43). Note, however, that the confidence intervals of the regression line (slope: [0.72,1.02], intercept: [-1.14, 12.05]) did contain the null hypothesis values. The data for all sportsbook point total with at least 100 samples is provided in Table 2 .

Matches were stratified into 24 subsamples defined by the value of the sportsbook total. The dependent variables are the 0.476, 0.5, and 0.524 quantiles of the true point total, as well as the expected profit of wagering conditioned on the amount of bias in the sportsbook’s total.

https://doi.org/10.1371/journal.pone.0287601.t002

Do sportsbook estimates deviate from the 0.476-0.524 interval?

In the common case of ϕ = 0.91, a positive expected profit is only feasible if the point spread (or point total) is either below the 0.476 or above the 0.524 quantiles of the outcome’s distribution. It is thus interesting to consider how often this may occur in a large betting market such as the NFL. To that end, the 0.476 and 0.524 quantiles of the margin of victory were estimated in each stratified sample (horizontal bars in Fig 2 ; the point spread is indicated with an orange marker; all quantiles are listed in Table 1 ).

With a standard payout of ϕ = 0.91, achieving a positive expected profit is only feasible if the sportsbook point spread falls outside of the 0.476-0.524 quantiles of the margin of victory. The 0.476 and 0.524 quantiles were thus estimated for each stratified sample of NFL matches. Light (dark) black bars indicate the 95% confidence intervals of the 0.476 (0.524) quantiles. Orange markers indicate the sportsbook point spread, which fell within the quantile confidence intervals for the large majority of stratifications. An exception was s = 5, where the sportsbook appeared to overestimate the margin of victory. For two other stratifications ( s = 3 and s = 10), the 0.524 quantile tended to underestimate the sportsbook spread, with the 95% confidence intervals extending to just above the spread.

https://doi.org/10.1371/journal.pone.0287601.g002

For the majority of samples, the confidence intervals of the 0.476 and 0.524 quantiles contained the sportsbook spread. One exception was the spread s = 5, where the margin of victory fell below the sportsbook value (95% confidence interval of the 0.524 quantile: [0.87,4.85]). The margin of victory for s = 3 (95% confidence interval of the 0.524 quantile: [0.78,3.08]) and s = 10 (95% confidence interval of the 0.524 quantile: [6.42,10.06]) also tended to underestimate the sportsbook spread, with the confidence intervals just containing the sportsbook value.

The analysis was repeated for point totals ( Fig 3 , all quantiles listed in Table 2 ). All but one stratified sample exhibited 0.476 and 0.524 quantiles whose confidence intervals contained the sportsbook total ( t = 47, [41.59, 45.42]). Examination of the sample quantiles suggests that NFL sportsbooks are very adept at proposing point totals that fall within 2.4 percentiles of the median outcome.

The 0.476 and 0.524 quantiles of the true point total were estimated for each stratified sample of NFL matches. For all but one stratification ( t = 47, 95% confidence interval [41.59-45.42], sportsbook overestimates the total), the confidence intervals of the sample quantiles contained the sportsbook proposition. Visual inspection of the data suggests that, in the NFL betting market at least, sportsbooks are very adept at proposing totals that fall within the critical 0.476-0.524 quantiles.

https://doi.org/10.1371/journal.pone.0287601.g003

How large of a discrepancy from the median is required for profit?

In practice, it is desirable to have an understanding of how large of a sportsbook bias, in units of points, is required to permit a positive expected profit. To address this, the value of the empirically measured CDF of the margin of victory was evaluated at offsets of 1, 2, and 3 points from the true median in each direction. The resulting value was then converted into the expected value of profit (see Materials and Methods ). The computation was performed separately within each stratified sample, and the height of each bar in Fig 4 indicates the hypothetical expected profit of a unit bet when wagering on the team with the higher probability of winning against the spread . For the sake of clarity, only the four largest samples ( s ∈ {−3, 2.5, 3, 7}) are shown in the Figure, with data for all samples listed in Table 1 .

In order to estimate the magnitude of the deviation between sportsbook point spread and median margin of victory that is required to permit a positive profit to the bettor, the hypothetical expected profit was computed for point spreads that differ from the true median by 1, 2, and 3 points in each direction. The analysis was performed separately within each stratified sample, and the figure shows the results of the four largest samples. For 3 of the 4 stratifications, a sportsbook bias of only a single point is required to permit a positive expected return (height of the bar indicates the expected profit of a unit bet assuming that the bettor wagers on the side with the higher probability of winning; error bars indicate the 95% confidence intervals as computed with the bootstrap). For a sportsbook spread of s = 3 (dark black bars), the expected profit on a unit bet is 0.021 [0.008-0.035], 0.094 [0.067-0.119], and 0.166 [0.13-0.2] when the sportsbook’s bias is +1, +2, and +3 points, respectively (mean and confidence interval over 500 bootstrap resamples).

https://doi.org/10.1371/journal.pone.0287601.g004

The expected profit is negative (i.e., ( ϕ − 1)/2 = −0.045) when the spread equals the median (center column). Interestingly however, for 3 of the 4 largest stratified samples, a positive profit is achievable with only a single point deviation from the median in either direction (the confidence intervals indicated by error bars do not extend into negative values). Averaged across all n = 21 stratifications, the expected profit of a unit bet is 0.022 ± 0.011, 0.090 ± 0.021, and 0.15 ± 0.030 when the spread exceeds the median by 1, 2, and 3 points, respectively (mean ± standard deviation over n = 21 stratifications, each of which is an average over 1000 bootstrap ensembles). Similarly, the expected return is 0.023 ± 0.013, 0.089 ± 0.026, and 0.15 ± 0.037 when the spread undershoots the median by 1, 2, and 3 points respectively. This indicates that sportsbooks must estimate the median outcome with high precision in order to prevent the possibility of positive returns.

The analysis was repeated on the data of point totals. A deviation from the true median of only 1 point was sufficient to permit a positive expected profit in all four of the largest stratifications ( Fig 5 ; t ∈ {41, 43, 44, 45}; error bars indicate 95% confidence intervals; data for all samples is provided in Table 2 ). When the sportsbook overestimates the median total by 1, 2, and 3 points, the expected profit on a unit bet is 0.014 ± 0.0071, 0.073 ± 0.014, and 0.13 ± 0.020, respectively (mean ± standard deviation over n = 24 samples, each of which is a average over 1000 bootstrap resamples). When the sportsbook underestimates the median, the expected profit on a unit bet is 0.015±0.0071, 0.076± 0.014, and 0.14± 0.020, for deviations of 1, 2, and 3 points, respectively. Note that despite the dependent variable having a larger magnitude (compared to margin of victory), the required sportsbook error to permit positive profit is the same as shown by the analysis of point spreads.

Vertical axis depicts the expected profit of an over-under wager, conditioned on the sportsbook’s posted total deviating from the true margin by a value of 1, 2, or 3 points (horizontal axis). The analysis was performed separately for each unique sportsbook total, and the figure displays the results for the four largest samples. A deviation from the true median of a single point permits a positive expected profit in all four of the depicted groups. For a sportsbook total of t = 44 (green bars), the expected profit on a unit bet is 0.015 [0.004-0.028], 0.075 [0.053-0.10], and 0.13 [0.10-0.17] when the sportsbook’s bias is +1, +2, and +3 points, respectively (mean and confidence interval over 500 bootstrap resamples).

https://doi.org/10.1371/journal.pone.0287601.g005

The theoretical results presented here, despite seemingly straightforward, have eluded explication in the literature. The central message is that optimal wagering on sports requires accurate estimation of the outcome variable’s quantiles. For the two most common types of bets—point spread and point total—estimation of the 0.476, 0.5 (median), and 0.524 quantiles constitutes the primary task of the bettor (assuming a standard commission of 4.5%). For a given match, the bettor must compare the estimated quantiles to the sportsbook’s proposed value, and first decide whether or not to wager ( Theorem 2 ), and if so, on which side ( Theorem 1 ).

The sportsbook’s proposed spread (or point total) effectively delineates the potential outcomes for the bettor ( Theorem 3 ). For a standard commission of 4.5%, the result is that if the sportsbook produces an estimate within 2.4 percentiles of the true median outcome, wagering always yields a negative expected profit— even if consistently wagering on the side with the higher probability of winning the bet . This finding underscores the importance of not wagering on matches in which the sportsbook has accurately captured the median outcome with their proposition. In such matches, the minimum error rate is lower bounded by 47.6%, the maximum error rate is upper bounded by 52.4%, and the excess error rate ( Theorem 4 ) is upper bounded by 4.8%.

The seminal findings of Kuypers [ 13 ] and Levitt [ 23 ], however, imply that sportsbooks may sometimes deliberately propose values that deviate from their estimated median to entice a preponderance of bets on the side that maximizes excess error. For example, by proposing a point spread that exaggerates the median margin of victory of a home favorite, the minimum error rate may become, for example, 45% (when wagering on the road team), and the excess error rate when wagering on the home team is 10%. In this hypothetical scenario, the sportsbook may predict that, due to the public’s bias for home favorites, a majority of the bets will be placed on the home team. The empirical data presented here hint at this phenomenon, and are in alignment with previous reports of market inefficiencies in the NFL betting market [ 5 , 32 – 35 ]. Namely, the sportsbook point spread was found to slightly overestimate the median margin of victory for some subsets of the data ( Fig 2 ). Indeed, the stratifications showing this trend were home favorites, agreeing with the idea that the sportsbooks are exploiting the public’s bias for wagering on the favorite [ 23 ].

The analysis of sportsbook point spreads performed here indicates that only a single point deviation from the true median is sufficient to allow one of the betting options to yield a positive expectation. On the other hand, realization of this potential profit requires that the bettor correctly, and systematically, identify the side with the higher probability of winning against the spread. Forecasting the outcomes of sports matches against the spread has been elusive for both experts and models [ 6 , 36 ]. Due to the abundance of historical data and user-friendly statistical software packages, the employment of quantitative modeling to aid decision-making in sports wagering [ 37 ] is strongly encouraged. The following suggestions are aimed at guiding model-driven efforts to forecast sports outcomes.

The argument against binary classification for sports wagering

The minimum error and minimum excess error rates defined in Theorems 3 and 4, respectively, are analogous to the Bayes’ minimum risk and Bayes’ excess risk in binary classification [ 38 ]. Indeed, one can cast the estimation of margin of victory in sports wagering as a binary classification problem, aiming to predict the event of “the home team winning against the spread”. Here this approach is not advocated. In conventional binary classification, the target variable (or “class label”) is static and assumed to represent some phenomenon (e.g. presence or absence of an object). In the context of sports wagering, however, the event m > s need not be uniform for different matches. For example, the event of a large home favorite winning against the spread may differ qualitatively from that of a small home “underdog” winning against the spread. Moreover, the sportsbook’s proposed point spread is a dynamic quantity. To illustrate the potential difficulty of utilizing classifiers in sports wagering, consider the case of a match with a posted spread of s = 4, where the goal is to predict the sign of m − 4. But now imagine that the the spread moves to s = 3. The resulting binary classification problem is now to predict the sign of m − 3, and it is not straightforward to adapt the previously constructed classifier to this new problem setting. One may be tempted to modify the bias term of the classifier, but it is unclear by how much it should be adjusted, and also whether a threshold adjustment is in fact the optimal approach in this scenario. On the other hand, by posing the problem as a regression, it is trivial to adapt one’s optimal decision: the output of the regression can simply be compared to the new spread.

The case for quantile regression

Conventional ordinary least-squares (OLS) regression yields estimates of the mean of a random variable, conditioned on the predictors. This is achieved by minimizing the mean squared error between the predicted and target variable.

The findings presented here suggest that conventional regression may be a sub-optimal approach to guiding wagering decisions, whose optimality relies on knowledge of the median and other quantiles. The presence of outliers and multi-modal distributions, as may be expected in sports outcomes, increases the deviation between the mean and median of a random variable. In this case, the dependent variable of conventional regression is distinct from the median and thus less relevant to the decision-making of the sports bettor. The significance of this may be exacerbated by the high noise level on the target random variable, and the low ceiling on model accuracy that this imposes.

Therefore, a more suitable approach to quantitative modeling in sports wagering is to employ quantile regression, which estimates a random variable’s quantiles by minimizing the quantile loss function [ 39 ]. Any features that are expected to forecast sports outcomes could be provided as the predictors in a quantile regression to produce estimates that are aligned with the bettor’s objectives: to avoid wagering on matches with negative expectation for both outcomes, and to wager on the side with zero excess error.

Potential challenges in moneyline wagering

Bias-variance in sports wagering

The view that low variance implies “simple” models has recently been challenged in the context of artificial neural networks [ 41 ]. Nevertheless, the desire for low-variance, high-bias modeling in sports wagering does suggest the preference for simpler models. Thus, it is advocated to employ a limited set of predictors and a limited capacity of the model architecture. This is expected to translate to improved generalization to future data.

Sport-specific considerations

The three types of wagers considered in this work—point spread, moneyline, and over-under—are the most popular bet types in North American sports. The empirical analysis employed data from the National Football League (NFL). One unique aspect of American football is its scoring system, in which the points accumulated by each team increase primarily in increments of 3 or 7 points. The structure of the scoring imposes constraints on the distribution of the margin of victory m . For example, in American Football, the distribution of the margin of victory is expected to exhibit local maxima near values such as: ±3, ±7, ±10. In the case of games in the National Basketball Association (NBA), the most common margins of victory tend to occur in the 5-10 interval, reflecting the overall higher point totals in basketball and its most common point increments (2 and 3). As a result, the shape and quantiles of the distribution of m may vary qualitatively between the NBA and NFL.

As a final illustrative example of the importance of the quantiles of m , consider the hypothetical scenario of two American football teams playing a match whose parameters θ have been exactly matched three times previously. In those past matches, the outcomes were m = 3, m = 7, and m = 35. In this fictitious example, the median is 7 but the mean is 15. Now imagine that the point spread for the next match has been set to s = 10 (home team favored to win the match by 10 points). Assuming that one has committed to wagering on the match, the optimal decision is to bet on the visiting team, despite that fact that the home team has won the previous matches by an average of 15 points.

Materials and methods

All analysis was performed with custom Python code compiled into a Jupyter Notebook (available at https://github.com/dmochow/optimal_betting_theory ). The figures and tables in this manuscript may be reproduced by executing the notebook.

Empirical data

Historical data from the National Football League (NFL) was obtained from bettingdata.com , who has courteously permitted the data to be shared on the repository listed above. All regular season matches from 2002 to 2022 were included in the analysis ( n = 5412). The data set includes point spreads and point totals (with associated payouts) from a variety of sportsbooks, as well as a “consensus” value. The latter was utilized for all analysis.

Data stratification

In order to estimate quantiles of the distributions of margin of victory and point totals from heterogeneous data (i.e., matches with disparate relative strengths of the home and visiting teams), the sportsbook point spread and sportsbook point total were used as a surrogate for the parameter vector defining the identity of each individual match ( θ in the text). This permitted the estimation of the 0.476, 0.5, and 0.524 quantiles over subsets of congruent matches.

Only spreads or totals with at least 100 matches in the dataset were included, such that estimation of the median would be sufficiently reliable. To that end, data was stratified into 21 samples for the analysis of margin of victory: {-7, -6, -3.5, -3, -2.5, -2, -1, 1, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 10) and 24 samples for the analysis of point totals (37, 37.5, 38, 39, 39.5, 40, 40.5, 41, 41.5, 42, 42.5, 43, 43.5, 44, 44.5, 45, 45.5, 46, 46.5, 47, 47.5, 48, 48.5, 49 }. This resulted in the employment of n = 3843 matches in the analysis of point spreads and n = 4300 matches in the analysis of point totals.

Note that the stratification process did not account for varying payouts, for example −110 versus −105 in the American odds system, as this would greatly increase the number of stratified samples while decreasing the number of matches in each sample. It is likely that the resulting error is negligible, however, due to the likelihood of the payout discrepancy being fairly balanced across the home and visiting teams.

Median estimation

In order to overcome the discrete nature of the margins of victory and point totals, kernel density estimation was employed to produce continuous quantile estimates. The KernelDensity function from the scikit-learn software library was employed with a Gaussian kernel and a bandwidth parameter of 2. For the margin of victory, the density was estimated over 4000 points ranging from -40 to 40. For the analysis of point totals, the density was estimated over 4000 points ranging from 10 to 90. The regression analysis relating median outcome to sportsbook estimates ( Fig 1 ) was performed with ordinary least squares (OLS).

Confidence interval estimation

In order to generate variability estimates for the 0.476, 0.5, and 0.524 quantiles of the margin of victory and point total, the bootstrap [ 42 ] technique was employed. 1000 resamples of the same size as the original sample were generated in each case. The confidence intervals were then constructed as the interval between the 2.5 and 97.5 percentiles of the relevant quantity. Bootstrap resampling was also employed to derive confidence intervals on the regression parameters relating the median outcomes to sportsbook spreads or totals ( Fig 1 ), as well as the confidence intervals on the expected profit of wagering conditioned on a fixed sportsbook bias (Figs 4 and 5 ).

Expected profit estimation

To model the idealized case of always placing the wager on the side with the higher probability of winning against the spread, the reported expected profit was taken as the maximum of the two expected values in ( 15 ). The analogous procedure was conducted for the analysis of point totals.

Acknowledgments

The author would like to thank Ed Miller and Mark Broadie for fruitful discussions during the preparation of the manuscript. The author would also like to acknowledge the effort of the reviewers, in particular Fabian Wunderlich, for providing many helpful comments and critiques throughout peer review.

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How to research football bets in 2019 – Key tips, tricks & strategies

Football research and analysis is vital if you want to succeed with your betting in 2019.

Despite the importance, bettors are often unsure of what football research to do and the best methods to use.

But not to worry. In this article, we’ll look at the key things to analyse , the best strategies to employ and what this means for your football betting .

Let’s get started.

The popularity of football betting

You probably don’t need me to tell you that betting on football is incredibly popular in the UK and Europe.

In Britain alone, £250 is bet on football every second . When you add in Europe and other countries around the world this soon becomes a ridiculous number!

It just goes to show how popular betting on football really is.

Football punters are often on the lookout for ways to increase the number of winning bets they place.

Whilst there are various strategies you can employ to win more footy bets , one of the best methods is research and analysis .

It’s a proven fact that bettors who complete football research are more likely to win their bets than those who bet on gut instinct.

So just how important is football analysis in 2019 and beyond?

Football research and analysis

Let’s not dodge the bullet, placing winning bets on a regular basis is not easy and don’t believe anyone who says it is.

If it was, everyone would be winning football bets.

However, if you invest time and effort , you can increase your chances of placing winning bets more often.

That’s where football research and analysis comes into its own.

So we know research and analysis is crucial for your betting strategy, but what should you look for?

Key areas to research

One of the main questions you’re probably asking is what areas you need to research and analyse?

The aim is to find valuable markets where you think the bookmakers have overpriced the odds.

Whilst these markets don’t come around too often, it’s important you spot the opportunities and act quickly when they do.

Here are three areas you should definitely consider when researching your football bets:

Recent form

Head to head results, team news and injuries.

Let’s check out each of these in more detail.

To kick off your football research I recommend you start with recent form and latest performances .

Looking at recent results and overall performances is one of the best ways to assess how good a team really is.

If you can avoid it, don’t just look at results as they can sometimes be deceiving. A team may get a result on paper but perform poorly in the game.

You might be wondering how far back you should consider a team’s form. In short, the longer the better . I would say the minimum is the start of the current season.

Overall, looking into the recent form of a team is one of the best bits of research you can do for your football betting.

It gives you a great insight into how a team is performing and whether they are worth betting on.

Another aspect you should consider in your football research is head to head results .

Sometimes recent form is thrown out the window when it comes to certain fixtures. This is especially the case when fierce rivals play each other.

The Manchester Derby is a great example. These games don’t often play out as you’d expect.

On the other hand, a team may have a great run of results but their next fixture is against a bogey team that they don’t often perform well against.

This is the kind of information you can analyse when looking at previous meetings.

Whilst you shouldn’t always rely on head to head data, it still gives you a good idea of how teams perform against each other.

There’s no denying it, team selection and injuries can play a big part in the outcome of a fixture.

That means it’s vital for you to keep a close eye on this information.

Teams can look and perform very differently with certain players included or missing.

For example, let’s say Harry Kane will miss a fixture for Tottenham . You’d probably determine their chances of winning would be significantly reduced without their main goalscorer.

It’s also important to consider the busy schedule that many teams face . Managers often rotate their squads for midweek games so this is something to bear in mind when looking at team selections.

Furthermore, you should look at who’s going to fill in for injured or rested players. At big teams like Man City and Liverpool, they have great squad depth so player quality doesn’t drop.

However, smaller teams that play in European leagues may struggle with two games a week.

This is all information you should consider when researching your football bets.

Obviously, bookmakers have access to this information and they take this into consideration when pricing the odds.

However, you’re looking for those opportunities where there’s more value available.

How much research is enough?

How long is a piece of string?

The more football research you do, the more informed you’ll be when it comes to picking bets.

I guess it comes to down to how much you want to win your bets.

Different methods to research football bets

So what methods can you use to research your footy bets? Here are a few options:

• Watch the latest games

Free information online

Paid services, watch the latest fixtures.

Arguably the easiest way to research your football bets is to watch recent games .

You get a great idea of how a team are performing when watching an event live.

You don’t need to watch every game, watching highlights on MOTD is often enough. It’s also free to air, meaning no expensive subscriptions to pay for.

If you can’t find the time to watch the latest games, you can research your football bets by reading information online .

What’s great about this method is that it’s generally free. Thankfully we live in an era when you can access an endless amount of information almost instantaneously so it doesn’t need to take that long.

You can find match reviews and previews at many different websites including the BBC, Skysports and Sporting Life to name a few.

These articles are often written by experts who know what they’re talking about, so they’re worthwhile listening to.

Last but not least, you can also use paid services to help you research your footy bets.

These websites often gather important information and statistics to help you pick bets.

You’ll often receive tips along with graphs and an endless amount of data directly to your inbox.

There are plenty of websites out there and you can check out our review of Betballers by clicking here .

Research, research, research

As you’ve probably gathered from reading this far, research is key to success in football betting .

The more informed you are, the better bets you’re likely to place which in turn should mean more profit in the long run .

Whilst research and analysis take time and effort, it’s vital if you want to succeed with your betting strategy in 2019.

As I mentioned earlier, I guess it comes down to how much you want to win your football bets.

What research do you do before placing football bets? Let me know by leaving a comment below right now.

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Expert Commentary

Sports betting in the US: A research roundup and explainer

We look at the landscape of legal sports betting in America, explain what the research says about how legalization affects tax revenues, and provide a brief history of the activity.

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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Clark Merrefield, The Journalist's Resource October 25, 2022

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On Nov. 8, Californians will vote on two ballot measures that would allow for different forms of sports betting in the state.

Proposition 26 would allow sports betting at licensed casinos and horse tracks on tribal lands and run by federally recognized Native American tribes.

Prop. 27 would allow tribes licensed to offer gambling and major gaming companies to offer online sports betting. These companies include FanDuel and DraftKings, which together make up roughly two-thirds of the U.S. online sports betting market.

“If both pass, they might both go into effect or the result could be decided in court, depending on which one gets more yes votes,” writes CalMatters economics reporter Grace Gedye in an article from June.

Although California is the only state with sports betting on the midterm ballot , it’s not the only state where sports betting is a topic of political discussion — and relevant for journalists across beats to understand. For example, Georgia gubernatorial candidate Stacey Abrams recently expressed support for legalized sports betting in her state. Abrams’ opponent, Gov. Brian Kemp, is opposed.

In Missouri, state lawmakers from both parties support legalizing sports betting , but Gov. Mike Parson is hesitant. Vermont lawmakers are considering taking up a sports betting bill during the next legislative session. Gubernatorial candidates in South Carolina and Texas support legal sports betting. In Florida, there is an ongoing lawsuit over whether the state should be allowed to give the Seminole Tribe the exclusive right to run online sports betting there.

Legal sports wagering in the U.S. has grown vertically in recent years — from less than $5 billion worth of bets placed in 2018 to $57 billion in 2021 — despite sports betting remaining illegal in nearly half of states. Sportsbooks, the entities that take sports bets, bring in about $4 billion yearly after wagers are settled.

The reason for this growth: a May 2018 Supreme Court ruling. Justice Samuel Alito, in delivering the 6-3 decision , reasoned that 1992 federal legislation banning states from allowing sports betting was unconstitutional.

Under the 1992 law, the Professional and Amateur Sports Protection Act, the federal government did not “make sports gambling itself federal crime,” Alito writes in the 2018 decision. “Instead, it allows the [U.S.] Attorney General, as well as professional and amateur sports organizations, to bring civil actions to enjoin violations.” Other than legislative powers the Constitution grants Congress, the federal government cannot “issue direct orders to state legislatures,” Alito writes. The majority interpreted the Professional and Amateur Sports Protection Act as doing so.

Here is how John Holden , an assistant professor of business at Oklahoma State University who has written extensively on sports gambling, explains the 2018 ruling:

“If the federal government wants to make sports betting illegal, they’re free to do so, but they can use the [Federal Bureau of Investigation] and the [Department of Justice] to enforce that,” Holden says. “They can’t tell a state legislature that you need to keep that law on the books and use your state police to go out and bust up gambling rings.”

A fundraising breakdown from the Los Angeles Times shows about $132 million has been raised to support Prop. 26, with about $43 million in opposition funding. Top backers include the Federated Indians of Graton Rancheria, the Pechanga Band of Indians and the Yocha Dehe Wintun Nation. Non-Native American casino and gaming interests are largely opposed — conversely, they have backed Prop. 27, which would open up sports betting to all gambling interests, not just Native American-run casinos.

Tribal gaming brings in nearly $40 billion a year across all tribes that operate gambling enterprises, according to the National Indian Gaming Commission . “Gaming operations have had a far-reaching and transformative effect on American Indian reservations and their economies,” write the authors of a 2015 paper about how the act affected tribal economic development. “Specifically, Indian gaming has allowed marked improvements in several important dimensions of reservation life.”

The landscape of legal sports betting

If California legalizes sports betting, it would represent a major coup for gaming interests in the state. In California, the most populous state, horse racing is the only legal form of sports betting.

Sports wagering is legal in 28 states plus the District of Columbia, according to a recent Washington Post analysis. Seven states prohibit online sports betting and only allow in-person wagers at licensed locations, such as casinos: Delaware, Maryland, Mississippi, Montana, New Mexico, North Carolina and North Dakota. Sports betting is legal but pending rollout in four states: Maine, Massachusetts, Nebraska and Ohio. Kansas is the most recent state to implement legal in-person and online sports gambling, as of Sept. 1.

States place a range of licensing fees on operators and tax rates on sports betting revenue, from a low of 6.75% in Nevada and Iowa to a high of 51% in New Hampshire and New York. States use tax revenues for a variety of purposes . Some, like Delaware, put sports wagering taxes toward their general fund. Colorado uses sports betting taxes to pay for its statewide water plan, Illinois funds transportation infrastructure and New York funds education programs.

In states where sports betting is legal, bettors can wager on nearly any major sporting event, both professional and amateur. For example, bettors can wager on the outcome of a baseball game, as well as events within the game, such as whether a particular player will hit a home run.

Polling indicates California may be unlikely to join the legal betting club. CalMatters reported earlier this month that despite various campaigns raising more than $440 million in marketing related to Props. 26 and 27, each measure is garnering support from less than a third of likely voters, according to October polling from the Institute of Governmental Studies at the University of California, Berkeley.

Below, we explore recent research on sports betting. Among the findings of the seven studies featured here:

• Sports bettors are more likely to be white, male, and exhibit psychological traits consistent with narcissism.
• Tax revenue from sports betting may appear substantial in raw numbers, but the impact on tax coffers is muted when compared with income and sales taxes, or tax revenue from other gambling offerings.
• Evidence is mixed as to whether introducing sports betting cannibalizes — eats away at — revenue from other types of gambling.
• Some college football referees may more heavily penalize betting favorites.

The nonprofit National Council on Problem Gambling estimates as many as 8 million adults in the U.S. may have a mild, moderate or severe gambling problem. However, there is a lack of comprehensive, recent academic research on the extent of gambling addiction in the U.S., and the societal costs.

If you feel you may have a problem with gambling you can get help from the National Council on Problem Gambling by call or text at 1-800-522-4700, or online chat at ncpgambling.org/chat .

Research roundup

The Income Elasticity of Gross Sports Betting Revenues in Nevada: Short-Run and Long-Run Estimates Ege Can and Mark Nichols. Journal of Sports Economics, October 2021.

The study: The authors analyze quarterly sports betting data from Nevada covering 1990 to 2019, to explore whether sports betting might be a viable tax revenue stream for other states. Sports betting has been legal in Nevada for decades, so it is the only state with long-run data that can potentially provide insight on the tax base future in states that have legalized sports betting since 2018. The authors note that Nevada is a “mature” market for sports betting, meaning industry growth is relatively stable year to year. A state that newly legalizes sports gambling is likely to see an immediate jump in sports betting revenue, with industry growth levelling off over time.

The findings: In the short-run, quarter-to-quarter, the rise and fall of sports betting revenue in Nevada is most closely tied to changing sports seasons. The authors suggest this is due to differences in how much bettors wager on various sports — the NFL, for example, is “the most popular sport to place wagers on,” with revenues rising and falling as an NFL season begins and ends. In the long run, taxable income in the state and sports betting revenues tend to grow at similar rates. Sports betting revenue in Nevada is a small fraction of revenues from other sources.

The authors write: “Total sports betting revenue in Nevada, the amount kept by the casinos, was $329 million in 2019, implying $22.2 million in tax revenue for the state. In contrast, casino gambling in Nevada in 2019 was $12 billion, generating $810 million in tax revenue. Sports betting is a gambling activity where the amount retained by the casino, and consequently retained by the state, is relatively small as most of the money from losing bets is transferred to those with winning bets. Therefore, sports gambling is a smaller contributor to tax coffers compared to more traditional tax sources such as income and taxable sales or, if applicable, casino revenue.”

A Comparative Analysis of Sports Gambling in the United States Brendan Dwyer, Ted Hayduk III and Joris Drayer. International Journal of Sports Marketing and Sponsorship, August 2022.

The study: The authors explore whether there are psychological differences between bettors and those who do not bet, as well as differences in how closely bettors identify with social institutions, such as religious organizations and far-right or far-left politics.

The authors surveyed 377 bettors and 402 non-betting sports fans from 47 states and explored differences between bettors and non-bettors in states with legal gambling and states where gambling is banned. They also asked about narcissism, which past research has found “is associated to gambling behavior especially as it relates to risky behavior such as participating in illegal gambling,” the authors write. Bettors in the sample were 81% male, compared with 69% of non-bettors. Among bettors, 64% were white and 27% were Black, while 77% of non-bettors were white and 17% were Black.

The findings: In legal gambling states, bettors felt more self-worth than non-bettors, though in states where gambling is illegal the difference in self-worth was almost nil. In legal gambling states, bettors reported a stronger personal identity, “or the importance with which an individual identifies with their relationship and career,” than non-bettors. This relationship flipped in illegal gambling states, with non-bettors showing a stronger personal identity than bettors. In both illegal and legal gambling states, bettors reported slightly higher levels of social uselessness — “an individual’s perceived lack of worth related to social institutions” — than non-bettors, though the gap was wider in illegal gambling states.

The authors write: “Bettors look different and come from different backgrounds and locations. Psychographically, they were clearly more narcissistic. They also indicated a higher social identity and self-worth, yet perceived themselves as less worthy members of important social institutions. In general, sports bettors out consumed non-bettors as it relates sports spectatorship.”

Game Changing Innovation or Bad Beat? How Sports Betting Can Reduce Fan Engagement Ashley Stadler Blank, Katherine Loveland, David Houghton. Journal of Business Research, June 2021.

The study: Legal sports betting means more than $4 billion in additional yearly revenue across the four major sports leagues, according to research the authors cite from the American Gaming Association. At the same time, there may be drawbacks that come with the financial windfall. The authors conduct two studies to explore how sports betting affects fan engagement — the emotional connection fans have with their favorite teams.

The first study included 325 people recruited from Mechanical Turk and focused on betting on a team to win, also called moneyline betting. The second was among 167 Mechanical Turk-recruited participants and focused on prop, or “proposition” bets. Prop bets are bets made on the outcome of some action during the game — whether the next foul ball is caught, missed or goes into the stands, for example. The study is among the first to explore whether there are negative emotional responses from fans related to sports betting.

Participants read a scenario — they were to imagine watching a Major League Baseball game, then randomly they were told they placed either no bet on the game or one of several types of bets. These bets included a $20 bet for the home team to win, along with prop bets. Gaming experts, according to the authors, contend that prop bets can potentially keep fans engaged even if the outcome of the game is obvious — if a team is up by 10 runs by the middle innings, for example. In each study, the participants were asked questions to gauge their emotional investment before and after being told the outcome of the game and their bets. Questions broadly asked about team loyalty, feelings of connectedness to the team and the likelihood participants would watch the team or attend a game, along with other measures of fan engagement.

The findings: In the short run, immediately after a game, the study indicates that betting and losing can decrease fan engagement. Participants who placed no bet were more likely to exhibit loyalty and purchase team-branded merchandise when the team lost, compared with those who placed a moneyline bet. Those who won a prop bet were slightly more likely to be engaged with the team than those who did not bet — but those who lost a prop bet were much less engaged than those who did not bet.

The authors write: “Although industry experts expect sports betting to increase fan engagement, results from two studies do not support this expectation. Instead, we find that when fans lose a bet, positive emotions and subsequent fan engagement decrease.”

College Football Referee Bias and Sports Betting Impact Rhett Brymer, Ryan Rodenberg, Huimiao Zheng and Tim Holcomb. Eastern Economic Journal, January 2021.

The study: The authors explore whether betting lines are related to bias in officiating in the six major Division I college football conferences across 6,598 games from 2005 to 2012. Betting lines indicate whether a sportsbook thinks a game will be close, will favor one team or the other, or be a blowout. The authors note that “college football and basketball are the only major U.S. sports in which conferences have primary managerial responsibility for officials.” If there is a game late in the season with an undefeated team playing a middling team, the conference will benefit financially if the undefeated team wins and goes on to play in a high-profile bowl game. “Referees, as employees of the conferences, are theoretically more likely to have implicit bias favoring the team with higher revenue potential,” the authors write. They use penalty yards per game as a proxy for whether an officiating crew exhibits bias toward one team or the other.

The findings: The authors find signs of bias during in-conference games in two conferences: the Atlantic Coast Conference and the Big East, which reorganized in 2013 and no longer sponsors football. In-conference games are those where two teams from the same conference play each other. In those ACC games where there one team was favored to win by three touchdowns or more, the authors find officials call 6.5 more penalty yards per game against the favorite. In the Big East, the penalty yards increase to 5.7 for the heavy favorite. Further, ACC officials appeared to flag fewer penalty yards against teams that had been in the league longer and enjoyed historic success, rather than newer teams enjoying more recent success. The authors found no officiating bias when an out-of-conference opponent was heavily favored.

The authors write: “… with increasing state regulation, there will likely be more scrutiny of officiating given that a wider spectrum of consumers will have a financial interest in game outcomes. Increased fan engagement via legal sports wagering highlights the importance of pinpointing evidence of bias and undertaking measures to ensure unbiased officiating and game integrity.”

Legalized Sports Betting, VLT Gambling, and State Gambling Revenues: Evidence from West Virginia Brad Humphreys. Eastern Economic Journal, January 2021.

The study: In one of the only studies to examine state-level sports betting revenue after the 2018 Supreme Court ruling, Humphreys looks at sports betting tax revenues in West Virginia and whether gamblers shifted their wagering from video lottery terminal games in casinos to sports betting.

The findings: From September to December 2018, casinos in West Virginia introduced five new sportsbooks, one at each of its licensed casinos. The year before, the state saw a windfall of $253 million in tax revenue from video lottery games. In the year after sports betting was introduced, the author estimates $45.4 million in lost video lottery revenue, with new sports betting revenue pegged at only $2.6 million. The state taxes video lottery revenues at 53.5%, while sports betting revenues are taxed at 10%.

The author writes: “These results should give state policy makers considering legalization of sports betting pause. While new revenue streams from legalized sports betting appear attractive on the surface, states already generate substantial tax revenues from gambling, and the introduction of sports betting to this mix does not leave spending on other forms of gambling untouched.”

Sports Betting’s Impact on Casino Gambling: Cannibalization or Expansion? Ernest Goss and Peyton Miller. University of Illinois Law Review, October 2021.

The study: Another one of few papers to examine how tax revenues and the games bettors played changed after the 2018 ruling, the authors analyze what happened after Iowa allowed sports gambling after August 2019. Iowa casinos that offer sportsbooks pay 6.75% of their sports betting revenue to the state, “a rate tied with Nevada for the lowest nationally,” the authors write. Like in West Virginia, taxes on all other forms of casino gambling are much higher — 22% on revenue over $3 million. The authors do not look at the specific effects of sports betting on other types of gambling, but rather whether there were any changes in overall revenues after August 2019.

The findings: Mobile sports betting and sports betting in casinos did not affect statewide gambling revenues from August 2019 to March 2020. After March, casinos shuttered due to the COVID-19 pandemic.

The authors write: “While these results do not indicate cannibalization within the Iowa gambling market, there are relevant implications for both casinos and the state. Conditions within the state of Iowa may limit the applicability to other states. For example, the varying tax brackets across gambling forms differ from casino taxing in other states.”

Frameworks of Gambling Harms: A Comparative Review and Synthesis Virve Marionneau, Michael Egerer and Susanna Raisamo. Addiction Research and Theory, August 2022.

The study: The authors gather and analyze “harm frameworks” related to problem gambling. A framework in this context refers to a way of categorizing and thinking about an issue with an ultimate goal of understanding the issue in a comprehensive way and finding solutions. A harm is simply an outcome that most of society would classify as negative — losing one’s house, for example, because of gambling-related losses.

While not specifically related to sports betting, the frameworks explored in the paper are useful for those who want to better understand what can happen to individuals and families affected by problem gambling. After searching major academic research databases, the authors settled on seven papers published between 2000 and 2021 that developed an original harm framework related to problem gambling — four of the papers focused on developing the same framework, leaving four frameworks total. The authors, while applauding the research that has already been done, note that further research is needed.

The findings: Two of the frameworks discussed problem gambling harms related to the workplace and personal relationships. One framework separated psychological and cultural harms, and harms related to crime. Another framework mostly focused on risk factors related to problem gambling, risks which “also occur on the individual, familial, community, and societal levels,” the authors write. They note none of the models explore the degree to which problem gambling harms individuals, families, communities and society — all the harms or risks were “treated as somewhat equal,” they write. Financial harms, they argue, might be a relatively worse harm since they “can be seen to precede or even cause many of the other harms, including criminal acts or emotional suffering.” The authors argue for more research on social harms, where, on the whole, the existence of high levels of problem gambling, “can cause harms irrespective of individual participation, including corruption, economic substitution, match fixing, environmental damage related to tourism, or animal suffering.”

The authors write: “We have found that while existing conceptualizations include a wide definition of harms, most harm items are still seen to stem from individual engagement with gambling. Further incorporation of social and societal harms is still needed to conceptualize and operationalize gambling as a public health issue. This includes the development of societal-level harm measurement and harm minimization.”

A brief history of U.S. sports betting

Americans have a long tradition of gambling. College of the Holy Cross economist Victor Matheson recounts in a January 2021 article in the Eastern Economics Journal:

“Lotteries funded activities such as the original European settlement at Jamestown, the operations of prestigious universities such as Harvard and Princeton, and construction of historic Faneuil Hall in Boston … In the sports realm, by 1900 betting on horse races was made illegal except in Kentucky and Maryland, states that to this day host two of the three Triple Crown events in American horseracing, the Kentucky Derby and the Preakness Stakes. States began to relegalize gambling on horse racing in the 1930s as a method of economic stimulus during the Great Depression.”

By the early 1960s, illegal gambling enterprises run by organized crime groups were worth a combined $7 billion . For more than 30 years, the Wire Act , enacted in September 1961, was the only federal law that addressed sports gambling. The law prohibits the use of a wire — a phone, or, more recently, the internet — to transmit information about placing sports bets across state lines.

The Indian Gaming Regulatory Act, which became federal law in 1988, allowed federally recognized Native American tribes to operate casinos on their land. Sports betting in tribal-run casinos, however, was not allowed unless a tribal-state compact was signed. This is the root of the current legal dispute in Florida. Such compacts were in effect in 22 states as of June 2021, according to the International Center for Gaming Regulation at the University of Nevada, Las Vegas.

By the early 1990s, federal legislators were expressing moral panic over the possibility of states allowing sports betting within their borders, to take advantage of billions being wagered illegally.

Illegal transactions are, by nature, difficult to track. People who bet illegally and their bookies do not typically share receipts with the government or trade groups, so it is difficult to say with precision how big the illegal gambling market was before 2018.

Noting that caveat, the American Gaming Association estimated illegal sports betting as a $150 billion-a-year business before the 2018 Supreme Court ruling. It is an oft-repeated figure in news stories and on websites devoted to sports betting.

In 1991, when overall illegal sports bets were estimated in the tens of billions, a Senate report declared sports gambling a “national problem.” The report continued:

“The harms it inflicts are felt beyond the borders of those states that sanction it. The moral erosion it produces cannot be limited geographically. Once a state legalizes sports gambling, it will be extremely difficult for other States to resist the lure. The current pressures in such places as New Jersey and Florida to institute casino-style sports gambling illustrate the point. Without federal legislation, sports gambling is likely to spread on a piecemeal basis and ultimately develop an irreversible momentum.”

Professional sports league commissioners and former athletes were publicly and adamantly against legal sports betting. They objected that sports integrity would be irreparably harmed, including the possibility of fixed games.

Gary Bettman, the top lawyer for the National Basketball Association, made clear to federal lawmakers in 1990 that sports betting was at odds with the league’s profit motive: “Bettors do not care about the win of their team,” Bettman said during a Senate committee hearing. “They only care about the spread being covered and winning their bets. That is not our product. That is not the product we are selling.”

President George H. Bush signed the Professional and Amateur Sports Protection Act on Oct. 28, 1992. It went into effect on Jan. 1, 1993. Bettman became commissioner of the National Hockey League a month later — and, eventually, a fan of sports betting.

“What we’ve learned is that [sports gambling] is another point of engagement for the fans,” Bettman said during a 2019 American Gaming Association conference. “Ultimately, I think if you’re interested in sports betting, you’re going to have an increased opportunity to engage with the game.”

After 1992, some limited sports betting was grandfathered in Delaware, Oregon and Montana. Delaware, for example, allowed a certain type of bets on National Football League games. States were given one year to legalize casino sports betting after the federal law went into effect, but none did. Nevada was the only grandfathered state that fully allowed sports betting. For nearly three decades, the 1992 federal legislation enshrined Las Vegas as the U.S. sports betting hub.

“[Legal] betting was pretty much happening in Nevada, in a regulated market, and you’d have to be at casino to do it,” says Holden, who wrote a comprehensive overview of the rise of legal sports betting published February 2019 in the Georgia State University Law Review. “That gave us sort of the image of sportsbook-style betting that you would see in the movies, you would see on TV. You go to the counter, you place a bet and you watch the game on 50 different screens.”

Constitutional cracks emerged in the 2010s. In 2014, New Jersey legislators voted to reverse their law banning sports betting there. The National Collegiate Athletic Association brought the state to court. This was the case the Supreme Court heard years later, leading to the fall of the Professional and Amateur Sports Protection Act.

Major sports leagues today are on board with gambling. It is impossible to watch professional sports without encountering advertisements encouraging betting. Online sportsbooks spend $154 million yearly in local TV spots, according to Nielsen. Aside from accepting ad dollars from sportsbooks, every major sports league and numerous individual teams have lucrative partnership deals with sportsbooks.

About The Author

Clark Merrefield

How to Analyse Football Matches & Improve Your Betting Skills

Learn how to analyse football matches, seek value betting opportunities, and devise the best football betting strategy.

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Betting Institute’s football betting tutorial intends to teach you how to devise a football betting strategy, seek value betting opportunities and shop around for the best odds. It is essentially a beginners guide, a ‘how to bet on football 101′, although it does include excellent betting advice that can prove to be useful regardless of your experience as a football bettor.

Being skilled in football betting relies mostly on a punter’s money management and value spotting ability. To spot value in football matches, you must have access to information and the ability to evaluate the data you have on hand correctly.

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Analysing Football Matches

Money management basics, shop around for the best odds, spot value bets.

Here we’ll talk a bit about the core elements that need to be part of any football betting strategy. Betting on football looking for a yield will require a lot of work, from collecting data and information to digesting it in order to discover football value betting tips.

Objective And Motivation

I can’t stress enough how important this is: get this right and the rest will be like baby puzzle bits falling into place. If you can find out what the clubs’ short and long term goals are, you’ve already got a decent platform to build on. We’re talking about fixture commitments.

Busy clubs will sacrifice some matches in favour of others every season, so if you find out this before the bookies do, you’re basically laughing. Leaving that aside, knowing each team's actual level of motivation to win, draw or lose a match can be crucial. Yes, you’ve heard well: some managers might ask their players not to lose by no more than two goals if they have a first-leg advantage of let’s say 4 goals; they will be happy to surrender to give some players a rest and to make sure nobody becomes exhausted or gets hurt.

Just think about it for a second; it happens all the time in FA Cup games involving English Premier League teams and of course, in other competitions involving famous football clubs, such as the Italian Serie A or even the mighty Champions League .

Remember always to check the upcoming fixtures of each club, not just their recent run of results.

Home & Away Behaviour

The ‘Home Advantage’ should not be taken for granted. Some teams play better away from home, and that can even vary from one competition to another. Also, teams might have completely different approaches depending on where they play. Spotting a solid away team before the bookies become aware of it can fill your pocket with cold hard cash.

Head To Heads

Past meetings can be deceitful when analysing football matches, and that’s because final scores can be deceiving, as much as stats can be. Of course, some teams have historically had problems playing others (or at specific grounds), but things change rapidly in football these days; a simple example would be PSG’s rise : in 2010 they finished 13th in Ligue 1, next season 4th and then they ended up league champions in 2012. And well all know what happened afterwards…  Do you think their head to heads mattered at all?

Form And Morale

The form is definitely an essential factor in football betting analysis, but remember that form is subject to sudden changes when you expect the least. Most punters haven’t got a proper way of determining true form: they just look at a few numbers and conclude in just seconds. And this could be the reason why those who place highly popular football bets often end up losing.

Form stats can be misleading: team who scored the first goal, goals scored, possession, corners awarded, shots on target etc. so you ideally want to watch football matches or at least highlights of those matches. On top of that, investigate advanced stats and information to figure out form, like the number of shots sent by the team and the on-target/off-target ratio, fouls, goals from action/set-pieces, mistakes made by referees – like lucky/unlucky scored/cancelled goals – and so on.

A team can play very badly and still win 2-0, as much as it can play really well and lose 0-2. Another facet that needs looking into would be morale, which is not necessarily connected to the most recent four or five results. A squad with a poor form can have good morale as a result of :

• receiving overdue wage payments
• attending a wedding of one of the players or staff members
• being promised a huge bonus if they win the next match
• the manager being sacked
• an upset of their closest rivals etc.

That is why team news can have a pivotal role in deciding the football tips to wager on. You head to read football day in and day out. Whenever a team with a very poor streak suddenly wins the game investigate why that happened. Same goes for the teams in great form that lose unexpectedly. Ideally, you’ll learn from these experiences and become better at anticipating such scenarios in the future.

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Unavailable Players

Most bettors misjudge injuries and suspensions. In fact, there are many football tips out there based solely on such information: ‘Falcao is missing, AS Monaco will surely lose’.

The truth is that some teams might even benefit from such scenarios, as their substitutes might be a lot more motivated to prove their worth to the team than those that are used to feature in the starting line-up. For example, Borussia Dortmund performed flawlessly in the 17/18 Bundesliga during the first 7 matchdays, winning 6 out of 7 fixtures, despite undergoing a nasty injury crisis – several key players were sidelined from a total of +11 injuries.

When you hear about an injury, don’t just think about the loss, but try to figure out how the replacement will perform. Generally, a squad with a good squad depth can overcome such trouble, so keep that in mind as the odds might be moving wrongly (because of what people bet) and you could benefit from that if you are above the crowd.

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Match Conditions

This is probably one of the most overlooked topics in football betting or sports betting in general. Before backing a favourite, ask yourself this question: “ Could they do it on a cold rainy night in Stoke? ” Leaving the jokes aside, take these elements into account when weighing options and try to investigate how well both teams could cope under such circumstances:

• Weather  – Pay attention to humidity, altitude, pressure, not just temperature and precipitations.
• Pitch Condition  – Will the match be played on grass or artificial turf? Is the pitch muddy, wet, sandy, frozen?
• Stadium & Fans  – Is it a neutral stadium? Match behind closed gates? Does the home side have many hardcode fans – does this have a positive or negative impact?
• Time  – Besides the eventual time zone difference, which is rarely a factor, observe how teams perform under daylight and night conditions.
• Referee  – Scout for possible animosities by checking out the history of the reff concerning the two clubs. Find out if he is more lenient or rigorous on the pitch and then combine this information with either squad's aggressiveness to draw relevant conclusions.

Consistency

Avoid betting on teams that usually perform very differently from a week to another. The standard variance when value betting is one thing, but if you choose to wager on unpredictable teams you’d better do it regularly to benefit from the unexpected results, otherwise just skip their matches.

Day-to-Day Issues

Head coach or staff changes? Financial problems? Club takeover? Internal rivalries, fights, discipline issues etc. Keep every single aspect under your radar, even if this means monitoring various social media accounts, bloggers, news portals, and so on. Remember, if it were easy, everybody would do it!

Weaknesses & Strengths

Develop a football betting strategy to follow when you analyse each fixture. Take a sheet of paper and split it in half. On the left side, write each club's weaknesses and write their strengths on the right. You’ll see that everything is a lot easier to weigh when you have to put your thoughts on paper.

After reaching a fair amount of betting samples feel free to evaluate your performance and tweak the model until you’re on top of the game. Remember that the cornerstone of winning football bets is, of course, weighing everything accurately and staying away from fixtures that are too unpredictable from your point of view.

Don’t expect to win bets every time , instead focus on betting where the value is, as you will benefit from it in the long run. Of course, winning your bet is always nice, but take note that pro punters who wager on even odds generally win just about 50% of their bets.

Did you know we're publishing safe football betting tips daily?

You already know that money management is critical to success in sports betting – almost every betting guide says so – but still you might not be on the right track just yet. Don’t get lost in all the Martingale’s and Fibonacci’s, but rather stick to the flat staking method. This staking strategy falls into the advanced betting category (most pros use it). Yet, it’s very simple to work with: you select a percentage between 0.5% and 5% of your initial bankroll, and you calculate the amount chosen as your stake.

You’ll always use that same stake (with each straight bet you place, so say goodbye to football accumulators) until you deposit or withdraw funds . Of course, you can feel free to recalculate the flat stake at the end of a season or every 12 months if you consider it would be wise doing so.

The flat staking money management routine works pretty well with Asian handicapping and is one of the two most popular methods employed by professional punters , the other being Kelly Criterion . And the good news is that either can be used for betting on football, horse racing, tennis, basketball, cricket and even on the NFL Super Bowl.

Don’t get excited by betting winnings or losses and try to keep your head clear during good and bad streaks. Remember to bet on singles and try to cut the footy accas and other bet types  as I said. Don’t get complacent and never chase losses. Set long-haul targets. Be patient: Good things come to those who wait!

Explore these 5 essential sports betting money management strategies

Every football tipster knows that winning your bets from time to time isn’t going to be enough to secure a profit at the end of the year. Football betting odds are significant for your betting success.

It doesn’t matter if you’re going for a straight bet, a double chance bet, a correct score bet or a handicap bet, if you want to wager on the English Premier League , Champions League, FA Cup or any other football competition, as long as you shop around to find the best offer. As you already know, betting lines are different with every bookmaker, so you must do your utmost to grab the best odds on the bet market.

It may not seem much at first, but if you do the betting calculations on a large sample of bets, you’ll see how many times bigger your bankroll would have been if you were picking the best betting odds offered by online sportsbooks. I recommend this bookie . If you want to learn more about odds, from decimal odds and fractional odds to the reasons why odds change, please give this resource a good read: betting odds explained .

What’s the best welcome bonus in online betting? Find out now!

Don’t just bet on the favourites, but on the odds that are better than they should be. How can you achieve that? Well, there’s only one way: devise a model to evaluate estimated probabilities for football markets and tweak them regularly. Having programming skills can be useful but not anyhow mandatory.

Browse our betting guide , try to pick up some key indicators, and then focus on one of the most popular football bets, such as the Under/Over 2.5 goals or the 1X2 Moneyline. Commence by creating your own football odds and forget about copying other punter’s betting tips.

Learn how to calculate value bets , combine the stats with team news and start placing football bets only where you find value. You won’t become a successful football bettor overnight, but you will certainly have a platform to build on if you take the value betting path.

Wait no more! You can start wagering with the best bookmaker in the UK in less than 2 minutes!

Read more BettingInstitute How To guides:

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Nice article… I feel more confident… although I will do more studies…

Thanks a lot

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The sure bet? Sports gambling will become an even bigger player, researcher says

by Leila Ugincius, Virginia Commonwealth University

Not long ago—1992, in fact—Congress passed a bill that essentially blocked sports betting nationwide, save for a few states. The law was ruled unconstitutional in 2018, and the scene changed quickly: Last year, Americans legally wagered nearly $120 billion on sporting events.

Brendan Dwyer, Ph.D., is director of research and distance learning at Virginia Commonwealth University's Center for Sport Leadership, whose acclaimed master's program propels graduates in the global sports industry. With the dramatic rise in sports gambling—a topic Dwyer has researched—we asked him for a fresh pulse of the evolving landscape.

Sports gambling feels like the Wild West, in terms of platforms, regulations and more. How accurate is that perception?

I always look at things from a sports fan perspective, and certainly, given the amount of commercials and media coverage , it can be overwhelming. There are so many providers and ways to bet. I don't know if I've used the term "the Wild West," but if you're not educated about sports betting—but you're a fan of basketball or football—it can be intriguing but also overwhelming.

You're seeing a few providers stand out, such as DraftKings and FanDuel, but ESPN, a major media provider, suddenly entered the marketplace with ESPN Bet. It's probably still more confusing for fans than it is clear. But like anything, once you start trying it, you start to feel it out and get used to it.

In terms of state regulation, it is also difficult because you cross a state line and you can gamble on your phone—and then you cross another state line and you can't. Even a Virginian who goes to Nevada may just assume, "Well, I can gamble on my phone because I gamble on my phone in Virginia." But you can't gamble on your phone in Nevada. You have to go to a casino. So every state has their own rules and regulations. For consumers, that can be confusing.

You mention the aggressive marketing. Is a cautionary tale developing?

There is more to be said and done about how easy and accessible it is to get media messages to youth. I already have my 10-year-old asking, "What is this? What is that?" They're watching sports, and these commercials and these conversations are happening. Most countries we would consider counterparts, whether it's the U.K. or Australia, that have had sports betting for years have strict regulations about advertisements and sponsorships, and a lot of that is for the protection of youth.

This is where "the Wild West" might come in right now. We're pretty unregulated as it relates to advertisements. We show primarily a young, successful male enjoying a sporting event even more by betting. We don't see the downside of it in any commercials. The messages to individuals under age 18 is going to be something important in the American context.

Where does Virginia stand in the market?

Virginia is an interesting case because we went online right away in 2021. We could bet everywhere on our phones. There's been a lot of revenue that has flowed through Virginia in term of handle, which is the total money spent by consumers. We're right in the middle if you compare us with other states of the same size that came on board at the same time. But we've raised more state tax revenue compared with them, and I think a lot of that has to do with online access. In Arizona, you can only bet at casinos and a few other retail locations. So as much as they've had similar revenue numbers, the state hasn't received the same in tax revenue.

Has sports gambling affected sports consumption—or even how we think of "fandom?"

Oh, yeah, 100%. There's a strong positive relationship between sports betting and viewership. Think about it from a simple bet, which is the point spread—how a game finishes. Some games can be completely out of hand, right? It can be the fourth quarter of an NFL game, and the only people watching a blowout are bettors, which means more money for advertisers and sponsors.

As sports bettors consume more live sporting events , they consume more live analysis shows on ESPN and elsewhere because they believe that the more you know, the better you'll bet. And there's a strong relationship between consumption and fandom because people like to have action on a game. Now that there's live betting within a game, too, it's become a social topic between friends and within families to talk about. "Did you win this bet? Did you lose this bet?" It's just becoming a different part of our social landscape.

Are there distinct categories of gamblers?

I've done a few studies on this, primarily on involvement—individuals who bet a lot compared with those who are more casual or sporadic. Serious bettors do not just bet on the traditional American sports—they'll bet on pretty much everything, and they have a strong emotional attachment to the activity. It's not just a hobby. Casual and more sporadic bettors focus on more of the mainstream sports and bet from time to time. And they're doing it more parallel to their traditional viewership.

Another group that is getting, and needs, more research is 18- to 24-year-olds. Men primarily. And that is because this group struggles to moderate any behavior. They can easily lose a lot of money, or they can be problem-gambling if it's not regulated. So between them and college student-athletes, they're the two segments or populations that probably need the most protection. You're starting to see more research focused on those two groups.

In the spirit of gambling ... give us a prediction or two for the next few years.

I work in education, so I think that as consumers become more educated, sports betting will continue to grow. We still have states that have yet to regulate sports betting, as well as large states that haven't legalized it. We also have room to grow among sports fans. Many have been reluctant to join the marketplace, but as media providers educate more, I think people will bet even more. It will continue to grow in popularity. I think it'll be less of a talking point because it will just become mainstream to how we watch sports.

Provided by Virginia Commonwealth University

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Effects of expertise on football betting

Yasser khazaal.

1 Geneva University Hospitals, Grand-pré 70 C, 1206 Geneva, Switzerland

Anne Chatton

Joël billieux.

2 Psychological Sciences Research Institute, Catholic University of Louvain, Louvain-La-Neuve, Belgium

Lucio Bizzini

Grégoire monney, emmanuelle fresard, gabriel thorens, guido bondolfi, nady el-guebaly.

3 Addiction Division, University of Calgary, Calgary, AB, Canada

Daniele Zullino

Football (soccer) is one of the most popular sports in the world, including Europe. It is associated with important betting activities. A common belief, widely spread among those who participate in gambling activities, is that knowledge and expertise on football lead to better prediction skills for match outcomes. If unfounded, however, this belief should be considered as a form of “illusion of control.” The aim of this study was to examine whether football experts are better than nonexperts at predicting football match scores.

Two hundred and fifty-eight persons took part in the study: 21.3% as football experts, 54.3% as laypersons (non-initiated to football), and 24.4% as football amateurs. They predicted the scores of the first 10 matches of the 2008 UEFA European Football Championship. Logistic regressions were carried out to assess the link between the accuracy of the forecasted scores and the expertise of the participants (expert, amateur, layperson), controlling for age and gender.

The variables assessed did not predict the accuracy of scoring prognosis (R 2 ranged from 1% to 6%).

Conclusions

Expertise, age, and gender did not appear to have an impact on the accuracy of the football match prognoses. Therefore, the belief that football expertise improves betting skills is no more than a cognitive distortion called the “illusion of control.” Gamblers may benefit from psychological interventions that target the illusion of control related to their believed links between betting skills and football expertise. Public health policies may need to consider the phenomenon in order to prevent problem gambling related to football betting.

Introduction

Football is one of the most popular sports in the world, Europe included. It is associated with important monetary transactions and financial sponsoring [ 1 ].

Sports betting is associated with pathological gambling [ 2 ] and is widely available on the Internet [ 3 ], one of the most important means for seeking general, medical, and gambling information [ 4 , 5 ]. There, one can find messages such as “To win at sports betting, you have to prognosticate correctly. Don’t forget that a sports bet is not the lotto. Sport is not only a question of chance, far from it. To place your bet efficiently, you must learn about football as a sport and follow a minimum of its championships.”

Football competition is, unmistakably, a sport based on a high level of training and specific skills. This assertion may lead to the belief that football knowledge and expertise will allow better prediction of match scores. If unfounded, however, this belief should be considered a form of “illusion of control.” This term was defined by Langer [ 6 ] as “an expectancy of a personal success probability inappropriately higher than the objective probability would warrant.” This type of distorted thinking was considered a major factor in gambling persistence and severity [ 7 , 8 ], and led to the development of cognitive restructuring therapies for pathological gamblers [ 6 ].

As suggested by Cantinotti, Ladouceur, and Jacques [ 9 ], to a certain degree, the utility of sport expertise in sport betting cannot be fully ruled out. For example, it was previously found that factors such as the home field advantage, team rankings, most recent results of teams, and injuries of key players significantly affect game results [ 10 - 14 ]. It was then suggested that skills could be helpful when betting on sports events [ 15 ].

Probably in connection with these considerations in sport and football betting, defeats have been shown to be more often discussed than wins [ 16 ] and were commonly attributed to unlikely or random events [ 5 ] or were considered a “near win” [ 11 ], whereas wins were attributed to skills in selecting the victorious players. This interpretation probably contributes to an overestimation of betting skills [ 5 ].

It would be relevant to determine whether expertise is essential for determining game scores. If this were not the case, the alleged skills in sports betting could be regarded as no more than a manifestation of the illusion of control, as observed in most gambling activities.

With several exceptions, such as horse betting [ 17 ] and hockey [ 7 ], the relation between gamblers’ skills and betting outcomes has been rarely studied. Studies that evaluated gambling skills rather than the role of expertise in sports for betting activities showed that monetary gains from gambling skills were not significantly higher than would have occurred by chance. Because of the wide popularity of football and football betting, it seems important from a public health policy perspective to assess the links between football expertise and prediction of match results.

The present study examined whether football experts were better than non-experts for predicting the scores of the first 10 matches of the 2008 UEFA European Football Championship.

During the 3 weeks prior to the beginning of the first match of the 2008 UEFA European Football Championship, a questionnaire was completed anonymously by 258 study participants recruited through local advertising and direct contact of football professionals (players, handlers, and referees) and sports reporters. The questionnaire assessed professional and amateur activity in relation to football. It also included five questions (Table ​ (Table1) 1 ) related to the degree of football interest (questions 1, 2, and 3), the degree of belief in the link between a good knowledge of football teams and accuracy of match-related prognoses (question 4), and sport betting habits (question 5). In addition, participants predicted outcomes for the first 10 matches of the 2008 UEFA European Football Championship.

Questions related to football and sport betting

Participants were classified as being in one of three categories:

(a) “Experts”: The experts are professional or semiprofessional football players, coaches, or football sport journalists whose work was related to the 2008 UEFA European Football Championship.

(b) “Amateurs”: These participants have an amateur link with football (e.g., amateur referee) and/or play football as amateurs.

(c) “Laypersons”: This group has neither professional nor amateur connections.

The forecasts were analyzed for winning accuracy (accuracy of the prognosis: winning team 1, winning team 2, or draw) and score accuracy (good score prediction).

Statistical analyses were performed with SPSS for Windows (version 15.0). An initial exploratory analysis involved the calculation of proportions, as well as means and standard deviation of the outcome values. Spearman correlations with Bonferroni’s correction ( p  = 0.05/4 since four correlations were analyzed; p  = 0.0125) were carried out to assess the links between each of the first four questions related to football interests and the fifth related to sports betting (Table ​ (Table1). 1 ). Moreover, one-way analyses of variance (ANOVAs) were performed to compare the distribution of the mean numbers of correct outcomes and correct score predictions as dependent variables with regard to the above-cited first four questions as factors, adjusting for multiple pairwise comparisons.

We also used a paired samples t -test to test whether gamblers had a greater number of correct outcomes than chance when forecasting the results of the games. Indeed, by chance, that is to say in the absence of any information, the probability of a gambler predicting 7 correct outcomes out of 10 games (0.016; the exact formula for the binomial distribution is given by p x = ( x n ) p x 1 − p n − x , where x is the number of successes and n the number of trials) is not the same as the probability of predicting 7 outcomes out of 10, given all the information in the bettor’s possession (0.7; given by the assumption: 7 correct outcomes out of 10 games). This last probability, referred to as conditional probability, means that before making a choice, the bettor will take into account all relevant information at their disposal. In addition to each participant’s observed probability of making the right bet, one may compare this to the expected probability based on chance.

Finally, a binary logistic regression for each of the 10 matches was done to predict the accuracy of the scores (correct vs. incorrect score) with the participants’ expertise categories (expert, amateur, or layperson) as predictor, controlling for age and gender (female vs. male). For the categorical factors “gender” and “expertise,” the reference groups were levels 2 and 3, respectively.

After checking for multicollinearity and outliers, we assessed the goodness of fit of these logistic models by considering the following:

The classification table of the intercept-only model (baseline or null model) with that of the full model, where a significant improvement should be expected over the null model.

The Nagelkerke R-square statistic with all the independent variables. This statistic attempts to quantify the proportion of explained variation in the logistic regression.

The statistical tests of the predictors, using the Wald chi-square statistics. P-values less than 0.05, or alternatively, confidence intervals that exclude the “1” value, are suggestive of significant predictions.

Two hundred and fifty-eight persons participated in the study (57% were men; mean age: 36.6 years ± 11.2). Fifty-five (21.3%) were classified as football experts, 140 (54.3%) as laypersons, and 63 (24.4%) as amateurs.

Answers to the five questions in the questionnaire are reported in Table ​ Table2. 2 . After Bonferroni’s correction was performed, the Spearman correlation showed significant associations between the first three questions related to football interest and sports betting (Spearman’s r = 0.49, r = 0.43, r = 0.41; p  < 0.0005, respectively). Sports betting appeared to be associated with football interest. There was no correlation found between question 4 (believed role of football expertise for prognosis skills) and sports betting.

Distribution of participants’ answers to the five questions reported in Table ​ Table1 1

The numbers and percentages of accurate outcomes and scores by category of participants are reported in Table ​ Table3. 3 . The mean number of correct outcome or score prognoses and the relative frequency of the distribution of correct outcomes by category of participants are reported in Table ​ Table4 4 and Figure ​ Figure1, 1 , respectively.

Number and percentage of correct outcomes and scores by categories of participants and by match

Comparison of mean number (standard deviation) of correct outcomes and scores exactly predicted by each group of participants

Distribution of relative frequencies of correct outcomes.

The ANOVAs that were used to compare the distribution of the mean numbers of correct outcomes and correct score predictions with regard to the first four questions showed a statistical significant between-group difference for the mean number of correct outcomes (F (3,253)  = 2.8 and p  = 0.04) in question 4 (“I think that a good knowledge of the teams allows me to predict with accuracy the match score results”). But after adjusting for multiple comparisons, this difference was no longer significant. No significant difference before or after adjustment was observed for the other three questions.

The paired sample t -test that was used to evaluate whether gamblers had a greater number of correct outcomes than chance when forecasting the results of the games showed a statistical significant difference (t = 39.15 and p  < 0.0005). We conclude from the data that the bettors were more accurate in their predictions than chance.

The logistic regressions, which were done to test the research hypothesis, yielded poor results. The classification table of the full models showed no improvement over the baseline models, meaning that the classification rates were exactly the same in both situations (Table ​ (Table5, 5 , column 2). The Nagelkerke R-square measures ranged from 1% to 6%, leading us to conclude that these models were not useful in explaining the outcome variable (Table ​ (Table5, 5 , column 3). Finally, the predictor variable “expertise” (Table ​ (Table5, 5 , column 4) did not prove significant except for the model involving the game Germany-Poland ( p  = 0.03, odds ratio = 2.57 and 95% CI for odds ratio = [1.08; 6.14]). This result means that compared with a layperson, being an amateur increases the likelihood of accurate score prediction by 2.57, assuming that the other factors in the model are held constant. There was no significant difference between experts and laypersons since the confidence interval includes “1” (exact results not shown).

Evaluation of model’s goodness of fit

*Maximum iterations reached and final solution not found because group sample size too small.

It is worthwhile noting that no expert was able to correctly predict more than seven outcomes and no participant more than eight (Figure ​ (Figure1 1 ).

In the present study, the results of the logistic regressions, although poor, were consistent across matches. Experts do not appear to be better than non-experts at predicting football match scores. Similarly, ANOVA results indicated that the average number of correct outcomes with respect to accurate scores were not significantly different across the four conditions (first four questions in Table ​ Table1). 1 ). The belief that expertise is useful for sports gamblers seems to be simply an illusion of control.

By chance alone, the probability of someone predicting 10 correct outcomes (first winning team, second winning team, or draw) out of 10 games is estimated to be 1.7 100 , 000 , i.e., P X = 10 = 10 ! 10 ! 0 ! × 1 3 10 × 2 3 0 . The exact formula for the binomial distribution is given by p x = ( x n ) p x 1 − p n − x , where χ is the number of successes and n the number of trials. This is an interesting probability for the sports betting business, which mostly offers big monetary winnings on a combination of match results. Thus, in consideration of this probability and the lack of impact of expertise on football betting outcomes, sports betting appears to be nothing other than a game of chance, as suggested by other studies [ 7 , 15 ].

As reported elsewhere [ 18 ], sport interest, rather than the athlete’s status [ 19 ], is possibly linked to sport betting. The finding of a lack of association between sports bets and the belief assessed in question 4 (“I think that a good knowledge of the teams allows me to predict with accuracy the match score results”) may result from the present sample being participants from the community and not problem or pathological gamblers. About 6% of the subjects did, however, consider this declaration as extremely correct and more than 30% as fairly correct, showing the wide diffusion of such beliefs.

One possible limitation of the present study is that it was not carried out as a real gambling condition. The results should be then taken with caution. Further studies may include measures of gambling-related cognitions (e.g., fallacy, superstitious beliefs, biased evaluation of outcomes), participants’ betting behaviors and habits, and more detailed measures of expertise and self-confidence related to a sense of expertise, as suggested by wagering models [ 20 ]. Further studies may also include betting related to other sport activities.

Another limitation was the small sample of games surveyed and the non-random selection of these games, which resulted in a non-probability sample. Out of all matches that were played during the 2008 UEFA European Football Championship, only the first 10 were selected for analysis. The possibility that, by pure chance, the games selected happened to be more or less predictable than the standard ones should not be ignored.

Finally, the logistic regression models set up to predict the accuracy of the number of goals scored by each team may have failed to take account of other possible significant predictors, such as the quality of the teams (ability to attack and/or to defend), the team’s league position at the time of playing, and the “home effect” (advantage in playing at home). The absence of these potential predictors may explain the small predictive power of our models.

Expertise, gender, and age did not have an impact on the accuracy of the football match prognoses. Consequently, the belief that football expertise improves betting skills seems to be a cognitive distortion.

Clinicians may inform gamblers about the limited help of football expertise in match-outcome predictions and the relative fallacy of commercial advertisements for sport betting, such as “….a sports bet is not the lotto… to place your bet efficiently, you must learn about football as a sport and follow a minimum of its championships.” Gamblers may benefit from psychological interventions that target the illusion of control related to their believed links between betting skills and football expertise. Furthermore, public health prevention policies may need to consider the present results in order to prevent problem gambling related to football betting.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

YK and DZ participated in the design of the study. YK and NG drafted the manuscript. AC performed the statistical analysis. JB, LB, GM, EF, GT, RK, and GB participated in recruitment and data collection. All authors read and approved the final manuscript.

Acknowledgements

We thank the study participants, the football experts who agreed to participate in the study, GREA and Mr. Pascal Savary, the “Rien ne va plus,” the Geneva Health Department, Dr. Christine Davidson, Mrs. Alessandra Horn, and Mr. Christian Osiek.

Funding source

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Fair Game? Inside Britain’s Football Betting Crisis

Britain has a gambling problem. While the industry’s raking in more money than ever, some estimates suggest over a million of us are at risk of harm or addiction. But it’s not just bad luck – it’s by design

Felix*, 24, can’t remember when he first bet on football, but he reckons he was between eight and 10 years old.

‘My dad would go into the bookies and I’d be sat in the van,’ he says. ‘He’d place his bets, then bring out a slip for me to fill in the teams.’

At the time, it seemed like a bit of low-stakes father-son bonding: £2 on the first scorer and result, a bit like how some parents let their kids pick the lottery numbers. He had his first big win in 2012 when Chelsea beat Liverpool 2-1 in the FA Cup final, with Didier Drogba getting on the score sheet. That earned Felix a new pair of football boots.

And as a boy, he was obsessed. ‘I lived football. It’s been my whole life, really,’ he says. He played for his school team. He and his grandad had season tickets at Bristol City. He watched every game he could on TV, played Fifa all the time and then, at 15, got into Fantasy Football and started studying the form of every obscure Premier League player. It was a natural progression to the bookies at 17 with fake IDs. ‘We rarely got questioned.’

‘I’d be studying the form on a Friday night. Hoping to win the Friday night games to pay for the Saturdays. Gamble on the early kick-offs. Then the three o’clocks, the evening games.’ He would still go to Bristol City with his grandad, but all his attention would be on his phone. ‘You end up not really supporting your own team. You’re supporting your five teams on the accumulator. I didn’t really care if City won or not.’

When he was forced to stop last year – miserable, anxious, suicidal, with £35,000 of debt, including £20,000 stolen from his employer over time – he didn’t even care if he was winning or losing any more. ‘It was about the cycle, the dopamine, the next bet,’ he says.

High Stakes

Britain’s £15.1bn gambling industry and its well-funded lobbying operation would like you to believe that the problem lies with Felix. Felix certainly isn’t looking to blame anyone else. ‘It’s my doing,’ he says. ‘It spiralled out of control through me and no one else.’ Still, the lax security checks at the bookies, the gambling adverts at the grounds, on TV, within computer games, all the WhatsApp bet chat among his friends – none of this can have helped.

.css-vjih4b{font-family:Knockout,Knockout-roboto,Knockout-local,Helvetica,Arial,Sans-serif;font-size:3.125rem;letter-spacing:0.03rem;line-height:1;margin:0rem;}@media(min-width: 64rem){.css-vjih4b{font-size:3.125rem;line-height:1;}}.css-vjih4b b,.css-vjih4b strong{font-family:inherit;font-weight:bold;}.css-vjih4b em,.css-vjih4b i{font-style:italic;font-family:inherit;}.css-vjih4b a{-webkit-text-decoration:underline;text-decoration:underline;text-decoration-color:#FFF200;} ‘It was about the cycle, the dopamine, the next bet’

And the fact that there could be as many as 1.4 million people in the UK experiencing harms from gambling, according to a 2022 report from GambleAware – and that some estimates have placed the number of deaths by suicides associated with problem gambling between 117 and 496 a year in England – suggests that it’s not just Felix’s problem. It suggests Britain has a gambling problem. And once you begin looking at the influence of gambling on our national game, it’s hard to know where one ends and the other begins.

For seven Premier League clubs (Aston Villa, Bournemouth, Brentford, Burnley, Everton, Fulham and West Ham), their primary shirt sponsor is a gambling company – but this is just the tip of the iceberg. Researchers at Bristol University counted 6,996 separate pro-gambling messages during a weekend of Premier League action. The league below is literally called the SkyBet Championship. You can’t even escape the messaging on radio: on TalkSport, commentators are paid to offer live in-play betting odds.

This is an unbelievably lucrative business: Bet365, founded in Stoke in 2000, is the world’s largest online betting company and its CEO, Denise Coates, earned £221 million last year. You can read all about her £90 million house and two helicopters online. It’s impossible to calculate just how much of her salary is paid for by at-risk customers. But according to statistics from the National Centre for Social Research, 86% of gross online gambling profits come from just 5% of users, while the Gambling Commission reports that 35% of people with a gambling disorder receive daily incentives to gamble.

Perhaps unsurprisingly, the industry itself disputes many of the figures relating to harm, pointing to difficulties in collecting accurate self-reported data (Bet365 didn’t respond to a request for comment). However, consultant psychologist Mark Gaskell, who runs the NHS’s Northern Gambling Service , is in no doubt about the scale of the problem. ‘This is not about a minority of so-called flawed individuals,’ he says. ‘The gambling industry is targeting the population en masse and appealing to universal decision-making and biases and susceptibility.’

Dr Gaskell is quick to stress that he’s not against gambling in itself. ‘Gambling could be something that’s done recreationally for a bit of fun.’ But the UK did not create a world-beating gambling industry on the back of a few fans betting on their teams. ‘This industry isn’t interested in recreational gamblers. They want to move you to the most addictive products… and our laws and regulations are not protecting children and they’re not protecting the young men who are experiencing the most harm.’

Dr Gaskell set up his first clinic for gambling addicts in Leeds in 2019. He was struck by how many of the men who turned up were wearing football shirts. And how many of those shirts were sponsored by gambling companies.

‘There’s a pandemic,’ says James, 51, a Manchester City fan and recovering addict, who estimates he has gambled over half a million pounds in his lifetime (including his mother’s £90,000 mortgage). He can speak at length about the guilt; the lies; the resentments; the long, hard road to recovery. He credits Gamblers Anonymous with saving his life. But he’s more worried about the younger men he’s seeing. ‘There are thousands of kids who are in this scenario because of football betting, believe me, and they cannot get away from it. It’s in their head. It never stops.’

Changing the Game

The mildly encouraging news is that after years of campaigns and warnings, Britain is slowly acknowledging that, yes, we do have a gambling problem – the crucial first step in actually doing something about it. Last year, the government published a long-delayed review of gambling laws in belated acknowledgement that the industry has mutated out of all recognition in the online era. (Tony Blair’s government liberalised gambling laws in 2005, opening the way for today’s mega profits, but no one seemed to have anticipated the invention of the iPhone in 2007.) Among the proposed changes: a maximum £2 stake on online slot machines (widely viewed as the most corrosive form of online gambling) and a statutory levy on gambling companies to fund independent research (currently, most research into gambling harms is funded by the industry itself).

A spokesperson for the Gambling Commission described the proposed laws as ‘a coherent package of proposals that we believe can significantly support and protect consumers, and improve overall standards in the industry’.

What the new laws will not do, however, is curb advertising or sponsorship. It’s true that the Premier League has announced – after widespread outcry – that it will ban front-of-shirt gambling sponsors by the 2026/27 season. The Betting and Gaming Council (BGC) – which exists to promote the industry – disputes the link between advertising and problem gambling. Although it has welcomed the shirt ban and cites other voluntary measures, such as a ‘whistle-to-whistle’ ban on betting adverts in football matches, introduced in 2019.

Nevertheless, research has shown that front-of-shirt sponsorship accounts for just 7% of the pro-gambling messages that are seen during a game – and football grounds are still full of gambling billboards, which are prominent even on the supposedly ad-free Match Of The Day highlights programme on the BBC. In 2020, researchers at Ipsos Mori and the University of Stirling found that 96% of people aged 11 to 24 had seen gambling marketing messages in the past month.

Annie Ashton discovered as much when she took her 11-year-old son to watch Leicester City last season – something her late husband Luke always used to do, until he took his own life in 2021 after relapsing into a gambling addiction. ‘All I wanted to do was take my son to the football and I was faced with flashing adverts for the very thing that killed his father,’ she says. ‘It was a very bitter experience.’

Luke Ashton’s story shows how gambling can spiral out of control, extremely fast, with few outward signs. Annie describes her late husband as a loving father with everything to live for. ‘Him and my son, they were each other’s shadows. They were so involved in each other’s lives.’ He also prided himself on being a provider. ‘He was a saver. Every bit of overtime he did, he put money away.’

She only discovered he had been gambling after she accidentally opened a letter from the bank addressed to him and realised they were thousands of pounds in debt. ‘I confronted him about it – and he just said straight away, “I’ve been gambling. I’ve been gambling way beyond my means and I’ve been taking out loans to fund the gambling.”’

The pair of them worked to clear the debts. They moved house and Annie started a new job. It felt like a fresh start. But during the second Covid lockdown, Luke was furloughed from his job at a printing firm and suddenly had time on his hands. When he died in April 2021, Annie had no idea that he had fallen into gambling again.

Annie now works with the charity Gambling With Lives and has been campaigning for what she calls Luke’s Law, a ban on the free bets and lures that the gambling companies use to encourage people to gamble. ‘Previously, Luke had opened up lots of different accounts. This is what his friends had told him about. You open lots of accounts. You take advantage of the free offers for new sign-ups. Then whatever you get from those free bets, you put into the exchange sites. The more you spend on the exchange site, the more rewards you get, which induces you to gamble more.’

Luke’s phone records showed that he had been bombarded with promotions – but almost nothing by way of discouragement. ‘There were times when he was gambling 14 hours a day, placing over 100 bets in a day.’ He would receive generic emails reminding him that he’d been on the site for a long time, but that wasn’t enough to deter him. ‘During the inquest, what we discovered was that there are individuals who should be looking at that data. It should have triggered an intervention. But he slipped through the net.’

Football is almost always the first exposure that young men have to betting culture, says Matt Zarb-Cousin, a campaigner for gambling reform and co-founder of the app Gamban . ‘What do young men like? They like football. So the gambling industry says, let’s market around football. We can establish some habits and some associations with the sport they love at a time when their brains haven’t yet learned how to gauge risk.’ The second part is more insidious. ‘Once they’ve acquired their customers’ data, that’s when you get things like in-app marketing, cross-selling, free spins, bonuses and you’re on to slots and casino content.’ Gambling companies actually make most of their money from online slot machines. But this isn’t what’s featured in the advertising. ‘They don’t market that stuff on TV. They market football.’

Even if you do stick to the beautiful game, you will be pushed towards riskier forms of ‘in-play’ betting. Darragh McGee, an associate professor at the University of Bath, who has studied gambling and football culture, gives me an insight into how this works by pulling up his own social media profile. ‘If the algorithms have profiled you as a sports fan, as they have me, you’ll also see constant adverts for bets, with odds that seem too good to be true. I’m looking right now. Manchester United are playing Aston Villa and Marcus Rashford is 50/1 to have a shot on target. Now, if you know anything about football, you’ll know that’s fairly likely to happen.’

It’s an iron law of betting that if something looks too good to be true, it is too good to be true. The 50/1 offer is, as it turns out, only available to new customers. Should you win £50, your winnings will arrive in bet credits as opposed to cash. At which point, Dr McGee points out, you will have handed over your bank details and experienced the early thrill of a win. ‘You put in £1. You think you have £50. Lots of gamblers will tell you that it begins to feel like Monopoly money, it’s not real to them, even though they’re moving more and more money from their actual bank accounts into the apps.’ (A BGC spokesperson responded that offers and promotions are ‘an important part of customer experience’ and flagged concerns that banning them could ‘drive punters to unregulated, unsafe black market gambling sites, which do offer promotions’.)

Dr McGee sees the current situation as resulting from a ‘perfect storm’: the lax gambling reforms of the Blair era in no way anticipated the way the smartphone would revolutionise the industry. ‘In the analogue world, gambling was a day at the races or a trip to the casino. These were social settings that were at once removed from your everyday life... but what we’re talking about with phones is the opposite of that,’ he explains.

However, the third development is harder to unpick. It’s the commercialisation of sport itself and, in particular, the transformation of football into a multibillion-pound global entertainment behemoth. The scheduling of matches for TV, one after another, means you can binge-watch football in a way that just wasn’t possible a couple of decades ago, and with this comes the ‘repetitive cycles’ that build up to an addiction. Here’s James, the Man City fan, describing a typical weekend: ‘My gambling started on a Friday evening with all the European games. There’d always be a decent Bundesliga match on a Friday evening. La Liga, too. You could tie a nice little accumulator together and that would run all the way through to Saturday lunchtime, the 3pm kick-offs, the evening games. And I couldn’t wait for Sundays. You’d have the French Ligue 1 at midday, the Premier League matches, the Italian league…’ This was all so he could ‘build up a nice lump’ to take into the week’s European games.

Against the Odds

The thing that’s sad about this is how football – which many of us associate with family, friends, community and happy childhood memories – has been hijacked. ‘We think of sport as being inherently healthy,’ says Dr McGee. ‘But it’s become a conduit to a world that we know is harmful.’ Indeed, the more you look into it, the more it begins to feel as if football is sponsoring gambling rather than the other way around.

Don’t believe me? Here’s a little experiment you can run on any children you have in your life. First, ask them how many cigarette brands they can name. My football-mad son, Teddy, 10, couldn’t name any – which is reassuring, as I reckon I could have reeled off quite a few when I was his age. Then, ask how many gambling companies they can name. At this question, Teddy lit up. ‘Oh… Betfair? Bet365. Paddy Power, is that one? Erm… who are Newcastle sponsored by again? Fun something?’ Newcastle’s official Asian betting partner is, indeed, Fun88. (Fun fact: sponsoring English football clubs offers a convenient way for Asian betting companies to reach the enormous audience for Premier League football in China, where gambling is banned.) Teddy might be legally unable to gamble for another eight years, but his brand recall is already excellent.

Many of the independent researchers I speak to (those who don’t accept industry funding) express concerns about the way the industry, as a whole, has shaped the messages around gambling – similar to how the tobacco industry sought to downplay the harms of cigarettes.

You have probably seen the adverts, ‘When the fun stops, stop.’ These were produced by the gambling industry as an attempt to show they really do care about problem gamblers, meanwhile reminding us that gambling is fun. ‘It’s anything but an explicit warning,’ says May van Schalkwyk, a public health doctor who studies the ways that ‘addiction industries’ like gambling seek to influence debate. ‘It doesn’t say gambling can harm anyone. Or gambling can destroy people’s lives. The implicit message is, “It’s not our product that’s the problem. It’s not the way we’re being regulated that’s the problem. It’s you. You need to learn to use it responsibly.”’

Gambling policy in the UK has long favoured the gambling industry, Dr van Schalkwyk argues. Even the term ‘problem gamblers’ is a source of concern. ‘The idea that there is a group who are vulnerable and a group who aren’t is contrary to what we know about the way things ebb and flow over time,’ she says. ‘If you lost your job or your partner left you in the morning, you will be more vulnerable that evening in a way you weren’t before. We’re all susceptible at different times.’

But it’s worth remembering that the tobacco industry was, eventually, regulated. One of the reasons my son couldn’t name any cigarette brands is because cigarette advertising was banned in 2003. There were other measures, too – plain packaging, smoking bans, explicit warnings – but banning advertising was a crucial step.

Until then, there are ways of getting help. Felix’s family signed him up to GamStop : an exclusion scheme that prevented him from gambling online, meaning he had to go and place bets in person. He still did this three or four times a day, but ‘it’s a chore to have to go to the bookies late at night’. The thing that ultimately helped him was being caught and given an ultimatum. Pay the money back. And go to Gamblers Anonymous . ‘The only hope was going somewhere where people understand what the problem is. It’s mind-blowing what I owe to that room. Now I look at it, it was a blessing that I was caught.’

And yet, now that he’s in recovery, he sees it everywhere. Most of his friends gamble. They try to change the subject when he’s around, but he knows they’re doing it. At Bristol City, too. ‘I notice more the amount of men sat around me looking at football bets with friends and not watching the game.’ He reckons it can’t be helped. ‘I can’t stop others.’

Annie Ashton is more optimistic that the tide is finally turning – and can foresee a time when football ceases to be an unending advert for the gambling industry. ‘Eventually, it will have to happen,’ she says. ‘They’re draining it as much as possible now, but as with smoking advertising, it will need to stop.’ At times, she despairs of how normalised gambling has become. But she feels that even if many people remain unaware of just how corrosive it can be, they’re fed up of it being flashed in their faces all the time. ‘People are becoming sick and tired of seeing it on telly. They’re sick and tired of seeing it at football matches. We’re being force-fed it, force-fed something we do not want. It will have to stop.’

For more information or to find support, visit gamblingwithlives.org or gamblersanonymous.org.uk

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Athlete betting scandals are rocking sports — but there's an upside

• High-profile betting scandals involving athletes are shaking professional and amateur sports.
• Some have faced career-ending bans, highlighting the risks of gambling even as it gains popularity.
• Experts explain how betting is being exposed in the sports world and how it's trying to thwart it.

The expansion of legal sports betting in the US over the last six years has made gambling more popular — including, it seems, among athletes.

2024 is shaping up to be the year of the sports-betting scandal, with several players across professional sports facing lifetime bans.

In April, the NBA permanently banned former Toronto Raptors center Jontay Porter for leaking confidential information and betting on games, including on the Raptors to lose. San Diego Padres player Tucupita Marcano was banned for life in June for gambling on 25 games involving his own team. And, in the UK, Premier League player Lucas Paqueta was charged by the Football Association in May for alleged breaches of its betting rules, which could lead to a lifetime ban if he's found guilty.

It's not just athletes.

A former baseball coach for the University of Alabama was caught last year knowingly sharing insider information with a gambler who had been betting against the team. And there was the April saga in which the former interpreter for Dodgers star Shohei Ohtani was charged with stealing $16 million from the pitcher to pay off his own gambling debts.

It seems every month, a new betting controversy shakes the sports world.

That's not entirely a bad thing.

While the expansion of legal sports betting has made gambling more accessible, it's also helped spot infractions like these. It's bringing to light behaviors that once occurred in the dark, with bets run through bookies or offshore companies.

"Unfortunately, the system is working," said Sara Slane, a consultant who works with teams and other sports properties on betting through her firm Slane Advisory. "It's flushing out when people are betting that should not be betting and having action taken against them."

Given the growing popularity of gambling and the propensity for athletes to take it up, it's hardly surprising that we're seeing a wave of betting scandals in sports. But with new technology and practices being rolled out to track and thwart it, along with a spate of high-profile controversies that have made examples of players who break the rules, 2024 could be the high-water mark for gambling controversies and not the new norm.

Sports-betting activity that once happened in the dark is being brought to light

Gambling scandals, from match-fixing to the sharing of insider information to athletes breaking leagues' betting rules, have long pervaded American sports. Look no further than Major League Baseball legend Pete Rose, who was suspended from the league in 1989 for betting on baseball, including wagering on the team he was managing when he was caught.

That's a big no-no in the MLB and other professional sports. It's a slippery slope from betting on your own team or sport to trying to fix games.

Back then, Rose's gambling habits only surfaced after his bet slips were found at an Ohio restaurant. Meanwhile, Porter's suspicious activity was flagged to the NBA by licensed sportsbooks and a firm that works with sports-betting apps, regulators, and leagues to monitor betting activity. The MLB also said it was tipped off about Marcano's betting activity by a legal sports-betting operator, ESPN reported.

Matt Holt, CEO of IC360, the integrity minority firm that helped flag the suspicious betting activity surrounding Porter and the Alabama baseball coach, said that from 2022 to 2023, there were almost 250 cases of athletes being suspended for "prohibited bettor issues" or betting on a sport they play, which typically violates league rules.

There's little data available to show whether gambling violations like these occur more or less often in the age of legal gambling, in part because they weren't easily tracked before 2018. (Holt said he's seen an uptick, but that's also due to new states introducing legal sports betting and regulators putting up better guardrails.)

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Still, it's reasonable to assume that as sports betting becomes more popular, so has gambling among athletes, who are sports fans themselves.

Six years into the industry's development in the US, the infrastructure and technology are in place to better spot and investigate prohibited and illegal betting within the sports world.

"When you are operating in the dark, you have no idea what is actually happening — if refs are partaking in illegal betting or players are partaking in betting," Slane said. "What the system now has provided is a legal, transparent operation where the leagues and the teams and the operators are working in partnership to identify it and stop it and thwart it."

Many US states where sports betting is legal require gambling companies to work with a licensed independent integrity-monitoring service, like IC360 or Sportradar, to identify suspicious betting activity. Leagues also work with companies like these on their own integrity monitoring.

Generally, these sports-tech companies use AI to monitor multiple data sets, like live odds, live betting data that comes from sportsbooks, and social-media activity. When they identify unusual betting activity, it's investigated by an analyst and then flagged to the relevant licensed sportsbooks, regulators, and sports leagues to take a closer look.

Sports-betting apps also do their own monitoring.

Still, regardless of the progress in information sharing and technology that's making it easier to catch bad actors, these scandals are prematurely ending the careers of promising athletes, like the Iowa State University student-athletes who got caught up in gambling. They're also threatening to undermine the integrity of sports if fans think games are rigged, and giving sports betting a bad rep .

"No one likes the obviously negative backlash," Slane said, "but I think the counter option — burying your head in the sand — is just worse."

Leagues are trying to educate athletes, who can be more prone to problem gambling

Sports leagues and teams from the collegiate to the professional levels are now putting more effort into educating their athletes, trainers, and coaches about gambling.

Studies have shown that athletes are at especially high risk for problem gambling .

"Athletes are more vulnerable to problem gambling because of their nature, natural competitiveness, and win-at-all-costs mentality," said Jim Brown, head of integrity services and athlete wellbeing for North America at Sportradar. "So how do you help educate them about that and how to get resources if needed?"

Some leagues are developing curriculums and bringing in experts to educate players on everything from anti-match-fixing to the role of social media to the impact gambling can have on mental health. On top of gambling addiction, players and coaches have spoken out about being harassed by bettors on social media .

Regulators are also getting involved to protect younger athletes. Brown said Sportradar created programs for Colorado and Ohio, which provide free educational resources to all student-athletes in their states and access to an app where they can report if they're approached about something like match-fixing.

Another challenge: The athletes may not even be aware that they're doing anything wrong when they place a bet on their own sport.

Holt said that in over 90% of those roughly 250 cases of player suspensions for prohibited bets in the last two years, the athletes weren't trying to fix or manipulate the games at all. They could be college football players betting on the NFL, or NFL players betting on games their teams weren't playing in.

He thinks tech can help alongside education.

IC360 launched a product called ProhiBet that teams and colleges can use to upload a list of their players, coaches, and referees so that the app can monitor if they try to place a prohibited bet. It's integrated with about 70 sportsbooks, so the operator and league are notified in real time if an athlete tries to place a prohibited bet, and the player is notified that they're barred from doing so. The goal is to stop the bet from happening before the athlete violates any policies.

"Instead of busting them after the fact, let's stop them from doing it on the front end," Holt said.

The rise of sports gambling and athlete scandals might also force us all to reckon with how pervasive betting has become among young men and the potentially harmful effects. On college campuses, fantasy sports and betting have become social currency among some young men, and students and researchers worry this demographic is more susceptible to developing harmful gambling habits.

As sports-betting continues to expand in more states and the industry evolves, there may be more gambling scandals to come. But some in the industry also hope the recent high-profile examples may make athletes think twice before placing a bet.

"To now see real consequences for the actions — hopefully it course corrects itself, and if it's happening, it stops happening, or they're just being educated about it more," Slane said.

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