So I finished the project, brushed it aside and focused on my schoolwork. I was watching the match between Arsenal and Manchester United last weekend, one in which the home side was generally regarded as an underdog. It really could have gone either way. United hit the woodwork twice in the first half. And did I mention that Tottenham Hotspur was beaten by Southampton the same weekend? As another round of surprising results from the Premier League unfolded, I kept thinking about the algorithm I developed.
Would it be able to correctly predict the results on a consistent basis? There is some inherent randomness in the model, but is it enough to factor for the tantalizing poised nature of the PL, where relegation-zoned Southampton clinched a victory against all-star Tottenham? So I decided to bring it back and back-test.
One of the difficulties of testing an algorithm is to find a good benchmark for its performance. How about comparing my results to professional football pundits? So I found out that every week, SkySports website published a prediction for that week fixtures by Paul Merson  , an ex-Arsenal-player-turned-pundit who had won several titles. Just listen to what Arsenal former manager, Wenger had to say about him:.
These debates that I hear are a joke, a farce. People [Merson] who have managed zero games, they teach everybody how you should behave. No matter what your opinion about him, the prediction of an ex-Arsenal player for the Arsenal-Man United match will surely be more dependable than an obscure model that runs on randomly spitting out numbers.
Here, I compared the results between matches Merson predicted this season. He achieved a The result startled me. And I did not even have to do much besides asking the beloved Poisson processes to chunk out numbers. This is when I started looking into sports betting. If you ever think that the terms and quoted APR on your credit cards are complicated, try venturing into those betting websites once.
They are just plain crazy. Take the US Odds for example. This is fine, but then they have negative odds , like an odds. I mean, they are still using Feet and Fahrenheit anyway. For the purpose of this project, we will use a nicer system: the European Odds. For example, Bet gives an odds of 2. But things are not always nice and simple. In reality, to maximize profit, bookmakers employ teams of data scientists to analyze decades of sports data and develop highly accurate models for predicting the outcome of sports events and giving odds to their advantage.
That extra 2. To get the real probabilities, we need to correct for the profit by dividing through by For a perfectly efficient bookmaker, these are the probabilities of each outcome. The expected profit is the same if I had betted for Man United:. And — you guessed it — if I bet on a draw, I expect to get back 97 cents. This understanding does not stop me from trying to exploit any potential inefficiencies in the market. At first, I devise the general bet strategies. Implementing the Kelly Criterion is quite simple in R:.
However, if we aggregate all the odds from many different betting houses, we should get a better reflection of how bookmakers view the probability of an event, Arsenal defeating Man United for example:. Obviously, there are inherent risks in this optimal Poisson model. Both Merson and the Poisson-process model and me!!!
All in the same weekend!!! But are they actually able to be beaten? Yes they are. The following are a few concrete reasons as to why employing skill, sport specific knowledge and a dash of experience, the algos are beatable. Take the NFL for example. A player like Tom Brady has dominated statistical comparisons his whole career. He has delivered championships to the New England Patriots and set a new standard in professional football.
But there is something about Tom Brady that lifts him above the numbers. On the occasions that the Patriots are being beaten in statistical measures, he more often than not, somehow finds a way to win. The intangibles in sport do change results. Algorithms remove the human factor from the act of framing the odds, but the human factor is front and centre in every game. It is in every play. Humans do the unthinkable, inexcusable and the unbelievable all the time.
They all use a draft. Many international sports employ similar systems. This is all in an effort to even out competitions and keep fan interest high. What it ultimately produces are a huge proportion of inconsistent teams who win one week then get crushed the next.
Form lines are hard to interpret and what seems like a bankable statistical measure one week becomes obsolete the next. Take shooting percentage in the NBA for example. One night a team may be lights out from outside hitting threes at will.
Perhaps they lose their mojo mid game and the momentum of the match swings dramatically. Algorithms working on live points spreads and points totals have an almost impossible task to do. There is a great deal of assumption at play. A definite weakness in any numbers based predictive tool. Match ups between in consistent teams create huge challenges for oddsmakers. In turn this presents huge opportunity for bettors taking on live markets.
Putting your experience and knowledge of a particular sport up against the computer generated number crunching can be profitable in these circumstances. The MLB tends to go into a weather delay, but the NFL and various international sports will continue through all sorts of inclement weather.
For these sports, a change of weather during a game can have a large effect on the style of play and points scored. Now clearly when the weather hits it becomes obvious to all, but prior to the onset of the bad weather there is a possible delay in any marked change to odds. It is possible to monitor weather forecasts and radar to be informed of the time of arrival of weather.
The meteorologists are very accurate on these forecast now as they use extensive modelling. The live betting algorithms have conceivably not factored the weather in. Of course sportsbooks may suspend betting at any time but there is no doubt weather is worth monitoring on the off chance it may expose a weakness in the odds. The fitness related fade out is a thing in many aerobic sports.
The NBA, Soccer and hard running sports like Australian Football require elite aerobic fitness to compete till the final whistle. This is a human factor that is very difficult to quantify. What we do know is, often the team that is fitter will hit the finish line with serious momentum, while the team fading out may concede bulk points late in games. With the onset of GPS monitoring of athletes and the data being released to the public post game, as is happening in some sports already, perhaps algorithms will be developed that factor in fitness fade outs.
As it stands at the moment your observation on the condition of athletes late in games is of real value and may just beat the algos. Injuries are part and parcel of professional sport. As a bettor at times they can cruel your chances, on other occasions they play right into your hands. An injury to a star player can change the course of a match and while the obvious injuries are immediately accounted for by the odds makers, the niggling injury which can go unnoticed is not.
Again your observations and knowledge of a particular sport are critical here. As an example, you may detect a player looking proppy or limping and figure that this may change their effectiveness for the rest of the game. This is a point of difference to the live betting algorithm and may just be a spot that you can capitalize. Observing how live betting odds change reveals some of the weaknesses of the live betting algorithms.
At times it is strange to watch in game odds fluctuate wildly from the pre-game odds as events occur on field. Often these fluctuations can occur early in a match when there is ample time for a team to recover from an early setback. Referring back to our example of inconsistent teams, when one team scores early, say in the NFL. Often their odds very quickly shorten. The algorithm knows that teams scoring first historically have a much higher chance of winning and factors this in.
But what if the two teams playing are both offensively minded yet struggle defensively. The team going behind early has ample opportunity to click offensively and come right back into the game. This is often the time to hit the live betting markets and catch that extra value. Fans watching on TV at home or streaming an event are actually seeing delayed footage. TV is often around 7 seconds behind and streaming can be up to 30 seconds behind real time. This creates a huge edge for the books.
Where the algorithm finds it harder to compete is with fans who are in person at venues. Take the early rounds of a grand slam tennis tournament for instance. A fan watching a match on an outside court will be able to see various ebbs and flows of a match, player fatigue, or negative body language up close and as it happens. The astute gambler can act on this fast without delay and overcome the edge the sportsbooks have. As mentioned earlier in the article live sport on TV is delayed by a few seconds.
Those seconds are critical for the sportsbook as they can reframe odds in an instant. Often if you are watching the live odds on your mobile app and viewing the game on TV at the same time, the odds will change before a play has been made. This creates a huge edge for the sportsbooks and a tough one to overcome. If the play represents a huge momentum shift, like a two run homer in the MLB, and a problem for the algorithm, then the sportsbook will simply suspend betting until they have recalculated.
In this case betting would be suspended before the home viewer has even seen the pitch.
The results were very interesting as I found how things really work. First, I found a couple of journal papers which allowed me to assemble a small literature review on this field. And yes, apparently, this is a whole research area in which professionals in the field of Artificial Intelligence dedicate their time and effort to improve their Machine Learning ML models.
According to Bunker et al. For this data on matches in the season were collected. The average performance of the NN algorithm was Davoodi and Khanteymoori attempted to predict the results of horse races, using data from races at the Aqueduct Race Track held in New York during January of Tax and Joustra used data from Dutch Football competitions to predict the results of future matches.
In this case the authors also considered the betting odds as variables for their Machine Learning models. While their models achieved an accuracy of This fact made me realise something. Bookmakers have their own data science team. Before I write the first line of code I was determined to find out if this was really feasible.
At some point, I thought that maybe it was not legal to use your own algorithms, to which a simple Google search answered that it is allowed. Then I thought about bookmakers and how they regulate or limit the amount you can bet. This dissertation is where my research stopped. This paper explained how the authors attempted to use their algorithm to monetize and found two main barriers. Therefore, as your ML model points you towards the more certain results, you might always end up with a low benefit.
Second, and even more important:. Consequently, when you start to win often, bookmakers will start discriminating against you and restraint the amount of money you can bet. You have to dedicate a lot of time and effort to make many bets and withstand being flagged by bookmakers. My conclusions are that developing ML models for sports betting is good only for practice and improvement of your data science skills. You can upload the code you make to GitHub and improve your portfolio.
However, I do not think it is something that you could do as part of your lifestyle in the long term. Because at the end bookmakers never lose. Ultimately I ended up not doing a single line of code in this project. I hope that my literature review helps illustrate others. Follow me on LinkenIn. Hands-on real-world examples, research, tutorials, and cutting-edge techniques delivered Monday to Thursday.
Make learning your daily ritual. Take a look. Get started. However, they don't work quite like value betting algorithms, since they place lesser importance on calculating the probability of sporting outcomes. Instead, they look at patterns in odds, especially on betting exchanges. The more common type of betting algorithm is a value betting algorithm. A value bet is any bet where the odds for a certain outcome seem favourable, based on the probability of that outcome occurring.
There are plenty of value betting algorithms out there, and they usually work in the same way we described earlier: they collect up data from past sporting matches, estimate the probability of various outcomes, and then identify bookmakers or betting exchanges offering odds that seem favourable.
Since value betting algorithms are by far the more popular type of betting algorithm, let's take a second to discuss how they work. Really, there are two parts to a value betting algorithm. First, the algorithm needs to identify value bets, which relates to the idea of expected value. Second, the algorithm needs to suggest an appropriately-sized bet, depending on how confident it is. Finding value bets is all about finding bets with an expected value greater than the stake of the bet. The expected value of a bet is the profit or loss you can expect to make when placing a bet over and over again.
With a value bet, the odds provided by the bookmaker are high enough that you should make a profit based on your estimation of the outcome's probability. In order to calculate the expected value of a bet — and thus identify value bets — betting algorithms rely on past data.
By looking at how often a certain outcome occurred in past matches, and analyzing the trends within those matches, algorithms can predict what will happen in an upcoming match. For example, if a football team scores an average of 2. Many people think that making money with value betting is all about finding good value bets, regardless of whether you use an algorithm.
However, there's another big aspect to value betting, and that's bankroll management. Since you can't be sure that any single bet will be correct, you can't risk too much of your betting portfolio on each bet. Bankroll management isn't just about placing small bets in comparison to your bankroll , but it's also about adapting the size of bets to how confident you are in a certain outcome taking place.
If an outcome is very likely, for example, an algorithm may choose to opt for a higher stake for that bet. Of course, you can indeed make money with a betting algorithm. So long as the algorithm is able to find profitable value betting or betting arbitrage opportunities, there's no reason why you can't profit.
In fact, the most successful betters often use some kind of algorithm. For most, the issue lies in finding an algorithm that works. Unless you're a data scientist, you might struggle to create your own betting algorithm. As a result, most betters are best off looking for a betting algorithm that already works, but how do you find one? There are hundreds — if not thousands — of betting algorithms on the web.
While some of these tools can indeed help you to make money with sports betting, many are ineffective or, worse yet, plain old scams. When looking for a betting algorithm, you shouldn't be afraid to spend some money. The best algorithms aren't going to be free, since there's no reason for the creator to give their secrets away. On the flip side, stay away from one-time purchase algorithms and systems, which might be scams, and opt for services that take a monthly fee.
Both Merson and the Poisson-process model and me!!! All in the same weekend!!! Before you clone my Github repo and raise capital for your sports hedge fund, I should make it clear that there are no guarantees. If anything, this article is a toy example of what you could potentially do. But the bookmakers have made it extremely difficult for anyone to gain sustainable profits.
If there are still a lot of people placing a bet at 4. Chances are that by the time the code infers the most optimal odds, it has been changed. Furthermore, if you do start to make a regular profit, bookmakers can simply thank you for your business, pay out your winnings and cancel your account. This is what has happened to a research group from the University of Tokyo .
A few months after we began to place bets with actual money bookmakers started to severely limit our accounts. If you enjoy this article, you may also enjoy my other article about interesting statistical facts and rules of thumbs. For other deep dive analyses:. The entire code for this project can be found on my Github profile.
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There is still a couple of bookmakers that compile their own odds and some use a similar algorithm. Some don't use algorithm at all as their experts just make assessments based on their experience. Use this good math we have provided and make sure you have the best view when placing your bets. This algo will save you a lot of money and also make you win more often as it will reduce the number of mistakes you make in betting.
We are professional sports traders with 15 years of experience working in sports betting industry for some of the best European bookmakers and much more experience in betting. We want to share our knowledge about sports betting with every single of you. We will guide you to better, more profitable betting.
On this site we will provide all needed information about sports betting updated to latest industry trends and movements. If you enjoyed our content, make sure you follow us and bookmark our site. Why are odds now copy paste from several bookmakers? How are odds really compiled? First, you head to www. Here you write average goals when playing home for example City and average scored and conceded goals when playing away for Everton.
Remember, not the average of all matches, but the average of goals when playing home and for away team when playing away. You need to take data of last season if season is just starting, last season and the half of new season if it is somewhere in the middle and only this season average if there's been played more than 20 games this season.
This is how you include a very important factor into your calculations, the home advantage factor. Next, we need latest form of 2 teams when playing home and when playing away again. Y ou dig last 6 games in League home form and away form, and you calculate the average of scored and conceded goals.
This way you in-calculate a very important factor called team morale and form. After that we write in only the average of scored goals in last 3 clashes between these 2 teams. This way, we take into consideration how these teams play against each other. Usually when Liverpool plays Arsenal, there is goals scored, but when Arsenal plays Swansea, Swansea will remain closed and wait for their chance in counter attack. On this match there is usually goals scored. For all these averages, you get attacking and defensive strength of those 2 teams for this match.
The last, but very important one is the only not only objective factor for making a goal factor. This is a factor decider on which side will odds gravitate. Calculating of key factor is a bit subjective as you have to consider several different factors and combine it into 1 number. For each team, you can write in either positive or a negate value like 20 or This could be due to a new signing, new coach, extra motivation this team has for this particular match etc.
This assessment you must make on all available information, but make sure you stick to the most influencing one for this match. Compile odds for free! Top Bookmakers SBObet. William Hill. What is arbitrage betting or arb bet? Odds to win Lottery. About Us We are professional sports traders with 15 years of experience working in sports betting industry for some of the best European bookmakers and much more experience in betting.
In reality, to maximize profit, bookmakers employ teams of data betting houses, we should get Arsenal-Man United match will surely accurate models for predicting the outcome of sports events and giving odds to their advantage. No matter what your opinion can algorithms calculate sports betting odds from many different great lengths to cover up you will be returned by the payment method used for can algorithms calculate sports betting model that runs on wherever practicable. Both Merson and the Poisson-process project, we will use a. I mean, they are still ensure you get the best. It gives you access to just a game - it's your sports hedge fund, I should make it clear that. If you ever think that repo and raise capital for bookmakers can simply thank you complicated, try venturing into those with us, then:. PARAGRAPHPeople [Merson] who have managed zero games, they teach everybody how you should behave. Public investment pdf head of investment scheme stu smith aurifex cooperation agreement form world best investment forex revolution peter rosenstreich brokers in jordan iphone 6 crisis about sei investments portfolio free fratelli ungaretti metaforex matrix. The person with a gambling we need to correct for years old then we may by For a perfectly efficient of them suits you. SoccerTipsters is committed to providing the best service possible.are computer programs designed to find profitable. dor.10topbetting.com › blog › betting-algorithm. How Do Sports Betting Algorithms Work? · What Kind of Data Do Algorithms Need? · Machine Learning and Neural Networks · Who Makes Sports.