# How Data Science Affects Sports Betting | Bookmaker & Player Perspectives

Casual sports bettors enjoy the heightened level of excitement that comes with placing wagers on their favourite sporting events. But what chance of success do they really have? What statistical methods are they up against?

The majority of sports bettors base their predictions on emotion and heavily rely on luck — rather than on logic and calculation. It’s not uncommon for punters to get carried away by the potential of a big upset, or to succumb to the temptation of backing a “dead cert” favourite. Some may bet purely because free bets are on offer.

Yet to truly succeed at beating the bookies, sports bettors need a lot more than luck. Consider the data science that’s at play in the battle between bookmakers and professional gamblers.

## Understanding Data Science

Data science is a scientific field that leverages statistics, probabilistic, and linear algebraic methods.

If you conversed with a data scientist within the sports betting field you would, at the very least, grasp that it involves inputting numbers into a system in order to discover hidden patterns and trends. These kinds of mathematical methods enable bookmakers, and professional bettors, to more accurately predict sporting events and improve their performance. Whatever side you’re playing for the ultimate objective is the same: to maximise ROI by making better decisions.

Most sports bettors appreciate the importance of researching upcoming events to reduce emotional attachment and guesswork. This usually involves referring to statistics in an attempt to better predict the outcome. However, very few bettors have the inclination or skillset to go the distance — by mining enormous data sets to extract truly valuable information.

And here’s the thing: data science theorises that using the highest amount of correlated data for a strategy will produce the best winning ratio and ROI.

## How Bookmakers Utilise Data Science

How much do bookmakers lean on data science to gain an advantage over their players?

We automatically expect that every bookie uses some kind of infallible method for setting their prices. But in reality it tends to be that the “sharp” bookies — such as Pinnacle — utilise highly sophisticated methods for setting the odds, while “soft” bookmakers merely follow them and the betting exchanges.

Learn how betting exchanges organically formulate accurate odds.

Sharp bookmakers are known employ teams of data scientists to analyse both current and past data to develop highly accurate models for predicting the outcome of sports events. Number-crunching techniques are leveraged to ensure that their odds are rarely taken advantage of by players. That’s precisely why some sharp bookmakers hold a “winners welcome” policy; they’re confident they’ll beat even the most savvy pros.

Soft bookmakers, on the other hand, are far more cautious when it comes to pro bettors, and regularly limit or close their accounts as a countermeasure. Essentially, they’re not as smart.

But data science not only facilitates the creation of odds. It’s also used to anticipate a customers’ future value, and to segment players into well-defined groups. For instance, bookmakers are able to estimate how long users are likely stay idle before returning to bet, and what what kinds of sports and promotions entices them. This is then used to formulate targeted marketing campaigns that are designed to raise turnover.

Additionally, data science techniques can be used for money-laundering detection, linking related fraudulent accounts, and identifying professional bettors. The applications are varied, and highly valuable.

## How Data Science Helps Sports Bettors

Big data analytics is the key to finding an advantage over the bookmaker.

With relatively elementary methods, bettors can utilise Excel or SPSS (statistical software suite) to collect and analyse data to identify recurring patterns. The tendency for most “intermediate” professional gamblers is to search for price inaccuracies using an array of variables that impact a particular sport — such as player injuries, and shots on goal in football — and then develop a mathematical model around that. Using past and present data, probabilities can be formed for upcoming events (which convert into odds). Then it’s simple a case of identifying prices in the market that represent value.

Aside from compiling odds to find value there are other, more advanced, ways in which sports bettors can utilise data to find an advantage. Many successful pros use web-scraping techniques to collect live odds across an array of bookmakers and betting exchanges to search for recurring patterns. This approach gives a broader overview of the betting markets without delving into the specifics of the sport itself.

For example, a pro may determine that under a particular set of circumstances, a price drop of X%, will usually revert back to it’s original price within time Y. This is valuable knowledge and in my experience, the type of analysis that’s most rewarding in terms of finding value.

Computing and mathematical skills are essential for data scraping, mining, machine learning and other advanced data science methods. Armed with the know-how and tools, professional bettors can find patterns, and simulate betting/trading strategies with far more confidence than by using spreadsheets. Two languages I can recommend to advanced sports bettors are:

• Python — a programming langue that’s particularly well suited to machine learning at a large scale.
• R — an open source programming language that’s designed for statistical analysis and data visualisation.

## Final Thoughts

Data science has emerged as a field that enables us to make wise decisions in different fields such health care, finance, business — and yes, sports betting. It empowers professional bettors with data-based evidence, enabling them to more effectively manage risk and, ultimately, find more opportunities.

It is however worth noting that the popular sports markets usually have the sharpest (most accurate) odds — meaning that even most statistical methods may fail to find a long-term advantage. So my advice is to focus on less-popular sports, events, or betting markets.

Alternatively, look to capitalise on volatile markets where price fluctuations are frequent (e.g. horse racing shortly before the off). It’s vitally important to find something that’s overlooked (rather than obvious), and where value still exists.

Lastly, if you do succeed in idenfiying a recurring pattern, you have to be aware that the bookmakers’ response to savvy players is to close or restrict their accounts. And no amount of analysis or trend-spotting will get around it!