data science in Sports Betting

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In 1995 three option traders and U.S. citizens, Haden Ware, Steve Schillinger and Jay Cohen, moved to Antigua and opened what is probably the first online sports betting platform, World Sports Exchange (WSEX). While online betting was legal in Antigua the platform was in violation of the U.S. Wire Act which forbid the use of telephone lines for inter-state betting. In 2013 Cohen was found guilty and sentenced to 18 months in federal prison. Schillinger was found dead in his Antigua home, an apparent suicide. By the time Ware returned to the U.S. in 2016 to face charges, sentiment toward online betting had changed and he was given a lenient sentence and spared prison time. The U.S. may have viewed them as criminals but they can be considered the pioneers of modern day sports betting. They foresaw interactive wagering during the game as the future of sports gambling. Data Science’s use in sports betting is integral to this $84.6 billion market which is forecast to be $288 billion by 2032.

As of September 2022 sports betting was live and legal  in 31 states and DC. It was legal but not yet launched in five more states: Maine, Massachusetts, Ohio, Florida and Nebraska. It is on the ballot In November for California but was defeated in the legislative body of Vermont, Kentucky, Missouri, Hawaii, Oklahoma, Georgia, Alaska, Alabama, Minnesota and South Carolina. It has yet to come up for consideration in Texas, Utah and Idaho. Clearly still an evolving response in the United States. Even with this state of transition, North America along with Asia-Pacific are the fastest growing regions. Asia-Pacific accounts for almost 30% of total revenue with soccer betting accounting for 23% of the global sports betting market.

While most gamblers base their bets on pure luck or intuition rather than statistics, data science can provide gamblers with better winning chances or turn the odds to their advantage. Players with the most information should have the best chance to make money. The “House” finds data science’s use in sports betting ensure’s odds’ clarity. Of course, betters can also develop their own algorithms or use betting algorithms for sale online to improve their odds. Betting operators and sports data-providing companies are aware of the advantage of using machine learning and data science in odds creation. They endeavor to keep that advantage for themselves and reduce their financial risks by blocking some bettor’s actions like restricting the amount of money a gambler can bet on a certain outcome or limiting the bets on a particular game.

According to Statista, the global sports analytics market is expected to surpass $10 billion by 2028 achieving a compound annual growth rate of 21.8% between 2021 and 2028. Fueling this growth more recently is the use of wearable devices and optical tracking solutions using artificial intelligence for tracking real-time athlete performance through biometrics and biomechanics during competitions. Bookmakers often have to change their odds during a competition which requires a more sophisticated data science’s use in sports betting. Gamblers create their own narrative tension by betting on individual pieces of the action, heightening the entertainment value of the game. The enthusiasm and money bet for this type of gamble means greater demand for faster and more sophisticated data science….both for the bookmakers, the data information providers and the gamblers.

Interested in talking about your career in data science? Contact Smith Hanley Associates’ Data Science and Analytics’ Executive Recruiter, Paul Chatlos at pchatlos@smithhanley.com.

 


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