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Data Science Meets Sports Gambling: How Researchers Beat the Bookies (newscientist.com) 78

"A trio of data scientists developed a betting strategy to beat bookmakers at football games," writes austro. [The game Americans call soccer.] New Scientist reports: The team studied 10 years' worth of data on nearly half a million football matches and the associated odds offered by 32 bookmakers between January 2005 and June 2015. When they applied their strategy in a simulation, they made a return of 3.5 per cent. Making bets randomly resulted in a loss of 3.32 per cent. Then the team decided to try betting for real. They developed an online tool that would apply their odds-averaging formula to upcoming football matches. When a favorable opportunity arose, a member of the team would email Kaunitz and his wife, one of whom then placed a bet.

They kept this up for five months, placing $50 bets around 30 times a week. And they were winning. After five months the team had made a profit of $957.50 -- a return of 8.5 per cent. But their streak was cut short. Following a series of several small wins, the trio were surprised to find that their accounts had been limited, restricting how much they could bet to as little as $1.25. The gambling industry has long restricted players who appear to show an edge over the house, says Mark Griffiths at Nottingham Trent University, UK.

The paper "illustrates how the sports gambling industry compensates market inefficiencies with discriminatory practices against successful clients," adds austro, noting that the researchers posted a paper explaining their methodology on arxiv last week. "They also made the dataset and source code available on github. And best of all, they made an online publicly available dashboard that shows a live list of bet recommendations on football matches based on their strategy here or here for anyone to try."

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