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Physics

How to beat the bookies by turning their odds against them

Bookmakers use complex prediction models to set the odds of sporting outcomes in their favour 鈥 but a simple analysis of available odds can still give good returns

By Chris Baraniuk

16 October 2017

Man sits at betting machines

The bookies collectively know best – so you use their odds to guide bets,聽so the claim goes

Matthew Lloyd/Bloomberg via Getty Images

Fancy a flutter? The chances of making a profit by betting on football matches are extremely low, but a trio of researchers has managed to beat the odds with a simple formula.

Mathematicians had already developed bookie-beating models that attempt to predict the outcome of sports matches, but they are difficult to devise and don’t always perform consistently. Lisandro Kaunitz at the University of Tokyo and his colleagues wanted to know if a more direct approach would work: using the bookmakers鈥 own odds against them.

The team studied 10 years鈥 worth of data on nearly half a million football matches and the associated odds offered by 32 bookmakers between January 2005 and June 2015. For every game, they looked for odds that might yield a better return than the average offered by bookies 鈥 say, 5 to 1 versus a mean of 2 to 1.

鈥淯sing the odds that are published, you can get a very good estimate of an event occurring,鈥 says team member Javier Kreiner, a data scientist at transport start-up CargoX in S茫o Paulo, Brazil. 鈥淲hat鈥檚 the probability of Barcelona winning against Real Madrid, for example.鈥

Mean odds of 2 to 1 suggest the bookies collectively think this reflects fair odds for that outcome. But 5 to 1 offers higher returns should the outcome materialise. The team used the historical data to work out the optimal distance from the mean odds 鈥 the one that would give a positive payout for the largest number of games.

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.

Into real time

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 favourable 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 鈥 a return of 8.5 per cent. There were some administrative costs, such as the expense of running servers to keep track of聽the odds in real time. But Kaunitz and his wife did get to splash out on a nice dinner in Tokyo, he says. 鈥淲e were excited but it鈥檚 worth mentioning 鈥 you need to spend a lot of time to do it.鈥

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.

A spokesman for William Hill, one of the bookmakers used by the team, said betting is sometimes restricted 鈥渋n a small number of cases鈥.

鈥淭his can be for a number of reasons, including bonus abuse and taking proportionately more than their fair share of special offers and enhanced prices, which are designed for the many rather than a few,鈥 he says.

The gambling industry has long restricted players who appear to show an edge over the house, says Mark Griffiths at Nottingham Trent University, UK. A classic example is card-counting, which can help players win at blackjack. Casinos are quick to expel those who try it and it is sometimes flagged as cheating. But it鈥檚 not illegal in the US or the UK.

Trapping bots

Griffiths compares the team鈥檚 approach to card-counting. 鈥淚t鈥檚 not cheating at all 鈥 it鈥檚 using mathematics to try and beat a particular system,鈥 he says.

Online bookmakers have very tight profit margins, so some offer generous odds for very short periods of time on certain matches to lure automated or expert betting systems out into the open, says economist David Forrest at the University of Liverpool, UK. 鈥淭hey will try to trap the robots,鈥 he says. 鈥淎nyone who responds has their account closed.鈥

Some of the researchers鈥 accounts may have fallen foul of this system. In some cases they found they could not bet at all after signing up with certain bookies. If so, then this suggests their technique really was finding the best odds out there. But the house still always wins in the end.

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