That allowed the team to calculate the likelihood that their first result was a fluke. In that case, the bets paid out 39 percent of time at a return of -3.2 percent, which is equivalent to loss of $93,000. Could they simply have got lucky? So the team compared their results to 2,000 simulations in which they placed bets randomly on the same games. “For an imaginary stake of $50 per bet, this corresponds to an equivalent profit of $98,865 across 56,435 bets,” they say.Īn important question is whether this result could have been pure chance.
This simulation paid out 44 percent of the time and delivered a yield of 3.5 percent over the 10-year period.
They calculated the average odds, found any outliers, and then worked out whether a bet would favor them or not.īefore committing any real money, the researchers tested the idea on 10 years of historical data on the closing odds and results of 479,440 soccer games played between 20. They built a Web crawler that gathered the odds offered by online betting companies on soccer games around the world. And that’s exactly what Kaunitz and co have done.
