Here’s a short list of items invented by the Swiss: cellophane, LSD, Velcro, the computer mouse, white chocolate, the Red Cross, and the — duh — Swiss army knife.
Welp, we can now add “how to win at sports betting” to this great list.
At least that’s the premise behind a paper written by Oliver Merz, Raphael Flepp, and Egon Franck at the University of Zurich’s Business Administration department. Their paper — titled Underestimating Randomness: Outcome Bias in Betting Exchange Markets — posits the following: If you bet on perceived “unlucky” teams when they play “lucky” teams, you will become a bettor with a 4.2% return on investment. Well, at least when you’re betting on the five biggest European soccer leagues in a betting exchange (you can’t get here fast enough, Sporttrade).
Now before you assume the authors of the study were actually taking LSD at the time of the writing, it’s probably worth a check under the hood to see just what, exactly, they found and — even more important — if the notion is transferable to other sports and markets.
Expected value
First: How do the authors define “lucky” and “unlucky” teams? Simple. By utilizing sabermetrics.
They looked at expected goals vs. actual outcomes of the games. To oversimplify things to a large extent — and I’m not kidding, as the authors quickly started getting into terms like “binary probability models” and “lagged table difference” — a “lucky” team would be one that won more games than their expected goals would indicate, and an “unlucky” team would be one that lost more games than their expected goals would indicate.
Next up? Seeing how bettors handled these games on the betting exchanges.
And what they found was not wholly unexpected: People tended to bet more on teams with bettor prior outcomes as opposed to teams with better expected outcomes. Also, the odds on lucky teams were “overstated” and the odds on unlucky teams “understated.”
Solution? Bet on the teams with worse records. Every time.
“Our results stemming from the regression using good luck and bad luck show that the prices of bets on previously lucky teams are overstated,” the authors wrote. “Conversely, the prices of previously unlucky teams are understated. This finding is mirrored in consistently negative returns for bets on previously lucky teams and consistently positive returns for bets on previously unlucky teams. Thus, we form a simple betting strategy by betting on unlucky teams and betting against lucky teams.”
Why do we need to know this? Because, according to the authors, these European soccer bettors do what we’ve all been guilty of: thinking outcomes are the gold standard, and not taking into account the actual randomness of sports.
Any given Sunday, indeed.
The Swiss method
For almost any sport, sabermetrics can help determine what a team’s “true” won-loss record should be. Dating back to Bill James and his Pythagorean Winning Percentage (runs scored squared divided by runs scored squared plus runs allowed squared), figuring out which teams are “lucky” and “unlucky” has been a hobby of many and, probably, a career for others.
Obviously, nothing can be so simple as the Swiss Method (patent pending), right?
“We demonstrate that bettors do not fully consider the influence of good and bad luck on soccer match outcomes,” the authors conclude. “This is reflected in higher returns on bets on previously unlucky teams and lower returns on bets on previously lucky teams. A simple betting strategy based on this finding leads to a net return of 4.2% in an out-of-sample backtest.”
I mean, they did invent cellophane. Maybe they’re onto something. Maybe someone will put it to the test Thursday night when the Philadelphia Phillies (who have three more wins than expected) host the Arizona Diamondbacks (four fewer wins than expected). Gimme five Swiss francs on the D-Backs, please.
