Former NFL head coach, and current Arizona State coach, Herm Edwards once famously said, “you play to win the game.”. Every once in a blue mood, Edwards’ logic is actually false, and sometimes teams don’t play to win–because they are incentivized NOT to win. At the 2012 Summer Olypmics, for example, several badmitton teams intentionally lost in hopes of securing a more favorable draw through the knockout phases of the tournament.
With the second round of group stage matches complete at the 2018 FIFA World Cup, knockout round qualification is becoming clearer. Several teams have already clinched their spots past the group stage, with a few more near locks to do so on the final match day. There are, however, still a few groups with something left to play for, ensuring dramatic matches during this next week. After running the latest batch of Monte Carlo simulations with my World Cup model to estimate each country’s chances of advancing to the knockout round, I noticed a few neat probability quirks that reveal a lot about which groups are sure to provide viewers with the most exciting final match day.
Introduction With the 2018 FIFA World Cup nearly upon us, we set out to build a model to predict game outcomes and estimate coutries chances of reaching various rounds of the tournament. Ranking systems for various sports, including NCAA Men’s Basketball, NCAA Football, and NBA, have been the basis of several of our projects in the past. With the exception of rankings using ELO, all of our past ranking systems have made use of linear regression in one form or another.