With an implementation in python.

Introduction

Ranking competitors in any sport is tough, and Mixed Martial Arts (MMA) is no exception. In every MMA forum that you can browse online, you will see a range of discussions about the G.O.A.T., and you will also find very little agreement in any posted lists. So, would it be possible to come up with a ranking methodology that multiple people can agree on? Let’s give it a try.

There are multiple ranking methodologies used for sports, but today we will explore the Elo rating system, leaving others for future posts. Elo is a rating system made for calculating players’ relative skill in zero-sum games (i.e. games in which someones victory means someones else loss), making it suitable for combat sports ranking, even though it was conceived in a very different context.

The system itself was actually created in the 1960s as a chess-rating system. and not meant for general sports. Still, its use has expanded to many sports such as soccer, basketball, American football, baseball and many others (FiveThirtyEight has popularized its use for NFL and the Soccer World Cup predictions. For more information, see [1]).

#sports-analytics #python #pandas #rankings #mma #ranking mma fighters using the elo rating system