To best perform these testing models, we will be specifically looking at League of Legends, a MOBA, created by Riot Games in 2009. After considering all of this, it is important to mention that some Esports, just as real sports do not have the data available to properly model game and player performance. We do, however, know that Esports is played as both team sports and individual sports, with some games providing hundreds of in-game character choices. With the total prize pool for some games reaching upwards of $100 Million it is becoming more and more important for team owners and coaches to better understand the competition strategies and personnel decision-making optimization pathways.Įsports, specifically LoL, provide a unique way to look at player value since it is hard to quantify them due to the complex invasion nature. While we see that it is substantially easier to model win prediction models and player performance in sports like baseball, as discussed in Sabermetrics, as opposed to complex invasion sports like football, limited research has been done in Esports. With this new focus on Esports, it is now important that Esports catch up in data-driven models. In the past 10 years, Esports has entered the picture as a viable sporting career path for gamers.
![bot of legends menu is too big bot of legends menu is too big](https://i.redd.it/5vlulloonfh61.jpg)
While this area has seen drastic improvements in the past century due to the forming of big data and machine learning, a new area of sports has entered the scene with large scale implications.
BOT OF LEGENDS MENU IS TOO BIG PROFESSIONAL
Tämän esikatselun koko | CC BY-SA 4.0 Introductionįor the past century, research has been conducted in the area of Professional Sports to quantify wins produced, value, optimized lineups, etc.