# Using Machine Learning to Predict Game Outcomes Based on Player-Champion Experience in League of Legends

arXiv: https://arxiv.org/abs/2108.02799 · HTML: https://mlsanity.com/paper/2108.02799/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 28 references that are in the map.
- First posted on arXiv 5 Aug 2021.

## Builds on (most cited first, 2 of 2)

- [Player Skill Decomposition in Multiplayer Online Battle Arenas](https://mlsanity.com/paper/1702.06253/) (2017)
- [Using Collaborative Filtering to Recommend Champions in League of Legends](https://mlsanity.com/paper/2006.10191/) (2020)

## Built on by (most cited first, 6 of 6)

- [League of Legends: Real-Time Result Prediction](https://mlsanity.com/paper/2309.02449/) (2023)
- [CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking System](https://mlsanity.com/paper/2406.19720/) (2024)
- [Action2Score: An Embedding Approach To Score Player Action](https://mlsanity.com/paper/2207.10297/) (2022)
- [An Integrated Framework for Team Formation and Winner Prediction in the FIRST Robotics Competition: Model, Algorithm, and Analysis](https://mlsanity.com/paper/2402.00031/) (2024)
- [When to Switch, Not Just What: Transition Quality Prediction in Clash Royale](https://mlsanity.com/paper/2605.21868/) (2026)
- [CHAMP: Cross-domain Hybrid Architecture for Matchmaking and Prediction in Online Multi-Player Games](https://mlsanity.com/paper/2609.04870/) (2026)

## Abstract (arXiv)

League of Legends (LoL) is the most widely played multiplayer online battle arena (MOBA) game in the world. An important aspect of LoL is competitive ranked play, which utilizes a skill-based matchmaking system to form fair teams. However, players' skill levels vary widely depending on which champion, or hero, that they choose to play as. In this paper, we propose a method for predicting game outcomes in ranked LoL games based on players' experience with their selected champion. Using a deep neural network, we found that game outcomes can be predicted with 75.1% accuracy after all players have selected champions, which occurs before gameplay begins. Our results have important implications for playing LoL and matchmaking. Firstly, individual champion skill plays a significant role in the outcome of a match, regardless of team composition. Secondly, even after the skill-based matchmaking, there is still a wide variance in team skill before gameplay begins. Finally, players should only play champions that they have mastered, if they want to win games.