4,446,966 anonymized player records across 29 performance metrics from over 65,000 matches. The data includes match-specific statistics such as kills, distance traveled, and damage dealt for various game modes including solo, duo, and squad play.
Use Cases
- Train a regression model to predict the winPlacePerc based on player performance metrics like kills and damageDealt
- Analyze the correlation between movement features like walkDistance and survival outcomes
- Perform cluster analysis on matchType to identify different playstyles in solo versus squad games
Strengths
- 4,446,966 rows of player data across 29 distinct features
- Includes movement metrics such as walkDistance, rideDistance, and swimDistance
- Features match-type labels for solo, duo, squad, and custom game modes
- Provides target variable winPlacePerc representing the percentile rank of the player or group