Unveiling Success Drivers in Gaming: A Machine Learning Study Across Steam, Twitch, and Metacritic

This study employs machine learning to assess the relative impact of major platforms—Steam, Twitch, and Metacritic—on video game revenue. Through an integrated analysis of three comprehensive datasets comprising commercially successful titles on Steam, key predictors of financial performance were identified. My analysis establishes Steam‐derived metrics as primary revenue drivers, with follower counts, peak concurrent users (peak CCU), and total reviews exhibiting the strongest predictive power and positive correlation with game earnings. Steam follower counts serve as a significant prelaunch indicator. Further analysis reveals game attributes like Early Access participation generate substantial revenue benefits, while supported languages, genres, and multiplayer features show comparatively weaker effects. Beyond Steam, both Twitch metrics (peak viewers/channels) and Metacritic critic scores exhibit significant positive revenue relationships. This association provides evidence that critical reception and livestreaming visibility collectively substantiate their roles in shaping player behavior to drive game revenue growth. These findings offer actionable insights for developers: prioritize Steam player engagement, supplemented by strategic Twitch marketing and Metacritic outreach. As the first integrated cross‐platform analysis in gaming economics, this research provides a foundation for exploring multiplatform dynamics.