winrate_loss_ranking

To analyze Go game mistakes by winrate drop, this Skill calculates the percentage decrease in expected win probability after each move. It evaluates KataGo analysis results to pinpoint significant player errors for both Black and White.

Winrate loss calculation works by parsing winrate strings from game data to compute the percentage drop from Black's perspective. It applies specific clamping and filtering logic to handle move color perspectives and identify the top mistakes.

Yes, you can use this to rank specific moves from a KataGo analysis. The Skill processes the analysis results to calculate winrate drops and generates a ranked list highlighting the moves with the largest losses in expected win probability.

No specific tools or dependencies are required to parse winrate strings for game analysis. The Skill operates independently to handle the parsing, color perspective adjustments, and clamping logic needed to evaluate your game data.

The best way to identify the biggest errors in your Go game is to rank moves by the severity of their winrate loss. This Skill calculates the exact percentage drop for both Black and White moves, providing targeted feedback for improvement.

The winrate loss calculation uses Black's perspective as a consistent baseline to measure percentage drops for both Black and White moves. This approach ensures accurate comparison and ranking of significant player errors across the entire game.