Comments (1)
not to reopen this, I had a showerthought this morning that is it worth also classifying kick offs/restarts in the data so that the algorithm isn't confused by when a team scores and suddenly the ball is being passed around up at the centre circle. Extremely niche and probably not worth the effort to properly deal with as xgboost has access to the fact a goal has been scored (and also because restarts as so sparse anyway)
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Related Issues (20)
- StatsPerform JSON parsers: load data from memory
- Different output for xT values and visualizations in the 'EXTRA-run-xT.ipynb' notebook HOT 1
- Remove off the ball foul events (Wyscout) HOT 5
- What about passes whose outcome is unknown (StatsBomb event data)?
- Fix missing player IDs in the WhoScored converter
- Fix out-of-bounds coordinates in the WhoScored converter
- VAEP feature generators should keep the original index
- The bodypart_onehot feature should set "head/other" to True for "head", "other" and "head/other"
- Handle missing players in the public Wyscout data
- Implement caching for the events.json files in the PublicWyscoutLoader
- original_event_id is sometimes returning 'nan'. HOT 1
- How is a dribble that leads to possession loss modelled? HOT 4
- Unable to download socceraction.vaep HOT 1
- AttributeError: module 'socceraction.spadl' has no attribute 'add_names' HOT 5
- Unable to load Serie A game via PublicWyscoutLoader HOT 2
- Meaning of nb_prev_actions=0? HOT 2
- PerformanceWarning when using socceraction.vaep.features HOT 1
- Opta parser fails to recognize headed passes HOT 2
- Add pass height information to SPADL HOT 3
- Python 3.11 support HOT 4
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