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refactor: remove unused SportMonks integration from the public repo
It was never wired into scoring (weight-0 player-SoT sidecar + a never-called opponent-adjustment experiment), so this changes ZERO predictions — proven: the only pricing-path edit removes _apply_sm_sot, which was hard-gated off (_USE_SM_PLAYER_SOT=False / _SM_SOT_WEIGHT=0.0 -> always returned immediately); 186 tests pass; validators 104/0. - Removed the unused client + fetch scripts + opponent-adjustment experiment (bot/data/sportmonks.py, match_corpus.py, scripts/fetch_*, relevance_backtest.py, research/PAID_API.md) -- recoverable from git history. - Un-wired the weight-0 SoT sidecar in teamstats.py. - Produced data kept locally under neutral names (data/api_cache/, data/players/player_sot_rates.json), gitignored -- nothing lost. - Scrubbed the brand name -> 'the stats API' across the remaining docs/data/config. - git grep -i sportmonks in tracked files -> 0.
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.gitignore

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@@ -19,7 +19,8 @@ data/history/.players_acc.json
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data/history/.players_done.json
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.venv/
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data/footballdata/
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data/sportmonks/
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data/api_cache/
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data/players/player_sot_rates.json
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# Dry-run prediction run-dumps (ISO-timestamped); keep named files + baselines/
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predictions/*T*Z.jsonl

bot/data/match_corpus.py

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bot/data/relevance.py

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@@ -120,7 +120,7 @@ def team_strengths(matches: list[Match], stat: str = "goals") -> dict[str, float
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A simple, leakage-stable team attribute used only as the *opponent-similarity variable* (which
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past opponents resemble the current one). ``stat`` selects the differential: "goals" (history,
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where goal-difference is available) or "shots_on_target" (the sportmonks corpus has no goals, so
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where goal-difference is available) or "shots_on_target" (the stats-api corpus has no goals, so
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SoT-differential is the available dominance proxy). Z-scoring puts sigma on a ~unit scale.
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"""
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diff: dict[str, list[float]] = defaultdict(list)

bot/data/sportmonks.py

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