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0.41512719381063046 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 100.0, "logLoss": 3.1508147576462653, "coefficients": { "strength": 0.17042948099555852, "record": 0.18674964903865962 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 300.0, "logLoss": 3.28799803871084, "coefficients": { "strength": 0.06816157348354876, "record": 0.07367041416537067 } } ], "protocol": { "version": "intraseason-coefficient-stability-v1", "declaredBeforeScoring": "2026-11-10", "status": "Exploratory follow-up after inspecting earlier forecasts; not an untouched holdout and not tuned to any named current team.", "checkpoints": [ "11-10", "02-01", "03-01" ], "minimumTrainingSeasons": 10, "minimumInnerTrainingSeasons": 5, "ridgeGrid": [ 10.0, 30.0, 100.0, 300.0 ], "ridgeSelection": "For each fixed model, choose the largest ridge whose earlier forward mean title log loss is no more than the best ridge's mean plus one standard error. No target-season loss participates.", "standardError": "Unweighted: sample standard deviation of whole-season losses divided by sqrt(n). Weighted: sqrt(weighted population variance/(effective_n-1)), effective_n=(sum weights)^2/sum(weights^2). For fewer than two effective observations, use zero estimated SE; with no validation seasons choose the largest ridge.", "bootstrapSelection": "Optional nonnegative weights indexed by earlier validation season reselect ridge using the same one-SE rule; target/future years are ignored. Fits normalize supplied season weights to sum to the training-season count.", "cohort": "Use the identical complete-feature historical snapshots and outer test seasons from the prior advanced model at each checkpoint. No new data-driven cohort filtering.", "fullFeatures": [ "strength", "record", "adjusted_off_rating", "adjusted_def_rating", "prior_net_rating", "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "efg_pct", "opp_efg_pct", "turnover_rate", "opp_turnover_rate", "oreb_pct", "dreb_pct", "ft_rate", "opp_ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "nonnegativeFullFeatures": [ "strength", "record", "adjusted_off_rating", "prior_net_rating", "efg_pct", "opp_turnover_rate", "oreb_pct", "dreb_pct" ], "nonpositiveFullFeatures": [ "adjusted_def_rating", "opp_efg_pct", "turnover_rate", "opp_ft_rate" ], "unconstrainedFullFeatures": [ "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "compactFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index", "recent_minutes_continuity" ], "compactDefinitions": { "stable_adjusted_net": "Current adjusted offensive rating minus adjusted defensive rating, then standardized within the as-of league. Score-margin strength, separate offense/defense coefficients and individual shooting-style variables are omitted.", "stable_player_index": "Equal mean of current league-standardized rotation and star box-production proxies, then league-standardized as one composite. This is a proxy, not causal player impact.", "remaining": "Current record, prior-season adjusted net rating and recent minutes continuity are the existing as-of features. All final model inputs are standardized within the snapshot league." }, "compactNonnegativeFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index" ], "constraintInterpretation": "Directional bounds are explicit modeling assumptions for conditional prediction; they do not establish causal effects and may add bias when correlated inputs or proxies behave differently.", "ensemble": { "model": "stable_ensemble", "components": [ "stable_full_ridge", "stable_full_constrained", "stable_compact", "stable_baseline" ], "weights": [ 0.25, 0.25, 0.25, 0.25 ], "rule": "Arithmetic mean of the four independently prior-only one-SE-tuned candidate probability distributions; no weights learned from target outcomes." }, "references": [ "uniform", "record", "strength", "strength_record", "adv_full", "adv_strength_record", "adv_selected" ], "metrics": [ "title_log_loss", "multiclass_brier", "top_pick_accuracy" ], "limits": [ "Very few independent championship outcomes and reused historical seasons limit model comparisons.", "One-standard-error estimates use whole seasons but do not fully model serial dependence between adjacent seasons.", "Coefficient bounds and stronger shrinkage can reduce interpretive instability while worsening predictive accuracy; all scores must be reported.", "No model-specific decisions may be changed in response to Philadelphia, New Orleans or another current team's resulting probability." ] }, "comparisons": [ { "model": "stable_full_ridge", "baseline": "adv_full", "logLossDifference": 0.16415242879813813, "logLossCi95": [ -0.1273306545490527, 0.394906772524549 ], "logLossBlockCi95": [ -0.0026404424935043322, 0.34792471398661867 ], "brierDifference": 0.02791102061655311, "brierCi95": [ -0.09756112940074169, 0.1378885358573608 ], "brierBlockCi95": [ -0.05313389109174734, 0.12416567282211506 ], "blockIntervalNote": "Circular blocks of three retained test seasons, not necessarily three consecutive calendar years." }, { "model": 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Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. 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Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "stable_ensemble", "independentSeasons": 9, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 86, "seasonCount": 9, "champions": 0, "expectedChampions": 0.4577560353461118, "meanPrediction": 0.005322744597047812, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 95, "seasonCount": 9, "champions": 0, "expectedChampions": 1.6691539646278142, "meanPrediction": 0.017570041732924358, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 42, "seasonCount": 9, "champions": 1, "expectedChampions": 1.5911571340768589, "meanPrediction": 0.03788469366849664, "observedFrequency": 0.023809523809523808, "observedFrequencyCi95": [ 0.0, 0.06818181818181818 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 29, "seasonCount": 9, "champions": 2, "expectedChampions": 1.955811435954145, "meanPrediction": 0.0674417736535912, "observedFrequency": 0.06896551724137931, "observedFrequencyCi95": [ 0.0, 0.16666666666666666 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 13, "seasonCount": 6, "champions": 5, "expectedChampions": 1.9040826243851126, "meanPrediction": 0.1464678941834702, "observedFrequency": 0.38461538461538464, "observedFrequencyCi95": [ 0.2, 0.5 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 5, "seasonCount": 4, "champions": 1, "expectedChampions": 1.4220388056099575, "meanPrediction": 0.2844077611219915, "observedFrequency": 0.2, "observedFrequencyCi95": [ 0.0, 0.75 ], "validBootstrapDraws": 2485, "emptyBootstrapDraws": 15 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 0, "seasonCount": 0, "champions": 0, "expectedChampions": 0.0, "meanPrediction": null, "observedFrequency": null, "observedFrequencyCi95": null, "validBootstrapDraws": 0, "emptyBootstrapDraws": 2500 } ], "descriptiveEce": 0.02326004399748698, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." } ], "leaveOneTestSeasonOut": { "stable_full_ridge": { "minimumDifference": 0.11165636730338153, "maximumDifference": 0.2821402063205898, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_full_constrained": { "minimumDifference": 0.1117316255264537, "maximumDifference": 0.2969597910960351, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_compact": { "minimumDifference": 0.001434420295562372, "maximumDifference": 0.24827656906233994, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_baseline": { "minimumDifference": 0.39711364283576295, "maximumDifference": 0.8471693906794595, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_ensemble": { "minimumDifference": 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"(PTS+ORB+DRB+AST+STL+BLK-missedFG-missedFT-TOV) per36; previous season weight0.5, current weight1, 300-minute prior-season league shrinkage; last5-game minute weights.", "currentPlayerCoverageByTeam": { "ATL": 1.0, "BOS": 1.0, "CHA": 1.0, "CHI": 1.0, "CLE": 1.0, "DAL": 1.0, "DEN": 1.0, "DET": 1.0, "GSW": 1.0, "HOU": 1.0, "IND": 0.75, "LAC": 1.0, "LAL": 1.0, "MEM": 1.0, "MIA": 1.0, "MIL": 1.0, "MIN": 1.0, "NJN": 1.0, "NOK": 1.0, "NYK": 1.0, "ORL": 1.0, "PHI": 0.8, "PHX": 1.0, "POR": 1.0, "SAC": 1.0, "SAS": 1.0, "SEA": 1.0, "TOR": 1.0, "UTA": 1.0, "WAS": 1.0 }, "priorPlayerCoverageByTeam": { "ATL": 1.0, "BOS": 1.0, "CHA": 1.0, "CHI": 1.0, "CLE": 1.0, "DAL": 1.0, "DEN": 1.0, "DET": 1.0, "GSW": 1.0, "HOU": 0.9878048780487805, "IND": 1.0, "LAC": 1.0, "LAL": 1.0, "MEM": 1.0, "MIA": 0.975609756097561, "MIL": 1.0, "MIN": 1.0, "NJN": 1.0, "NOP": 1.0, "NYK": 1.0, "ORL": 1.0, "PHI": 1.0, "PHX": 1.0, "POR": 1.0, "SAC": 1.0, "SAS": 1.0, "SEA": 1.0, "TOR": 0.9878048780487805, "UTA": 1.0, "WAS": 1.0 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0.41512719381063046 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 100.0, "logLoss": 3.1508147576462653, "coefficients": { "strength": 0.17042948099555852, "record": 0.18674964903865962 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 300.0, "logLoss": 3.28799803871084, "coefficients": { "strength": 0.06816157348354876, "record": 0.07367041416537067 } } ], "protocol": { "version": "intraseason-coefficient-stability-v1", "declaredBeforeScoring": "2026-11-10", "status": "Exploratory follow-up after inspecting earlier forecasts; not an untouched holdout and not tuned to any named current team.", "checkpoints": [ "11-10", "02-01", "03-01" ], "minimumTrainingSeasons": 10, "minimumInnerTrainingSeasons": 5, "ridgeGrid": [ 10.0, 30.0, 100.0, 300.0 ], "ridgeSelection": "For each fixed model, choose the largest ridge whose earlier forward mean title log loss is no more than the best ridge's mean plus one standard error. No target-season loss participates.", "standardError": "Unweighted: sample standard deviation of whole-season losses divided by sqrt(n). Weighted: sqrt(weighted population variance/(effective_n-1)), effective_n=(sum weights)^2/sum(weights^2). For fewer than two effective observations, use zero estimated SE; with no validation seasons choose the largest ridge.", "bootstrapSelection": "Optional nonnegative weights indexed by earlier validation season reselect ridge using the same one-SE rule; target/future years are ignored. Fits normalize supplied season weights to sum to the training-season count.", "cohort": "Use the identical complete-feature historical snapshots and outer test seasons from the prior advanced model at each checkpoint. No new data-driven cohort filtering.", "fullFeatures": [ "strength", "record", "adjusted_off_rating", "adjusted_def_rating", "prior_net_rating", "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "efg_pct", "opp_efg_pct", "turnover_rate", "opp_turnover_rate", "oreb_pct", "dreb_pct", "ft_rate", "opp_ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "nonnegativeFullFeatures": [ "strength", "record", "adjusted_off_rating", "prior_net_rating", "efg_pct", "opp_turnover_rate", "oreb_pct", "dreb_pct" ], "nonpositiveFullFeatures": [ "adjusted_def_rating", "opp_efg_pct", "turnover_rate", "opp_ft_rate" ], "unconstrainedFullFeatures": [ "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "compactFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index", "recent_minutes_continuity" ], "compactDefinitions": { "stable_adjusted_net": "Current adjusted offensive rating minus adjusted defensive rating, then standardized within the as-of league. Score-margin strength, separate offense/defense coefficients and individual shooting-style variables are omitted.", "stable_player_index": "Equal mean of current league-standardized rotation and star box-production proxies, then league-standardized as one composite. This is a proxy, not causal player impact.", "remaining": "Current record, prior-season adjusted net rating and recent minutes continuity are the existing as-of features. All final model inputs are standardized within the snapshot league." }, "compactNonnegativeFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index" ], "constraintInterpretation": "Directional bounds are explicit modeling assumptions for conditional prediction; they do not establish causal effects and may add bias when correlated inputs or proxies behave differently.", "ensemble": { "model": "stable_ensemble", "components": [ "stable_full_ridge", "stable_full_constrained", "stable_compact", "stable_baseline" ], "weights": [ 0.25, 0.25, 0.25, 0.25 ], "rule": "Arithmetic mean of the four independently prior-only one-SE-tuned candidate probability distributions; no weights learned from target outcomes." }, "references": [ "uniform", "record", "strength", "strength_record", "adv_full", "adv_strength_record", "adv_selected" ], "metrics": [ "title_log_loss", "multiclass_brier", "top_pick_accuracy" ], "limits": [ "Very few independent championship outcomes and reused historical seasons limit model comparisons.", "One-standard-error estimates use whole seasons but do not fully model serial dependence between adjacent seasons.", "Coefficient bounds and stronger shrinkage can reduce interpretive instability while worsening predictive accuracy; all scores must be reported.", "No model-specific decisions may be changed in response to Philadelphia, New Orleans or another current team's resulting probability." ] }, "comparisons": [ { "model": "stable_full_ridge", "baseline": "adv_full", "logLossDifference": 0.16415242879813813, "logLossCi95": [ -0.1273306545490527, 0.394906772524549 ], "logLossBlockCi95": [ -0.0026404424935043322, 0.34792471398661867 ], "brierDifference": 0.02791102061655311, "brierCi95": [ -0.09756112940074169, 0.1378885358573608 ], "brierBlockCi95": [ -0.05313389109174734, 0.12416567282211506 ], "blockIntervalNote": "Circular blocks of three retained test seasons, not necessarily three consecutive calendar years." }, { "model": 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Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." } ], "leaveOneTestSeasonOut": { "stable_full_ridge": { "minimumDifference": 0.11165636730338153, "maximumDifference": 0.2821402063205898, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_full_constrained": { "minimumDifference": 0.1117316255264537, "maximumDifference": 0.2969597910960351, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_compact": { "minimumDifference": 0.001434420295562372, "maximumDifference": 0.24827656906233994, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_baseline": { "minimumDifference": 0.39711364283576295, "maximumDifference": 0.8471693906794595, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_ensemble": { "minimumDifference": 0.11257926584686904, "maximumDifference": 0.3595888752608135, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." } } }, { "id": "01-01", "label": "January 1", "status": "insufficient_data", "reason": "Only 14 verified historical snapshots; the fixed protocol requires at least 15 before fitting this experiment.", "coverage": { "trainingSeasons": 14, "testSeasons": 0 } }, { "id": "02-01", "label": "February 1", "status": "available", "coverage": { "trainingSeasons": 16, "testSeasons": 6, "firstTest": 2016, "lastTest": 2026, "testYears": [ 2016, 2021, 2022, 2023, 2024, 2026 ], "excluded": [ { "season": 1995, "reason": "Previous-season team box-score coverage below95% for at least one team.", "priorTeamCoverage": { "ATL": 1.0, "BOS": 1.0, "CHH": 1.0, "CHI": 1.0, "CLE": 0.9878048780487805, "DAL": 0.9390243902439024, "DEN": 1.0, "DET": 1.0, "GSW": 1.0, "HOU": 1.0, "IND": 1.0, "LAC": 1.0, "LAL": 1.0, "MIA": 1.0, "MIL": 1.0, "MIN": 1.0, "NJN": 1.0, 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"1996-1995-12-26-HOU-VAN", "1996-1995-12-28-DAL-VAN", "1996-1995-12-30-VAN-BOS", "1996-1996-01-05-VAN-PHI", "1996-1996-01-07-VAN-LAC", "1996-1996-01-09-GSW-VAN", "1996-1996-01-10-VAN-DEN", "1996-1996-01-12-VAN-GSW", "1996-1996-01-13-VAN-MIA", "1996-1996-01-18-VAN-CLE", "1996-1996-01-20-VAN-NYK", "1996-1996-01-22-MIL-VAN", "1996-1996-01-24-CHI-VAN", "1996-1996-01-25-TOR-VAN", "1996-1996-01-27-WSB-VAN", "1996-1996-01-29-PHI-VAN", "1996-1996-01-31-BOS-VAN" ] }, { "season": 1997, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "1997-1996-11-08-CLE-VAN", "1997-1996-11-15-UTA-VAN" ] }, { "season": 1998, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "1998-1997-11-01-UTA-DEN", "1998-1997-12-10-CLE-DEN" ] }, { "season": 1999, "reason": "At least one league team has no games before the matched calendar cutoff." }, { "season": 2000, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ 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"reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "2015-2014-12-12-CHI-POR" ] }, { "season": 2017, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "2017-2017-01-20-LAL-IND", "2017-2017-01-29-ATL-NYK" ] }, { "season": 2018, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "2018-2017-12-31-BOS-BKN" ] }, { "season": 2019, "reason": "Per-team player coverage below80% at cutoff or90% in the previous season.", "currentPlayerTeamGameCoverage": 0.982444733420026, "priorPlayerTeamGameCoverage": 1.0, "proxy": "(PTS+ORB+DRB+AST+STL+BLK-missedFG-missedFT-TOV) per36; previous season weight0.5, current weight1, 300-minute prior-season league shrinkage; last5-game minute weights.", "currentPlayerCoverageByTeam": { "ATL": 1.0, "BKN": 0.9811320754716981, "BOS": 1.0, "CHA": 1.0, "CHI": 1.0, "CLE": 1.0, "DAL": 0.9803921568627451, "DEN": 1.0, "DET": 1.0, "GSW": 1.0, "HOU": 1.0, "IND": 1.0, "LAC": 1.0, "LAL": 1.0, 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"record": 0.5655268649521186 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 30.0, "logLoss": 2.99178047649585, "coefficients": { "strength": 0.38451615270140144, "record": 0.3562348900340013 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 100.0, "logLoss": 3.160537749825572, "coefficients": { "strength": 0.16945139332875886, "record": 0.1603545063475521 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 300.0, "logLoss": 3.2951401661606083, "coefficients": { "strength": 0.06597043669977395, "record": 0.06288870190230333 } } ], "protocol": { "version": "intraseason-coefficient-stability-v1", "declaredBeforeScoring": "2026-11-10", "status": "Exploratory follow-up after inspecting earlier forecasts; not an untouched holdout and not tuned to any named current team.", "checkpoints": [ "11-10", "02-01", "03-01" ], "minimumTrainingSeasons": 10, "minimumInnerTrainingSeasons": 5, "ridgeGrid": [ 10.0, 30.0, 100.0, 300.0 ], "ridgeSelection": "For each fixed model, choose the largest ridge whose earlier forward mean title log loss is no more than the best ridge's mean plus one standard error. No target-season loss participates.", "standardError": "Unweighted: sample standard deviation of whole-season losses divided by sqrt(n). Weighted: sqrt(weighted population variance/(effective_n-1)), effective_n=(sum weights)^2/sum(weights^2). For fewer than two effective observations, use zero estimated SE; with no validation seasons choose the largest ridge.", "bootstrapSelection": "Optional nonnegative weights indexed by earlier validation season reselect ridge using the same one-SE rule; target/future years are ignored. Fits normalize supplied season weights to sum to the training-season count.", "cohort": "Use the identical complete-feature historical snapshots and outer test seasons from the prior advanced model at each checkpoint. No new data-driven cohort filtering.", "fullFeatures": [ "strength", "record", "adjusted_off_rating", "adjusted_def_rating", "prior_net_rating", "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "efg_pct", "opp_efg_pct", "turnover_rate", "opp_turnover_rate", "oreb_pct", "dreb_pct", "ft_rate", "opp_ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "nonnegativeFullFeatures": [ "strength", "record", "adjusted_off_rating", "prior_net_rating", "efg_pct", "opp_turnover_rate", "oreb_pct", "dreb_pct" ], "nonpositiveFullFeatures": [ "adjusted_def_rating", "opp_efg_pct", "turnover_rate", "opp_ft_rate" ], "unconstrainedFullFeatures": [ "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "compactFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index", "recent_minutes_continuity" ], "compactDefinitions": { "stable_adjusted_net": "Current adjusted offensive rating minus adjusted defensive rating, then standardized within the as-of league. Score-margin strength, separate offense/defense coefficients and individual shooting-style variables are omitted.", "stable_player_index": "Equal mean of current league-standardized rotation and star box-production proxies, then league-standardized as one composite. This is a proxy, not causal player impact.", "remaining": "Current record, prior-season adjusted net rating and recent minutes continuity are the existing as-of features. All final model inputs are standardized within the snapshot league." }, "compactNonnegativeFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index" ], "constraintInterpretation": "Directional bounds are explicit modeling assumptions for conditional prediction; they do not establish causal effects and may add bias when correlated inputs or proxies behave differently.", "ensemble": { "model": "stable_ensemble", "components": [ "stable_full_ridge", "stable_full_constrained", "stable_compact", "stable_baseline" ], "weights": [ 0.25, 0.25, 0.25, 0.25 ], "rule": "Arithmetic mean of the four independently prior-only one-SE-tuned candidate probability distributions; no weights learned from target outcomes." }, "references": [ "uniform", "record", "strength", "strength_record", "adv_full", "adv_strength_record", "adv_selected" ], "metrics": [ "title_log_loss", "multiclass_brier", "top_pick_accuracy" ], "limits": [ "Very few independent championship outcomes and reused historical seasons limit model comparisons.", "One-standard-error estimates use whole seasons but do not fully model serial dependence between adjacent seasons.", "Coefficient bounds and stronger shrinkage can reduce interpretive instability while worsening predictive accuracy; all scores must be reported.", "No model-specific decisions may be changed in response to Philadelphia, New Orleans or another current team's resulting probability." ] }, "comparisons": [ { "model": "stable_full_ridge", "baseline": "adv_full", "logLossDifference": 0.2601641737715686, "logLossCi95": [ 0.09563351011540067, 0.42540969683599156 ], "logLossBlockCi95": [ 0.21880385072037237, 0.3015244968227648 ], "brierDifference": 0.037798100544245226, "brierCi95": [ -0.0396742998516445, 0.12364112569990167 ], "brierBlockCi95": [ -0.0038961239061836204, 0.07949232499467407 ], "blockIntervalNote": "Circular blocks of three retained test seasons, not necessarily three consecutive calendar years." }, { "model": 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Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "adv_full", "independentSeasons": 6, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 84, "seasonCount": 6, "champions": 0, "expectedChampions": 0.31094725196873424, "meanPrediction": 0.0037017529996277885, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 49, "seasonCount": 6, "champions": 0, "expectedChampions": 0.7799772890465013, "meanPrediction": 0.015917903858091862, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 11, "seasonCount": 5, "champions": 0, "expectedChampions": 0.42598582954026876, "meanPrediction": 0.0387259845036608, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 20, "seasonCount": 6, "champions": 1, "expectedChampions": 1.4603999469828222, "meanPrediction": 0.07301999734914111, "observedFrequency": 0.05, "observedFrequencyCi95": [ 0.0, 0.2 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 12, "seasonCount": 5, "champions": 4, "expectedChampions": 1.7459416531213372, "meanPrediction": 0.14549513776011144, "observedFrequency": 0.3333333333333333, "observedFrequencyCi95": [ 0.2, 0.6 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 3, "seasonCount": 3, "champions": 1, "expectedChampions": 0.8299706470685854, "meanPrediction": 0.2766568823561951, "observedFrequency": 0.3333333333333333, "observedFrequencyCi95": [ 0.0, 1.0 ], "validBootstrapDraws": 2450, "emptyBootstrapDraws": 50 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 1, "seasonCount": 1, "champions": 0, "expectedChampions": 0.446777382271751, "meanPrediction": 0.446777382271751, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 1657, "emptyBootstrapDraws": 843 } ], "descriptiveEce": 0.026934307775667524, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. 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ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "stable_full_ridge", "independentSeasons": 6, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 51, "seasonCount": 6, "champions": 0, "expectedChampions": 0.26037859498836396, "meanPrediction": 0.005105462646830666, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 71, "seasonCount": 6, "champions": 0, "expectedChampions": 1.3032604915902697, "meanPrediction": 0.01835578157169394, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 22, "seasonCount": 6, "champions": 0, "expectedChampions": 0.8444722826015264, "meanPrediction": 0.03838510375461484, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 25, "seasonCount": 6, "champions": 2, "expectedChampions": 1.8754321966586969, "meanPrediction": 0.07501728786634787, "observedFrequency": 0.08, "observedFrequencyCi95": [ 0.0, 0.2 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 9, "seasonCount": 5, "champions": 4, "expectedChampions": 1.1959886686369243, "meanPrediction": 0.13288762984854716, "observedFrequency": 0.4444444444444444, "observedFrequencyCi95": [ 0.25, 0.6666666666666666 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 2, "seasonCount": 2, "champions": 0, "expectedChampions": 0.5204677655242191, "meanPrediction": 0.26023388276210957, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2272, "emptyBootstrapDraws": 228 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 0, "seasonCount": 0, "champions": 0, "expectedChampions": 0.0, "meanPrediction": null, "observedFrequency": null, "observedFrequencyCi95": null, "validBootstrapDraws": 0, "emptyBootstrapDraws": 2500 } ], "descriptiveEce": 0.032539768163381985, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "stable_full_constrained", "independentSeasons": 6, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 51, "seasonCount": 6, "champions": 0, "expectedChampions": 0.25961468870435334, "meanPrediction": 0.005090484092242223, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 71, "seasonCount": 6, "champions": 0, "expectedChampions": 1.3009625545158072, "meanPrediction": 0.018323416260786016, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 22, "seasonCount": 6, "champions": 0, "expectedChampions": 0.8435918687654089, "meanPrediction": 0.038345084943882224, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 25, "seasonCount": 6, "champions": 2, "expectedChampions": 1.874708781247388, "meanPrediction": 0.07498835124989552, "observedFrequency": 0.08, "observedFrequencyCi95": [ 0.0, 0.2 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 9, "seasonCount": 5, "champions": 4, "expectedChampions": 1.1975251744215927, "meanPrediction": 0.1330583527135103, "observedFrequency": 0.4444444444444444, "observedFrequencyCi95": [ 0.25, 0.6666666666666666 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 2, "seasonCount": 2, "champions": 0, "expectedChampions": 0.5235969323454499, "meanPrediction": 0.26179846617272495, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2272, "emptyBootstrapDraws": 228 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 0, "seasonCount": 0, "champions": 0, "expectedChampions": 0.0, "meanPrediction": null, "observedFrequency": null, "observedFrequencyCi95": null, "validBootstrapDraws": 0, "emptyBootstrapDraws": 2500 } ], "descriptiveEce": 0.03253073382590022, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "stable_compact", "independentSeasons": 6, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 45, "seasonCount": 6, "champions": 0, "expectedChampions": 0.22076168100568588, "meanPrediction": 0.004905815133459686, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 74, "seasonCount": 6, "champions": 0, "expectedChampions": 1.3798641163409295, "meanPrediction": 0.018646812382985534, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 28, "seasonCount": 6, "champions": 0, "expectedChampions": 1.0662695158389055, "meanPrediction": 0.03808105413710377, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 20, "seasonCount": 6, "champions": 2, "expectedChampions": 1.4845066339893729, "meanPrediction": 0.07422533169946864, "observedFrequency": 0.1, "observedFrequencyCi95": [ 0.0, 0.2 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 12, "seasonCount": 5, "champions": 4, "expectedChampions": 1.5877640610328865, "meanPrediction": 0.13231367175274053, "observedFrequency": 0.3333333333333333, "observedFrequencyCi95": [ 0.16666666666666666, 0.5555555555555556 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 1, "seasonCount": 1, "champions": 0, "expectedChampions": 0.2608339917922197, "meanPrediction": 0.2608339917922197, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 1633, "emptyBootstrapDraws": 867 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 0, "seasonCount": 0, "champions": 0, "expectedChampions": 0.0, "meanPrediction": null, "observedFrequency": null, "observedFrequencyCi95": null, "validBootstrapDraws": 0, "emptyBootstrapDraws": 2500 } ], "descriptiveEce": 0.03253032561086378, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "stable_ensemble", "independentSeasons": 6, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 43, "seasonCount": 6, "champions": 0, "expectedChampions": 0.21323662428212037, "meanPrediction": 0.004958991262374892, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 79, "seasonCount": 6, "champions": 0, "expectedChampions": 1.4788957662601236, "meanPrediction": 0.018720199572912957, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 22, "seasonCount": 6, "champions": 0, "expectedChampions": 0.85521813309302, "meanPrediction": 0.03887355150422818, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 24, "seasonCount": 6, "champions": 2, "expectedChampions": 1.7313413464950973, "meanPrediction": 0.07213922277062905, "observedFrequency": 0.08333333333333333, "observedFrequencyCi95": [ 0.0, 0.2 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 10, "seasonCount": 5, "champions": 4, "expectedChampions": 1.2396086353653848, "meanPrediction": 0.12396086353653848, "observedFrequency": 0.4, "observedFrequencyCi95": [ 0.23076923076923078, 0.6666666666666666 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 2, "seasonCount": 2, "champions": 0, "expectedChampions": 0.48169949450425387, "meanPrediction": 0.24084974725212693, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2272, "emptyBootstrapDraws": 228 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 0, "seasonCount": 0, "champions": 0, "expectedChampions": 0.0, "meanPrediction": null, "observedFrequency": null, "observedFrequencyCi95": null, "validBootstrapDraws": 0, "emptyBootstrapDraws": 2500 } ], "descriptiveEce": 0.033656111312661316, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." } ], "leaveOneTestSeasonOut": { "stable_full_ridge": { "minimumDifference": 0.19578291503773038, "maximumDifference": 0.31930650922509873, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_full_constrained": { "minimumDifference": 0.1961919066172828, "maximumDifference": 0.31798652156427426, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_compact": { "minimumDifference": 0.2673800973315405, "maximumDifference": 0.4341783209104758, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_baseline": { "minimumDifference": 0.41375201214999313, "maximumDifference": 0.6702996914978476, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_ensemble": { "minimumDifference": 0.2699207565529667, "maximumDifference": 0.4045176949713019, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." } } }, { "id": "03-01", "label": "March 1", "status": "available", "coverage": { "trainingSeasons": 17, "testSeasons": 7, "firstTest": 2012, "lastTest": 2026, "testYears": [ 2012, 2016, 2021, 2022, 2023, 2024, 2026 ], "excluded": [ { "season": 1995, "reason": "Previous-season team box-score coverage below95% for at least one team.", "priorTeamCoverage": { "ATL": 1.0, "BOS": 1.0, "CHH": 1.0, "CHI": 1.0, "CLE": 0.9878048780487805, "DAL": 0.9390243902439024, "DEN": 1.0, "DET": 1.0, "GSW": 1.0, "HOU": 1.0, "IND": 1.0, "LAC": 1.0, "LAL": 1.0, "MIA": 1.0, "MIL": 1.0, "MIN": 1.0, "NJN": 1.0, "NYK": 1.0, "ORL": 1.0, "PHI": 1.0, "PHX": 1.0, "POR": 1.0, "SAC": 1.0, "SAS": 1.0, "SEA": 1.0, "UTA": 0.9634146341463414, "WSB": 0.9878048780487805 } }, { "season": 1996, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "1996-1995-11-03-POR-VAN", "1996-1995-11-05-VAN-MIN", "1996-1995-11-07-DAL-VAN", "1996-1995-11-08-SAS-VAN", "1996-1995-11-10-VAN-LAC", "1996-1995-11-11-SEA-VAN", "1996-1995-11-13-VAN-DAL", "1996-1995-11-16-LAC-VAN", "1996-1995-11-17-VAN-LAL", "1996-1995-11-19-NYK-VAN", "1996-1995-11-22-ORL-VAN", "1996-1995-11-24-CHH-VAN", "1996-1995-11-25-MIA-VAN", "1996-1995-11-28-MIN-VAN", "1996-1995-11-30-VAN-CHI", "1996-1995-12-01-LAL-VAN", "1996-1995-12-03-VAN-MIL", "1996-1995-12-05-PHX-VAN", "1996-1995-12-07-VAN-DET", "1996-1995-12-10-VAN-TOR", "1996-1995-12-13-VAN-HOU", "1996-1995-12-15-VAN-POR", "1996-1995-12-16-VAN-GSW", "1996-1995-12-18-SAC-VAN", "1996-1995-12-19-VAN-SEA", "1996-1995-12-21-SEA-VAN", "1996-1995-12-22-VAN-PHX", "1996-1995-12-26-HOU-VAN", "1996-1995-12-28-DAL-VAN", "1996-1995-12-30-VAN-BOS", "1996-1996-01-05-VAN-PHI", "1996-1996-01-07-VAN-LAC", "1996-1996-01-09-GSW-VAN", "1996-1996-01-10-VAN-DEN", "1996-1996-01-12-VAN-GSW", "1996-1996-01-13-VAN-MIA", "1996-1996-01-18-VAN-CLE", "1996-1996-01-20-VAN-NYK", "1996-1996-01-22-MIL-VAN", "1996-1996-01-24-CHI-VAN", "1996-1996-01-25-TOR-VAN", "1996-1996-01-27-WSB-VAN", "1996-1996-01-29-PHI-VAN", "1996-1996-01-31-BOS-VAN", "1996-1996-02-02-VAN-NJN", "1996-1996-02-05-VAN-UTA", "1996-1996-02-07-UTA-VAN", "1996-1996-02-14-VAN-SAC", "1996-1996-02-16-VAN-ATL", "1996-1996-02-18-VAN-SEA", "1996-1996-02-19-PHX-VAN", "1996-1996-02-25-VAN-SAS", "1996-1996-02-28-VAN-LAL" ] }, { "season": 1997, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "1997-1996-11-08-CLE-VAN", "1997-1996-11-15-UTA-VAN", "1997-1997-02-20-UTA-BOS" ] }, { "season": 1998, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "1998-1997-11-01-UTA-DEN", "1998-1997-12-10-CLE-DEN" ] }, { "season": 2000, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "2000-1999-11-02-CHH-ORL", "2000-1999-11-20-WAS-LAC", "2000-2000-01-10-CLE-LAC", "2000-2000-01-15-UTA-LAC" ] }, { "season": 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2017, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "2017-2017-01-20-LAL-IND", "2017-2017-01-29-ATL-NYK" ] }, { "season": 2018, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "2018-2017-12-31-BOS-BKN" ] }, { "season": 2019, "reason": "Per-team player coverage below80% at cutoff or90% in the previous season.", "currentPlayerTeamGameCoverage": 0.9843581445523193, "priorPlayerTeamGameCoverage": 1.0, "proxy": "(PTS+ORB+DRB+AST+STL+BLK-missedFG-missedFT-TOV) per36; previous season weight0.5, current weight1, 300-minute prior-season league shrinkage; last5-game minute weights.", "currentPlayerCoverageByTeam": { "ATL": 1.0, "BKN": 0.9841269841269841, "BOS": 1.0, "CHA": 1.0, "CHI": 1.0, "CLE": 1.0, "DAL": 0.9836065573770492, "DEN": 1.0, "DET": 1.0, "GSW": 1.0, "HOU": 1.0, "IND": 1.0, "LAC": 1.0, "LAL": 1.0, "MEM": 1.0, "MIA": 1.0, "MIL": 1.0, "MIN": 0.9838709677419355, "NOP": 1.0, "NYK": 0.9838709677419355, "OKC": 1.0, "ORL": 0.9841269841269841, "PHI": 0.8870967741935484, "PHX": 0.7419354838709677, "POR": 1.0, "SAC": 0.9836065573770492, "SAS": 1.0, "TOR": 1.0, "UTA": 1.0, "WAS": 1.0 }, "priorPlayerCoverageByTeam": { "ATL": 1.0, "BKN": 0.9878048780487805, "BOS": 0.9878048780487805, "CHA": 1.0, "CHI": 1.0, "CLE": 1.0, "DAL": 1.0, "DEN": 1.0, "DET": 1.0, "GSW": 1.0, "HOU": 1.0, "IND": 1.0, "LAC": 1.0, "LAL": 1.0, "MEM": 1.0, "MIA": 1.0, "MIL": 1.0, "MIN": 1.0, "NOP": 1.0, "NYK": 1.0, "OKC": 1.0, "ORL": 1.0, "PHI": 1.0, "PHX": 1.0, "POR": 1.0, "SAC": 1.0, "SAS": 1.0, "TOR": 1.0, "UTA": 1.0, "WAS": 1.0 } }, { "season": 2020, "reason": "Excluded under existing pandemic-season protocol." }, { "season": 2025, "reason": "Incomplete/mismatched team box scores at cutoff.", "missingGames": [ "2025-2024-10-25-POR-NOP" ] } ] }, "models": [ { "id": "stable_full_ridge", "name": "Full model \u00b7 strong ridge + one-SE", "features": [ "strength", "record", "adjusted_off_rating", "adjusted_def_rating", "prior_net_rating", 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"stable_player_index": 0.06483775669422731, "recent_minutes_continuity": 0.03773424129275547 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 10.0, "logLoss": 2.861433182573064, "coefficients": { "strength": 0.6941725126368881, "record": 0.5049659374572804 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 30.0, "logLoss": 2.942225561727954, "coefficients": { "strength": 0.4068354758545043, "record": 0.33932784486694023 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 100.0, "logLoss": 3.135581927376204, "coefficients": { "strength": 0.17874577247058016, "record": 0.15780921372384452 } }, { "model": "stable_baseline", "season": 2026, "trainingEnd": 2024, "ridge": 300.0, "logLoss": 3.2840096466777, "coefficients": { "strength": 0.06979697580680527, "record": 0.06275543007382388 } } ], "protocol": { "version": "intraseason-coefficient-stability-v1", "declaredBeforeScoring": "2026-11-10", "status": "Exploratory follow-up after inspecting earlier forecasts; not an untouched holdout and not tuned to any named current team.", "checkpoints": [ "11-10", "02-01", "03-01" ], "minimumTrainingSeasons": 10, "minimumInnerTrainingSeasons": 5, "ridgeGrid": [ 10.0, 30.0, 100.0, 300.0 ], "ridgeSelection": "For each fixed model, choose the largest ridge whose earlier forward mean title log loss is no more than the best ridge's mean plus one standard error. No target-season loss participates.", "standardError": "Unweighted: sample standard deviation of whole-season losses divided by sqrt(n). Weighted: sqrt(weighted population variance/(effective_n-1)), effective_n=(sum weights)^2/sum(weights^2). For fewer than two effective observations, use zero estimated SE; with no validation seasons choose the largest ridge.", "bootstrapSelection": "Optional nonnegative weights indexed by earlier validation season reselect ridge using the same one-SE rule; target/future years are ignored. Fits normalize supplied season weights to sum to the training-season count.", "cohort": "Use the identical complete-feature historical snapshots and outer test seasons from the prior advanced model at each checkpoint. No new data-driven cohort filtering.", "fullFeatures": [ "strength", "record", "adjusted_off_rating", "adjusted_def_rating", "prior_net_rating", "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "efg_pct", "opp_efg_pct", "turnover_rate", "opp_turnover_rate", "oreb_pct", "dreb_pct", "ft_rate", "opp_ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "nonnegativeFullFeatures": [ "strength", "record", "adjusted_off_rating", "prior_net_rating", "efg_pct", "opp_turnover_rate", "oreb_pct", "dreb_pct" ], "nonpositiveFullFeatures": [ "adjusted_def_rating", "opp_efg_pct", "turnover_rate", "opp_ft_rate" ], "unconstrainedFullFeatures": [ "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "compactFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index", "recent_minutes_continuity" ], "compactDefinitions": { "stable_adjusted_net": "Current adjusted offensive rating minus adjusted defensive rating, then standardized within the as-of league. Score-margin strength, separate offense/defense coefficients and individual shooting-style variables are omitted.", "stable_player_index": "Equal mean of current league-standardized rotation and star box-production proxies, then league-standardized as one composite. This is a proxy, not causal player impact.", "remaining": "Current record, prior-season adjusted net rating and recent minutes continuity are the existing as-of features. All final model inputs are standardized within the snapshot league." }, "compactNonnegativeFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index" ], "constraintInterpretation": "Directional bounds are explicit modeling assumptions for conditional prediction; they do not establish causal effects and may add bias when correlated inputs or proxies behave differently.", "ensemble": { "model": "stable_ensemble", "components": [ "stable_full_ridge", "stable_full_constrained", "stable_compact", "stable_baseline" ], "weights": [ 0.25, 0.25, 0.25, 0.25 ], "rule": "Arithmetic mean of the four independently prior-only one-SE-tuned candidate probability distributions; no weights learned from target outcomes." }, "references": [ "uniform", "record", "strength", "strength_record", "adv_full", "adv_strength_record", "adv_selected" ], "metrics": [ "title_log_loss", "multiclass_brier", "top_pick_accuracy" ], "limits": [ "Very few independent championship outcomes and reused historical seasons limit model comparisons.", "One-standard-error estimates use whole seasons but do not fully model serial dependence between adjacent seasons.", "Coefficient bounds and stronger shrinkage can reduce interpretive instability while worsening predictive accuracy; all scores must be reported.", "No model-specific decisions may be changed in response to Philadelphia, New Orleans or another current team's resulting probability." ] }, "comparisons": [ { "model": "stable_full_ridge", "baseline": "adv_full", "logLossDifference": 0.10705869182265511, "logLossCi95": [ -0.07579012136693196, 0.3014862502273781 ], "logLossBlockCi95": [ -0.06828647470186734, 0.24394968690901964 ], "brierDifference": 0.004621298853829646, "brierCi95": [ -0.06725813375169783, 0.09275362342532709 ], "brierBlockCi95": [ -0.0636757215652531, 0.07309381779359657 ], "blockIntervalNote": "Circular blocks of three retained test seasons, not necessarily three consecutive calendar years." }, { "model": 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retained test seasons, not necessarily three consecutive calendar years." }, { "model": "stable_compact", "baseline": "strength_record", "logLossDifference": -0.11515186299311883, "logLossCi95": [ -0.6752011664834263, 0.3926798052220401 ], "logLossBlockCi95": [ -0.552117793138284, 0.3541509793399217 ], "brierDifference": -0.11322082155745959, "brierCi95": [ -0.33520806732237635, 0.0901862880926538 ], "brierBlockCi95": [ -0.2926603814340957, 0.08540905703359179 ], "blockIntervalNote": "Circular blocks of three retained test seasons, not necessarily three consecutive calendar years." }, { "model": "stable_baseline", "baseline": "adv_full", "logLossDifference": 0.25523565764297335, "logLossCi95": [ -0.12022726025575693, 0.652930198712654 ], "logLossBlockCi95": [ -0.06577198487007789, 0.5172801492980976 ], "brierDifference": 0.026198448537971018, "brierCi95": [ -0.09295125644924508, 0.15471164435553927 ], "brierBlockCi95": [ -0.08226550740858282, 0.11442574694802092 ], "blockIntervalNote": 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0.1, "upper": 0.2, "teamForecasts": 9, "seasonCount": 5, "champions": 2, "expectedChampions": 1.2837168729310389, "meanPrediction": 0.14263520810344876, "observedFrequency": 0.2222222222222222, "observedFrequencyCi95": [ 0.0, 0.5 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 5, "seasonCount": 4, "champions": 1, "expectedChampions": 1.543446530695134, "meanPrediction": 0.3086893061390268, "observedFrequency": 0.2, "observedFrequencyCi95": [ 0.0, 0.42857142857142855 ], "validBootstrapDraws": 2493, "emptyBootstrapDraws": 7 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 4, "seasonCount": 4, "champions": 1, "expectedChampions": 2.0461585463780962, "meanPrediction": 0.5115396365945241, "observedFrequency": 0.25, "observedFrequencyCi95": [ 0.0, 0.75 ], "validBootstrapDraws": 2495, "emptyBootstrapDraws": 5 } ], "descriptiveEce": 0.018207472755103867, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "adv_full", "independentSeasons": 7, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 104, "seasonCount": 7, "champions": 0, "expectedChampions": 0.39737007151551845, "meanPrediction": 0.0038208660722646006, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 54, "seasonCount": 7, "champions": 0, "expectedChampions": 0.8898629793308164, "meanPrediction": 0.016478944061681784, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 16, "seasonCount": 7, "champions": 1, "expectedChampions": 0.6089189148468266, "meanPrediction": 0.03805743217792666, "observedFrequency": 0.0625, "observedFrequencyCi95": [ 0.0, 0.2 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 13, "seasonCount": 6, "champions": 2, "expectedChampions": 0.9197273193753307, "meanPrediction": 0.0707482553365639, "observedFrequency": 0.15384615384615385, "observedFrequencyCi95": [ 0.0, 0.2631578947368421 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 16, "seasonCount": 7, "champions": 2, "expectedChampions": 2.116240760555991, "meanPrediction": 0.13226504753474944, "observedFrequency": 0.125, "observedFrequencyCi95": [ 0.0, 0.25 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 6, "seasonCount": 5, "champions": 2, "expectedChampions": 1.5896563635914207, "meanPrediction": 0.26494272726523677, "observedFrequency": 0.3333333333333333, "observedFrequencyCi95": [ 0.0, 0.6666666666666666 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 1, "seasonCount": 1, "champions": 0, "expectedChampions": 0.47822359078409626, "meanPrediction": 0.47822359078409626, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 1646, "emptyBootstrapDraws": 854 } ], "descriptiveEce": 0.017920927639870684, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. 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Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "stable_compact", "independentSeasons": 7, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 77, "seasonCount": 7, "champions": 0, "expectedChampions": 0.3384249637406224, "meanPrediction": 0.004395129399228863, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 68, "seasonCount": 7, "champions": 0, "expectedChampions": 1.250075577564004, "meanPrediction": 0.018383464375941235, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 26, "seasonCount": 7, "champions": 1, "expectedChampions": 0.9904179323027692, "meanPrediction": 0.038092997396260354, "observedFrequency": 0.038461538461538464, "observedFrequencyCi95": [ 0.0, 0.125 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 19, "seasonCount": 7, "champions": 2, "expectedChampions": 1.3194667954885106, "meanPrediction": 0.06944562081518477, "observedFrequency": 0.10526315789473684, "observedFrequencyCi95": [ 0.0, 0.18518518518518517 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 16, "seasonCount": 7, "champions": 1, "expectedChampions": 2.055136667425929, "meanPrediction": 0.12844604171412055, "observedFrequency": 0.0625, "observedFrequencyCi95": [ 0.0, 0.17647058823529413 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 3, "seasonCount": 3, "champions": 3, "expectedChampions": 0.6428035116866583, "meanPrediction": 0.2142678372288861, "observedFrequency": 1.0, "observedFrequencyCi95": [ 1.0, 1.0 ], "validBootstrapDraws": 2458, "emptyBootstrapDraws": 42 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 1, "seasonCount": 1, "champions": 0, "expectedChampions": 0.40367455179150674, "meanPrediction": 0.40367455179150674, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 1646, "emptyBootstrapDraws": 854 } ], "descriptiveEce": 0.02902201676687678, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." }, { "model": "stable_ensemble", "independentSeasons": 7, "bins": [ { "lower": 0.0, "upper": 0.01, "teamForecasts": 64, "seasonCount": 7, "champions": 0, "expectedChampions": 0.3307415276496203, "meanPrediction": 0.005167836369525317, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.01, "upper": 0.03, "teamForecasts": 80, "seasonCount": 7, "champions": 0, "expectedChampions": 1.534027816827619, "meanPrediction": 0.019175347710345236, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.03, "upper": 0.05, "teamForecasts": 25, "seasonCount": 7, "champions": 0, "expectedChampions": 0.9557838052035799, "meanPrediction": 0.03823135220814319, "observedFrequency": 0.0, "observedFrequencyCi95": [ 0.0, 0.0 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.05, "upper": 0.1, "teamForecasts": 24, "seasonCount": 7, "champions": 3, "expectedChampions": 1.7254291870062808, "meanPrediction": 0.07189288279192836, "observedFrequency": 0.125, "observedFrequencyCi95": [ 0.016964285714285765, 0.23529411764705882 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.1, "upper": 0.2, "teamForecasts": 15, "seasonCount": 7, "champions": 3, "expectedChampions": 1.9377985082012583, "meanPrediction": 0.12918656721341723, "observedFrequency": 0.2, "observedFrequencyCi95": [ 0.058823529411764705, 0.3333333333333333 ], "validBootstrapDraws": 2500, "emptyBootstrapDraws": 0 }, { "lower": 0.2, "upper": 0.4, "teamForecasts": 2, "seasonCount": 2, "champions": 1, "expectedChampions": 0.5162191551116423, "meanPrediction": 0.25810957755582115, "observedFrequency": 0.5, "observedFrequencyCi95": [ 0.0, 1.0 ], "validBootstrapDraws": 2275, "emptyBootstrapDraws": 225 }, { "lower": 0.4, "upper": 1.0, "teamForecasts": 0, "seasonCount": 0, "champions": 0, "expectedChampions": 0.0, "meanPrediction": null, "observedFrequency": null, "observedFrequencyCi95": null, "validBootstrapDraws": 0, "emptyBootstrapDraws": 2500 } ], "descriptiveEce": 0.026862410949341133, "note": "Descriptive fixed-bin reliability; entire seasons are bootstrapped. Sparse or empty-champion bins can produce degenerate bootstrap bands, not evidence of certainty. ECE is not a selection criterion and lower Brier/log loss alone does not prove better calibration." } ], "leaveOneTestSeasonOut": { "stable_full_ridge": { "minimumDifference": 0.03650164093663929, "maximumDifference": 0.17781271559810943, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_full_constrained": { "minimumDifference": 0.025832582317908897, "maximumDifference": 0.16484764510684413, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_compact": { "minimumDifference": -0.15046096677029275, "maximumDifference": 0.08275948364822854, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_baseline": { "minimumDifference": 0.10799980476633315, "maximumDifference": 0.3882222607726907, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." }, "stable_ensemble": { "minimumDifference": -0.0057654190362457225, "maximumDifference": 0.15646527480104647, "note": "Influence of omitting one evaluated season from the mean; not an additional backtest." } } } ], "coefficientStability": { "models": [ { "id": "adv_full", "name": "All verified feature groups", "medianCoefficientSd": 0.10473566903576437, "meanPredictionShiftLoso": 0.0033607321157086575, "maxPredictionShiftLoso": 0.0612558284495906, "removedSeasons": [ 2001, 2002, 2004, 2005, 2007, 2008, 2009, 2010, 2011, 2013, 2014, 2015, 2016, 2017, 2018, 2022, 2023, 2024, 2026 ], "note": "Whole training seasons omitted one at a time; feature specification and chosen ridge held fixed. 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0.1328125, "boundaryFraction": null, "constrained": false, "label": "Opponent 3PA rate" }, { "id": "opp_three_pct", "coefficient": -0.014614583213214873, "sd": 0.05726006451292478, "lower95": -0.12283600033883162, "upper95": 0.09809367281595412, "positiveFraction": 0.4140625, "negativeFraction": 0.5859375, "boundaryFraction": null, "constrained": false, "label": "Opponent 3P%" } ], "ridgeSelectionFrequency": { "10.0": 0.04296875, "30.0": 0.802734375, "100.0": 0.15234375, "300.0": 0.001953125 } }, { "id": "stable_compact", "name": "Compact five-feature model", "medianCoefficientSd": 0.1410036093811058, "meanPredictionShiftLoso": 0.001440771986189138, "maxPredictionShiftLoso": 0.017069690253309677, "removedSeasons": [ 2001, 2002, 2004, 2005, 2007, 2008, 2009, 2010, 2011, 2013, 2014, 2015, 2016, 2017, 2018, 2022, 2023, 2024, 2026 ], "note": "Whole training seasons omitted one at a time; feature specification and chosen ridge held fixed. 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This is influence analysis, not validation.", "features": [ { "id": "strength", "coefficient": 0.5373619623251981, "sd": 0.1323196503176788, "lower95": 0.29414989872145886, "upper95": 0.7926258455250248, "positiveFraction": 1.0, "negativeFraction": 0.0, "boundaryFraction": null, "constrained": false, "label": "Strength z-score" }, { "id": "record", "coefficient": 0.6751798789251852, "sd": 0.10872440868584572, "lower95": 0.3974667503172224, "upper95": 0.846496705503714, "positiveFraction": 1.0, "negativeFraction": 0.0, "boundaryFraction": null, "constrained": false, "label": "Record z-score" } ], "ridgeSelectionFrequency": { "10.0": 0.974609375, "30.0": 0.025390625 } }, { "id": "stable_ensemble", "name": "Equal-weight stability ensemble", "medianCoefficientSd": null, "meanPredictionShiftLoso": 0.0012645915229416692, "maxPredictionShiftLoso": 0.017589081902831677, "features": [], "note": "Probability average has no single coefficient vector; family penalties held fixed during leave-one-season-out influence." } ] }, "intervalMethodology": { "method": "Equal-family sensitivity mixture with shared whole-season Bayesian-bootstrap refits", "drawsPerFamily": 512, "scope": [ "Four fixed research families receive equal weight; their probability predictions are averaged for the ensemble point estimate.", "Every refit uses the same Exp(1) weights keyed to entire historical seasons across all families; weights sum to the training-season count.", "Each draw reselects the ridge penalty using weighted earlier forward validation losses, then refits coefficients on weighted earlier seasons.", "80% and 95% sensitivity ranges are quantiles of the equally weighted family-and-refit mixture, not confidence intervals for the ensemble mean.", "Separate ensemble-refit ranges average the four families within each shared draw before taking quantiles; these include coefficient and partial ridge-selection variation at fixed family weights." ], "limitations": [ "Family weights are declared research scenarios, not inferred probabilities that each model is true; the family set is incomplete.", "Ridge reselection reweights saved earlier validation losses; it does not rebuild the inner validation fits, so selection uncertainty is only partially represented.", "As-of team features remain fixed. Measurement error, evolving team strength, injuries, future roster changes and calibration uncertainty remain omitted.", "These ranges have no established 80% or 95% coverage of the true title probability; one binary championship outcome cannot validate an individual probability interval.", "Team bands are marginal, not simultaneous portfolio limits. Their endpoints need not sum to 100%, although each simulated league probability vector does.", "Historical comparisons reuse inspected seasons and are exploratory. Different checkpoints in the same season are not independent champions." ] }, "protocol": { "version": "intraseason-coefficient-stability-v1", "declaredBeforeScoring": "2026-11-10", "status": "Exploratory follow-up after inspecting earlier forecasts; not an untouched holdout and not tuned to any named current team.", "checkpoints": [ "11-10", "02-01", "03-01" ], "minimumTrainingSeasons": 10, "minimumInnerTrainingSeasons": 5, "ridgeGrid": [ 10.0, 30.0, 100.0, 300.0 ], "ridgeSelection": "For each fixed model, choose the largest ridge whose earlier forward mean title log loss is no more than the best ridge's mean plus one standard error. No target-season loss participates.", "standardError": "Unweighted: sample standard deviation of whole-season losses divided by sqrt(n). Weighted: sqrt(weighted population variance/(effective_n-1)), effective_n=(sum weights)^2/sum(weights^2). For fewer than two effective observations, use zero estimated SE; with no validation seasons choose the largest ridge.", "bootstrapSelection": "Optional nonnegative weights indexed by earlier validation season reselect ridge using the same one-SE rule; target/future years are ignored. Fits normalize supplied season weights to sum to the training-season count.", "cohort": "Use the identical complete-feature historical snapshots and outer test seasons from the prior advanced model at each checkpoint. No new data-driven cohort filtering.", "fullFeatures": [ "strength", "record", "adjusted_off_rating", "adjusted_def_rating", "prior_net_rating", "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "efg_pct", "opp_efg_pct", "turnover_rate", "opp_turnover_rate", "oreb_pct", "dreb_pct", "ft_rate", "opp_ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "nonnegativeFullFeatures": [ "strength", "record", "adjusted_off_rating", "prior_net_rating", "efg_pct", "opp_turnover_rate", "oreb_pct", "dreb_pct" ], "nonpositiveFullFeatures": [ "adjusted_def_rating", "opp_efg_pct", "turnover_rate", "opp_ft_rate" ], "unconstrainedFullFeatures": [ "retained_minutes_share", "rotation_box_production", "star_box_production", "recent_minutes_continuity", "ft_rate", "pace", "three_attempt_rate", "three_pct", "opp_three_attempt_rate", "opp_three_pct" ], "compactFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index", "recent_minutes_continuity" ], "compactDefinitions": { "stable_adjusted_net": "Current adjusted offensive rating minus adjusted defensive rating, then standardized within the as-of league. Score-margin strength, separate offense/defense coefficients and individual shooting-style variables are omitted.", "stable_player_index": "Equal mean of current league-standardized rotation and star box-production proxies, then league-standardized as one composite. This is a proxy, not causal player impact.", "remaining": "Current record, prior-season adjusted net rating and recent minutes continuity are the existing as-of features. All final model inputs are standardized within the snapshot league." }, "compactNonnegativeFeatures": [ "stable_adjusted_net", "record", "prior_net_rating", "stable_player_index" ], "constraintInterpretation": "Directional bounds are explicit modeling assumptions for conditional prediction; they do not establish causal effects and may add bias when correlated inputs or proxies behave differently.", "ensemble": { "model": "stable_ensemble", "components": [ "stable_full_ridge", "stable_full_constrained", "stable_compact", "stable_baseline" ], "weights": [ 0.25, 0.25, 0.25, 0.25 ], "rule": "Arithmetic mean of the four independently prior-only one-SE-tuned candidate probability distributions; no weights learned from target outcomes." }, "references": [ "uniform", "record", "strength", "strength_record", "adv_full", "adv_strength_record", "adv_selected" ], "metrics": [ "title_log_loss", "multiclass_brier", "top_pick_accuracy" ], "limits": [ "Very few independent championship outcomes and reused historical seasons limit model comparisons.", "One-standard-error estimates use whole seasons but do not fully model serial dependence between adjacent seasons.", "Coefficient bounds and stronger shrinkage can reduce interpretive instability while worsening predictive accuracy; all scores must be reported.", "No model-specific decisions may be changed in response to Philadelphia, New Orleans or another current team's resulting probability." ] }, "recommendation": { "promote": false, "reason": "Research comparison: the main forecast and market default remain unchanged. Stability is assessed separately from accuracy; these inspected historical cohorts do not establish a reliable replacement." }, "limitations": [ "The sign constraints are explicit modeling assumptions, not causal claims; their sign consistency is imposed. Boundary frequency shows when the constraint binds.", "The November comparison has nine independent championship outcomes; February and March reuse some of the same seasons and are reported separately.", "A smaller coefficient standard deviation can reflect shrinkage bias or imposed bounds. Prediction influence and held-out scores must also be checked.", "All original model forecasts, including the full advanced model, remain frozen for comparison.", "Family weights are declared research scenarios, not inferred probabilities that each model is true; the family set is incomplete.", "Ridge reselection reweights saved earlier validation losses; it does not rebuild the inner validation fits, so selection uncertainty is only partially represented.", "As-of team features remain fixed. Measurement error, evolving team strength, injuries, future roster changes and calibration uncertainty remain omitted.", "These ranges have no established 80% or 95% coverage of the true title probability; one binary championship outcome cannot validate an individual probability interval.", "Team bands are marginal, not simultaneous portfolio limits. Their endpoints need not sum to 100%, although each simulated league probability vector does.", "Historical comparisons reuse inspected seasons and are exploratory. Different checkpoints in the same season are not independent champions." ], "audit": { "inputHashes": { "data\\championship\\advanced-season-features.json": "e9b991ca97738f712aa3427f3913a47be77c500a0e9f0ce597e4037750825ce8", "public\\data\\championship-advanced.json": "7fa4e64e26ea5d8204ec7f81aed363d2213d98f2cc387f1564e2c7ea21ac59e8", "data\\championship\\advanced-season-features-02-01.json": "4e49e772775c9585c5c495ab1900f8965157104041b3ab277f28581e9511d8ac", "data\\championship\\advanced-season-features-03-01.json": "85174c635f58c6cc8b71e5fed23c44ee14d130e8203a614bfe4ceaed739cddb5" }, "sourceCodeHashes": { "stability_model.py": "433a00875b9b6f1be83d3613f312cb052f7350c0488d257ef4d14390cf331282", "stability_uncertainty.py": "d708ec04476589b105de4740c17e432949b6864c0cacb44a0958be3f50699b31", "run_stability.py": "9590992ef55d1a18ed114849258134edb96ab65036de179c158dab9eddd94cff" }, "protocolHash": "16883df40a53676b90f5b105c969973ef81006dbbc88889f1279f76e73ed5673" } }