Model output, not advice.
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Model predictions Book feed as of Tue, Sep 22, 11:07 PM EDT
Model Track Record
Counts only picks made before kickoff
Every pick on this page was generated before its game started and graded against the final result. Anything recorded after a game settled is excluded, so the record here is real forward performance. A model has no record until it has made picks ahead of upcoming games.
Cover rate by model, sport and market against the −110 break-even (52.38%), built on 5,074 forward picks. New picks are graded nightly.
Strong +EV
6
edge ≥ +5pts, n ≥ 30
Strong Fade
18
edge ≤ −5pts, n ≥ 30
⚠ Leak Suspect
0
edge ≥ +20pts (improbable)
Combos
86
model × sport × market
Sport: Market: Min picks:
| Model | Sport / Market | N | Record | Cover | Edge | ROI/pick | Verdict |
|---|---|---|---|---|---|---|---|
[Auto] MLB Player RBIs (Quantile XGB) | MLB · mlb_player_rbis | 130 | 100-30 | 76.9% n=130 · strong [69.7%–84.2%] | — | 46.9% n=130 · strong | n<5 |
[Auto] MLB Player Strikeouts (Poisson) | MLB · mlb_player_strikeouts | 124 | 82-42 | 66.1% n=124 · strong [57.8%–74.5%] | — | 26.2% n=124 · strong | n<5 |
[Auto] MLB Player Home Runs (Quantile XGB) | MLB · mlb_player_home_runs | 311 | 278-33 | 89.4% n=311 · strong [86.0%–92.8%] | — | 70.7% n=311 · strong | n<5 |
[Auto] MLB Moneyline (Ridge Classifier) | MLB · Moneyline | 115 | 66-49 | 57.4% n=115 · strong [48.4%–66.4%] | — | 9.6% n=115 · strong | n<5 |
[Auto] MLB Player Strikeouts (Quantile XGB) | MLB · mlb_player_strikeouts | 124 | 73-51 | 58.9% n=124 · strong [50.2%–67.5%] | — | 12.4% n=124 · strong | n<5 |
[Auto] MLB Player Walks (Quantile XGB) | MLB · mlb_player_walks | 315 | 166-149 | 52.7% n=315 · strong [47.2%–58.2%] | — | 0.6% n=315 · strong | n<5 |
[Auto] MLB Player Walks (Poisson) | MLB · mlb_player_walks | 315 | 213-102 | 67.6% n=315 · strong [62.5%–72.8%] | — | 29.1% n=315 · strong | n<5 |
[Auto] MLB Player RBIs (Poisson) | MLB · mlb_player_rbis | 130 | 99-31 | 76.2% n=130 · strong [68.8%–83.5%] | — | 45.4% n=130 · strong | n<5 |
[Auto] MLB Player Home Runs (Poisson) | MLB · mlb_player_home_runs | 311 | 280-31 | 90.0% n=311 · strong [86.7%–93.4%] | — | 71.9% n=311 · strong | n<5 |
[Auto] MLB Player Hits (Quantile XGB) | MLB · mlb_player_hits | 111 | 71-40 | 64.0% n=111 · strong [55.0%–72.9%] | — | 22.1% n=111 · strong | n<5 |
[Auto] MLB Player Total Bases (Quantile XGB) | MLB · mlb_player_total_bases | 220 | 148-72 | 67.3% n=220 · strong [61.1%–73.5%] | — | 28.4% n=220 · strong | n<5 |
[Auto] MLB Elo Power Ratings Moneyline (LogReg) | MLB · Moneyline | 95 | 46-49 | 48.4% n=95 · marginal [38.4%–58.5%] | — | -7.6% n=95 · marginal | n<5 |
[Auto] MLB Moneyline (ExtraTrees) | MLB · Moneyline | 95 | 42-53 | 44.2% n=95 · marginal [34.2%–54.2%] | — | -15.6% n=95 · marginal | n<5 |
[Auto] MLB Moneyline Classifier (Random Forest) | MLB · Moneyline | 57 | 36-21 | 63.2% n=57 · marginal [50.6%–75.7%] | — | 20.6% n=57 · marginal | n<5 |
[Auto] MLB Run Line (KNN) | MLB · Spread | 55 | 34-21 | 61.8% n=55 · marginal [49.0%–74.7%] | — | 18.0% n=55 · marginal | n<5 |
[Auto] MLB Run Total (LightGBM) | MLB · Total | 56 | 32-21-3 | 60.4% n=53 / 56 · marginal [47.2%–73.5%] | — | 14.4% n=56 · marginal | n<5 |
[Auto] MLB Moneyline Predictor (XGBoost) | MLB · Moneyline | 57 | 38-19 | 66.7% n=57 · marginal [54.4%–78.9%] | — | 27.3% n=57 · marginal | n<5 |
[Auto] MLB Moneyline (ExtraTrees) | MLB · Moneyline | 57 | 35-22 | 61.4% n=57 · marginal [48.8%–74.0%] | — | 17.2% n=57 · marginal | n<5 |
[Auto] MLB Run Total (LightGBM) | MLB · Total | 56 | 34-19-3 | 64.2% n=53 / 56 · marginal [51.2%–77.1%] | — | 21.3% n=56 · marginal | n<5 |
[Auto] MLB Moneyline Predictor (XGBoost) | MLB · Moneyline | 57 | 38-19 | 66.7% n=57 · marginal [54.4%–78.9%] | — | 27.3% n=57 · marginal | n<5 |
[Auto] MLB Run Line (HistGradientBoosting) | MLB · Spread | 56 | 27-29 | 48.2% n=56 · marginal [35.1%–61.3%] | — | -8.0% n=56 · marginal | n<5 |
[Auto] MLB Run Line (KNN) | MLB · Spread | 56 | 29-27 | 51.8% n=56 · marginal [38.7%–64.9%] | — | -1.1% n=56 · marginal | n<5 |
[Auto] MLB Moneyline Classifier (Random Forest) | MLB · Moneyline | 57 | 38-19 | 66.7% n=57 · marginal [54.4%–78.9%] | — | 27.3% n=57 · marginal | n<5 |
[Auto] MLB Elo Power Ratings Moneyline (LogReg) | MLB · Moneyline | 57 | 34-23 | 59.6% n=57 · marginal [46.9%–72.4%] | — | 13.9% n=57 · marginal | n<5 |
[Auto] MLB Run Line (MARS) | MLB · Spread | 56 | 27-29 | 48.2% n=56 · marginal [35.1%–61.3%] | — | -8.0% n=56 · marginal | n<5 |
[Auto] MLB Moneyline (TabPFN) | MLB · Moneyline | 57 | 35-22 | 61.4% n=57 · marginal [48.8%–74.0%] | — | 17.2% n=57 · marginal | n<5 |
[Auto] MLB Moneyline (CatBoost) | MLB · Moneyline | 57 | 39-18 | 68.4% n=57 · marginal [56.4%–80.5%] | — | 30.6% n=57 · marginal | n<5 |
[Auto] NFL Cover Probability (Logistic Regression) | NFL · Moneyline | 32 | 20-12 | 62.5% n=32 · marginal [45.7%–79.3%] | +14.7pts | 19.3% n=32 · marginal | +EV |
[Auto] NFL Cover Probability (Logistic Regression) | NFL · Moneyline | 32 | 19-13 | 59.4% n=32 · marginal [42.4%–76.4%] | +13.5pts | 13.4% n=32 · marginal | +EV |
[Auto] NFL ML Stacking (Calibrated) | NFL · Moneyline | 32 | 20-12 | 62.5% n=32 · marginal [45.7%–79.3%] | +11.9pts | 19.3% n=32 · marginal | +EV |
[Auto] NFL Cover Probability (XGBoost Classifier) | NFL · Moneyline | 32 | 15-17 | 46.9% n=32 · marginal [29.6%–64.2%] | +6.7pts | -10.5% n=32 · marginal | +EV |
[Auto] NFL Cover Probability (Random Forest) | NFL · Moneyline | 32 | 15-17 | 46.9% n=32 · marginal [29.6%–64.2%] | +6.7pts | -10.5% n=32 · marginal | +EV |
[Auto] NFL Moneyline (Ridge Classifier) | NFL · Moneyline | 32 | 17-15 | 53.1% n=32 · marginal [35.8%–70.4%] | +5.8pts | 1.4% n=32 · marginal | +EV |
[Auto] Playbook (Py): Game Total Model (ElasticNet) | NFL · Total | 32 | 18-14 | 56.3% n=32 · marginal [39.1%–73.4%] | +4.1pts | 7.4% n=32 · marginal | +lean |
[Auto] Blueprint (Py): Game Total Model (ElasticNet) | NFL · Total | 32 | 18-14 | 56.3% n=32 · marginal [39.1%–73.4%] | +4.1pts | 7.4% n=32 · marginal | +lean |
[Auto] Blueprint (Py): Full Feature Total (XGB) | NFL · Total | 32 | 17-15 | 53.1% n=32 · marginal [35.8%–70.4%] | +0.9pts | 1.4% n=32 · marginal | flat |
[Auto] Blueprint (Py): Game Total Model (XGB) | NFL · Total | 32 | 17-15 | 53.1% n=32 · marginal [35.8%–70.4%] | +0.9pts | 1.4% n=32 · marginal | flat |
[Auto] Blueprint (Py): Game Total Model (ElasticNet) | NFL · Total | 32 | 17-15 | 53.1% n=32 · marginal [35.8%–70.4%] | +0.8pts | 1.4% n=32 · marginal | flat |
[Auto] Blueprint (Py): Full Feature Total (XGB) | NFL · Total | 32 | 17-15 | 53.1% n=32 · marginal [35.8%–70.4%] | +0.8pts | 1.4% n=32 · marginal | flat |
[Auto] Blueprint (Py): Momentum Spread Model (XGB) | NFL · Spread | 32 | 16-15-1 | 51.6% n=31 / 32 · marginal [34.0%–69.2%] | -0.5pts | -1.4% n=32 · marginal | flat |
[Auto] NFL ATS XGBoost (Custom Objective) | NFL · Spread | 32 | 16-15-1 | 51.6% n=31 / 32 · marginal [34.0%–69.2%] | -0.7pts | -1.4% n=32 · marginal | flat |
[Auto] NFL Spread (KNN) | NFL · Spread | 32 | 16-15-1 | 51.6% n=31 / 32 · marginal [34.0%–69.2%] | -0.8pts | -1.4% n=32 · marginal | flat |
[Auto] NFL Spread (ExtraTrees) | NFL · Spread | 32 | 16-15-1 | 51.6% n=31 / 32 · marginal [34.0%–69.2%] | -0.8pts | -1.4% n=32 · marginal | flat |
[Auto] Blueprint (Py): Full Feature Spread (Mixture of Experts) | NFL · Spread | 32 | 16-15-1 | 51.6% n=31 / 32 · marginal [34.0%–69.2%] | -0.8pts | -1.4% n=32 · marginal | flat |
[Auto] NFL Spread (MARS) | NFL · Spread | 32 | 16-15-1 | 51.6% n=31 / 32 · marginal [34.0%–69.2%] | -1.0pts | -1.4% n=32 · marginal | flat |
[Auto] NFL Online SGD ML | NFL · Moneyline | 32 | 12-20 | 37.5% n=32 · marginal [20.7%–54.3%] | -1.2pts | -28.4% n=32 · marginal | flat |
[Auto] Blueprint (Py): Momentum Spread Model (ElasticNet) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.8pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Full Feature Spread (Stacking Ensemble) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.8pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Full Feature Spread (XGB) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.8pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Market Efficiency Spread (XGBoost) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.8pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Pressure & Efficiency Model (LightGBM) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.8pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Minimal Signal Spread (XGBoost) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.8pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Spread (Gaussian Process) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.8pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Full Feature Spread (Stacking Ensemble) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.9pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Full Feature Spread (XGB) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.9pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Spread (AdaBoost) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.9pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL GNN Matchup | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.9pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Spread Stacking | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.9pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL MLP Spread | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.9pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Spread (SVR) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -3.9pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Momentum Spread Model (ElasticNet) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -4.0pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Turnover Regression Model (ElasticNet) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -4.0pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Multi-Task Spread | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -4.0pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Turnover Regression Model (ElasticNet) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -4.0pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Spread (HistGradientBoosting) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -4.0pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Pressure & Efficiency Model (LightGBM) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -4.1pts | -7.4% n=32 · marginal | fade lean |
[Auto] NFL Spread (SVR) | NFL · Spread | 31 | 15-16 | 48.4% n=31 · marginal [30.8%–66.0%] | -4.2pts | -7.6% n=31 · marginal | fade lean |
[Auto] Blueprint (Py): Turnover Regression Model (ElasticNet) | NFL · Spread | 32 | 15-16-1 | 48.4% n=31 / 32 · marginal [30.8%–66.0%] | -4.3pts | -7.4% n=32 · marginal | fade lean |
[Auto] Blueprint (Py): Simple Elo Spread Model (Linear) | NFL · Spread | 32 | 14-17-1 | 45.2% n=31 / 32 · marginal [27.6%–62.7%] | -6.9pts | -13.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): Simple Elo Spread Model (Bayesian) | NFL · Spread | 32 | 14-17-1 | 45.2% n=31 / 32 · marginal [27.6%–62.7%] | -6.9pts | -13.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): SHAP Explainable Elo Model (Linear) | NFL · Spread | 32 | 14-17-1 | 45.2% n=31 / 32 · marginal [27.6%–62.7%] | -6.9pts | -13.4% n=32 · marginal | Fade |
[Auto] NFL Elo Power Ratings Spread (XGBoost) | NFL · Spread | 32 | 14-17-1 | 45.2% n=31 / 32 · marginal [27.6%–62.7%] | -7.1pts | -13.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): Simple Elo Spread Model (Bayesian) | NFL · Spread | 32 | 14-17-1 | 45.2% n=31 / 32 · marginal [27.6%–62.7%] | -7.1pts | -13.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): SHAP Explainable Elo Model (Linear) | NFL · Spread | 32 | 14-17-1 | 45.2% n=31 / 32 · marginal [27.6%–62.7%] | -7.3pts | -13.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): Simple Elo Spread Model (Linear) | NFL · Spread | 32 | 14-17-1 | 45.2% n=31 / 32 · marginal [27.6%–62.7%] | -7.3pts | -13.4% n=32 · marginal | Fade |
[Auto] NFL Elo Power Ratings Moneyline (LogReg) | NFL · Moneyline | 32 | 17-15 | 53.1% n=32 · marginal [35.8%–70.4%] | -8.7pts | 1.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): Moneyline Model (Random Forest) | NFL · Moneyline | 32 | 10-22 | 31.3% n=32 · marginal [15.2%–47.3%] | -18.4pts | -40.3% n=32 · marginal | Fade |
[Auto] NFL Market Efficiency Moneyline (LogReg) | NFL · Moneyline | 32 | 11-21 | 34.4% n=32 · marginal [17.9%–50.8%] | -19.5pts | -34.4% n=32 · marginal | Fade |
[Auto] NFL Moneyline (ExtraTrees) | NFL · Moneyline | 32 | 11-21 | 34.4% n=32 · marginal [17.9%–50.8%] | -19.5pts | -34.4% n=32 · marginal | Fade |
[Auto] NFL Minimal Signal Moneyline (LogReg) | NFL · Moneyline | 32 | 11-21 | 34.4% n=32 · marginal [17.9%–50.8%] | -19.5pts | -34.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): Moneyline Model (Random Forest) | NFL · Moneyline | 32 | 11-21 | 34.4% n=32 · marginal [17.9%–50.8%] | -19.8pts | -34.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): Moneyline Model (Logistic Regression) | NFL · Moneyline | 32 | 11-21 | 34.4% n=32 · marginal [17.9%–50.8%] | -19.8pts | -34.4% n=32 · marginal | Fade |
[Auto] Blueprint (Py): Moneyline Model (Logistic Regression) | NFL · Moneyline | 32 | 11-21 | 34.4% n=32 · marginal [17.9%–50.8%] | -19.8pts | -34.4% n=32 · marginal | Fade |
[Auto] NFL Moneyline (Voting Ensemble) | NFL · Moneyline | 32 | 10-22 | 31.3% n=32 · marginal [15.2%–47.3%] | -20.9pts | -40.3% n=32 · marginal | Fade |
[Auto] NFL MLP Moneyline | NFL · Moneyline | 32 | 10-22 | 31.3% n=32 · marginal [15.2%–47.3%] | -20.9pts | -40.3% n=32 · marginal | Fade |
[Auto] NFL Moneyline (TabPFN) | NFL · Moneyline | 32 | 10-22 | 31.3% n=32 · marginal [15.2%–47.3%] | -21.1pts | -40.3% n=32 · marginal | Fade |
Methodology: cover_rate = wins / (wins + losses) excluding pushes. edge_vs_break_even = cover_rate − 0.5238 (the 52.38% breakeven for a −110 standard payout). ROI/pick is derived from the same wins and losses at that stated price, then shown as a percentage. Materialized view refreshed via SELECT public.refresh_model_cover_rate_mv() — currently auto-refreshed nightly with the multi-sport grader.