Davidson
Model Outputs
2025-2026 latest available
No materialized model snapshot for 2024 yet, so this section is showing the latest available team-model rows.
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → | 1019 (#313) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1077 (#201) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1001 (#452) | HCA +56 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +24.0 (#46) | HCA +2.4 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +14.4 (#171) | HCA +3.0 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.994 (#151) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.980 (#83) | AdjNet +33.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.981 (#87) | AdjNet +33.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.908 (#86) | AdjO 89.6 | AdjD 64.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.621 (#179) | AdjO 79.4 | AdjD 74.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.769 (#130) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.730 (#164) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1088 (#211) | RD 350 | GP 1 |
2024 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2023-11-06 | vs | Wash. & Lee | - | Incomplete score |
| 2023-12-16 | vs | Lynchburg | - | Incomplete score |
2024 Roster
Minutes by Position
The surface stays filled across the five on-court roles. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.
| Player | Pos | GP | MIN | PTS | REB | AST | STL | BLK | TO | FGA | Numbers | PM | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Connor Kochera | - | 1 | 17.0 | 17.0 | 3.0 | 1.0 | 0.0 | 0.0 | 0.0 | 11.0 | 10.0 | - | - | - | 63.6 | 75.0 | 0 | - | 77.3 | 77.3 |
| Bobby Durkin | - | 1 | 15.0 | 11.0 | 2.0 | 1.0 | 1.0 | 0.0 | 0.0 | 8.0 | 7.0 | - | - | - | 50.0 | 42.9 | 0 | - | 68.8 | 68.8 |
| David Skogman | - | 1 | 14.0 | 11.0 | 2.0 | 2.0 | 0.0 | 1.0 | 0.0 | 5.0 | 11.0 | - | - | - | 80.0 | 75.0 | 0 | - | 110.0 | 110.0 |
| Grant Huffman | - | 1 | 21.0 | 9.0 | 2.0 | 8.0 | 2.0 | 1.0 | 0.0 | 7.0 | 15.0 | - | - | - | 28.6 | 50.0 | 100.0 | - | 51.4 | 35.7 |
| Mike Loughnane | - | 1 | 15.0 | 9.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 | 3.0 | 7.0 | - | - | - | 100.0 | 100.0 | 0 | - | 150.0 | 150.0 |
| Hunter Adam | - | 1 | 13.0 | 8.0 | 1.0 | 2.0 | 0.0 | 0.0 | 0.0 | 5.0 | 6.0 | - | - | - | 40.0 | 40.0 | 100.0 | - | 68.0 | 60.0 |
| Angelo Brizzi | - | 1 | 16.0 | 7.0 | 2.0 | 3.0 | 1.0 | 0.0 | 2.0 | 5.0 | 6.0 | - | - | - | 60.0 | 33.3 | 0 | - | 70.0 | 70.0 |
| Achile Spadone | - | 1 | 14.0 | 7.0 | 4.0 | 1.0 | 0.0 | 0.0 | 0.0 | 5.0 | 7.0 | - | - | - | 40.0 | 0.0 | 100.0 | - | 55.4 | 40.0 |
| Jarvis Moss | - | 1 | 11.0 | 5.0 | 2.0 | 1.0 | 0.0 | 0.0 | 0.0 | 3.0 | 5.0 | - | - | - | 66.7 | 50.0 | 0 | - | 83.3 | 83.3 |
| Reed Bailey | - | 1 | 14.0 | 4.0 | 1.0 | 2.0 | 0.0 | 0.0 | 1.0 | 3.0 | 3.0 | - | - | - | 66.7 | 0 | 0 | - | 66.7 | 66.7 |
| Michael Katsock | - | 1 | 4.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 1.0 | - | - | - | 50.0 | 50.0 | 0 | - | 75.0 | 75.0 |
| Sean Logan | - | 1 | 15.0 | 3.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 4.0 | 34 | 3.1 | 1217.9 | 100.0 | 0 | 33.3 | -1.51 | 64.7 | 100.0 |
| Riccardo Ghedini | - | 1 | 10.0 | 2.0 | 3.0 | 2.0 | 1.0 | 0.0 | 1.0 | 3.0 | 4.0 | - | - | - | 33.3 | 0.0 | 0 | - | 33.3 | 33.3 |
| Chris Sosnik | - | 1 | 4.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | 0.0 | 0.0 | 100.0 | - | 53.2 | 0.0 |
| Brock Matheny | - | 1 | 4.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | -1.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
| Rikus Schulte | - | 1 | 8.0 | 0.0 | 3.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | 3.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
Numbers/Game vs RAPM
Not enough players with both Numbers/Game and RAPM to plot.
Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG