Model Outputs
2025-2026 latest available
No materialized model snapshot for 2016 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 → | 1070 (#143) | - |
| Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → | 900 (#530) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1164 (#57) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 814 (#579) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 931 (#634) | HCA +56 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -10.9 (#541) | HCA +3.0 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.897 (#240) | - |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.006 (#786) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.830 (#221) | AdjNet +13.8 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.002 (#793) | AdjNet -51.8 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.828 (#222) | AdjNet +13.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.002 (#793) | AdjNet -52.3 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.735 (#206) | AdjO 84.3 | AdjD 73.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.028 (#792) | AdjO 61.4 | AdjD 100.6 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.435 (#532) | AdjO 75.9 | AdjD 78.7 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.365 (#526) | 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 → | 0.356 (#542) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 936 (#434) | RD 130 | GP 24 |
2016 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2016-02-04 | vs | Valley Forge | W | 93 - 73 |
2016 Roster
No roster data available for this season.