Forward Availability
Forward Availability forecasts a player's medical availability share for a future season. It is intentionally separate from playing time: a player can be medically available but receive no minutes because they are outside the rotation.
The target is available games divided by known rostered player-games, not games played. Its training panel and binary label are defined in the player-game availability contract.
Current Contract
For target season \(t\), the model uses only completed earlier seasons. An exposure-weighted quadratic age curve provides the pooled baseline. Each player's deviation from that baseline is carried forward with persistence \(\rho\), a gap adjustment, and a small standardized lagged-workload term:
Observed availability updates the state with a beta-binomial-style pseudo-game prior. The first observed season starts from the age baseline, rather than treating a raw \(0/82\) observation as certainty:
Here \(A\) is available games and \(N\) is known rostered player-games. The promoted output is paired with Forward Conditional Minutes to form expected season minutes:
Current Production State: v0.2
The promoted configuration is:
| Parameter | Value |
|---|---|
| State persistence \(\rho\) | 0.50 |
| Later-state update strength \(q_{\mathrm{update}}\) | 60 pseudo-games |
| Initial-state strength \(q_{\mathrm{init}}\) | 15 pseudo-games |
| Lagged workload weight | -0.25 |
It was selected on completed 2020-21 through 2022-23 targets and evaluated on frozen 2023-24 through 2025-26 seasons.
| Mean frozen metric | Age-only control | v0.2 |
|---|---|---|
| Exposure-weighted Brier score | 0.06133 | 0.05816 |
| Binomial log loss | 0.56145 | 0.55168 |
| Player-share MAE | 0.19984 | 0.19145 |
| Player-share RMSE | 0.25888 | 0.25338 |
Artifact:
artifacts/rotation/forward_availability/forward-availability-20260909T233439Z-e341ed5.
Update History
v0.1: Initial State Filter
The first release established the forward-only age curve, filtered player state, pseudo-game update, and frozen evaluation contract. It improved player share MAE but lost to the age-only control on probability-sensitive metrics, which exposed overconfidence in first observed seasons. It was not promoted.
v0.2: First-State Calibration
v0.2 changed only the first-state update: a player's first observed season now
starts from the age baseline with its own tuned pseudo-game strength. This fixes
the failure mode where a missed rookie season produced an implausibly near-zero
forecast. For example, Chet Holmgren's 0 / 82 rookie observation led v0.1 to
forecast 0.3% availability for 2023-24; v0.2 forecast 47.3% before his return,
with 100.0% realized availability.
The v0.2 result cleared every aggregate frozen metric and is the availability component used by Win Projections.