Our All-Stars and award winners
Our selections · current-season evidence onlyWho deserves recognition according to this season’s measured impact? Every player starts with the same neutral population prior. The model estimates offence, defence and total contribution from this season’s games, rotations and minutes. Most Improved adds a separate last-season comparison.
This merit snapshot is more than 48 hours old. Its original data cutoff remains shown above.
Our major award selections
Point selections rank expected contribution. The frequencies show how often a player leads in the model’s uncertain paths; they are merit probabilities, not actual voting odds. Small samples can produce surprising and fragile selections.
Most Improved comparison and exclusions
Previous-season coverage by team
Our representative teams
Our All-Stars are positionless: 12 from each conference, with the first five labelled starters. These are our merit rosters. Official voting, roster formats and games-played eligibility exceptions are outside this definition.
Every observed player
Contribution is estimated points added above league average; defensive contribution is estimated points prevented. The range contains the middle 80% of model paths. Teammates’ effects are correlated and can be difficult to separate.
| Player | Team | Games / starts | Actual minutes | Contribution | 80% range | Defence | Off / def per 100 | MVP merit | Notes |
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What this model measures
When a full game passes strict lineup, score and minutes checks, the model uses rotation stints. Otherwise it uses the game’s verified team scores with actual player minute shares. A game enters once at one resolution. Aggregate-game rows add extra model noise and assume possession shares follow minute shares. They cannot distinguish teammates as well as rotations.
Stan fits partially pooled offensive and defensive player effects, a league scoring level, home offence and a shared game scoring environment. Generic zero-centred player priors are identical for everybody. Scoring errors use a robust Student-t distribution and estimated possessions. These are statistical attributions within shared lineups, rather than isolated causal player effects.
Current-season regular games supply all evidence for the current player ratings. No preseason player ratings, prior-season performance, salaries, draft slots, market prices or voting history enter this fit. Reported current roster membership and rookie status supply identity and selection metadata only. An unrecognised rookie status is withheld from rookie selections. Most Improved independently fits last season as a comparison only, using coarser team-game observations. The change includes uncertainty and differences in evidence resolution; it does not prove individual development.
Season-end paths hold measured impact and current minutes per appearance fixed, then simulate remaining appearances from this season’s participation and starts. They assume an 82-game team season, current team membership and continuing roles. Departed players keep earned contribution and receive no future minutes. This does not forecast injuries, trades, improvement or future coaching decisions; October evidence makes the extrapolation particularly uncertain.
MVP and All-NBA use total net contribution; DPOY and All-Defence use defensive contribution. Rookie selections use net contribution among reported rookies. Sixth Man uses net contribution among players with a bench majority; a projected point selection needs at least 50% probability of finishing with more bench appearances than starts. Coach and clutch awards require other definitions and are not assessed here.
Stan diagnostics and model checks
Four chains; sampling-only retries retain the same likelihood, priors and input population. Published fits require zero divergences and treedepth hits, structural R-hat ≤1.01, bulk/tail ESS ≥400 and BFMI ≥0.3. Observation coverage below is an in-sample posterior predictive check, not held-out forecast calibration.