AFL Player Ratings: How TORP Works

How our AFL player ratings work: TORP blends EPR, a possession-value rating, with PSR, a stats-based rating, into one number for every AFL player.

What is TORP?

TORP (Total On-field Rating of Players) is our headline AFL player rating. It answers one question: how good is this player right now? It is an average of two ratings that look at a player in different ways, EPR and PSR, weighted 50/50. The scale is points of value above a league baseline, so a rating above zero means we expect the player to help his team more than a typical player in his role.

TORP is a rating, not a score for one game. A rating is a smoothed estimate of how a player will perform next. For what a player did in a single match, see how we value individual games.

What goes into TORP?

Two parts, each covering the other’s blind spot.

EPR (Expected Possession Rating) is built from what actually happened on the field. Every disposal, reception, spoil, tackle and hitout in the play-by-play data earns or loses value, based on how it changed the scoring chances of the team in possession. We explain the value of a ball position in AFL expected possession value. EPR has four additive pieces: receiving, disposal, spoiling and hitouts.

PSR (Player Stat Rating) is a regression, a model that finds which statistics best predict a result. We take each player’s recent box-score profile (goals, disposals, tackles, marks and dozens of other statistics), add up the profiles of the 22 players in a team, and fit a model that predicts the match margin. The fitted weights are then read back onto each individual player. PSR splits into an offensive part (OSR) and a defensive part (DSR) that always add up to the whole.

EPR trusts the observed value of a player’s actions. PSR trusts the shape of his statistical profile. A player who is strong on one view and ordinary on the other lands near the middle rather than being over- or under-rated by either.

How is it calculated?

Step 1: credit each game. For every player in every game we add up the value he created. A disposal earns a share of the change in expected points on that play. On a contested kick, the disposer’s share drops from half to a third, because the contest is shared with the player who wins it. Spoils, tackles, pressure acts and hitouts earn value from fixed weights we set by hand. Totals are put on a per-80-minute basis and then centred within each player’s role, so a ruckman is compared with ruckmen and a key defender with key defenders.

Step 2: weight recent games more. Older games count for less, and the rate of decay differs by component. The decay setting is 273 days for receiving, 523 for spoiling, 545 for hitouts and 630 for disposal. Weighting is by minutes on the ground, so a game where a player was on for ten minutes counts for far less than a full game.

Step 3: pull toward average when evidence is thin. A player with three games of data should not be rated as if three games told us everything. We shrink each component toward a prior rate. The prior is worth three games of evidence, so a player with a long record is barely moved and a debutant stays close to the starting value.

Step 4: fit PSR and blend. PSR comes from an elastic-net regression (a regression that drops the statistics it does not need), fitted on matches from seasons before 2025 and tested on 2025 onward. The final rating is TORP = 0.5 x EPR + 0.5 x PSR. Historical ratings use the PSR as it stood at the time, not today’s.

Where can I see it?

Ratings are calculated offline, not live during games, and published as a table the site reads.

What are the limits?

  • TORP is a prediction of a player’s next-game impact, not a verdict on his last game.
  • EPR only sees what the tracking data records. Off-ball work that never shows up as an action is invisible to it.
  • PSR only sees the statistics we count.
  • Players with few games are pulled toward average by design, so a breakout star takes time to register.
  • The weights inside EPR are hand-set constants, not fitted coefficients. They are judgements, and we say so.

How accurate is it?

We test the match forecasts built on TORP by replaying past seasons, refitting each round only on games already played. Across 429 matches in 2025 and 2026 (measured September 2026), the forecast margin was off by 25.6 points on average and the forecast picked the winner in 314 of them, 73%. Its Brier score, the average squared gap between the stated win chance and what happened, was 0.177. Lower is better, and always guessing 50% scores 0.25.