| Number of wins per team | |||
| Based on 1,000 simulations, from round 11, 2026. | |||
| Team | Average | Minimum | Maximum |
|---|---|---|---|
| Fremantle | 17 | 14 | 21 |
| Sydney | 17 | 14 | 21 |
| Geelong | 16 | 12 | 19 |
| Brisbane | 14 | 11 | 18 |
| Hawthorn | 14 | 11 | 18 |
| Gold Coast | 13 | 10 | 17 |
| Adelaide | 13 | 9 | 17 |
| Melbourne | 13 | 9 | 17 |
| Footscray | 12 | 8 | 15 |
| Collingwood | 11 | 8 | 16 |
| St Kilda | 11 | 7 | 15 |
| GWS | 10 | 6 | 14 |
| N. Melbourne | 8 | 5 | 13 |
| Port Adelaide | 8 | 5 | 13 |
| Carlton | 7 | 4 | 12 |
| West Coast | 6 | 3 | 10 |
| Essendon | 5 | 2 | 9 |
| Richmond | 3 | 1 | 7 |
Round predictions
Updated 2026-05-25.
| St Kilda v Hawthorn | ||
| 28 May @ Docklands | ||
|
Hawthorn by 2 points.
Upset potential: High. |
| Carlton v Geelong | ||
| 29 May @ M.C.G. | ||
|
Geelong by 14 points.
Upset potential: Medium. |
| Sydney v Richmond | ||
| 30 May @ S.C.G. | ||
|
Sydney by 30 points.
Upset potential: Low. |
| Brisbane v Fremantle | ||
| 30 May @ Gabba | ||
|
Brisbane by 5 points.
Upset potential: High. |
| Footscray v Collingwood | ||
| 30 May @ Docklands | ||
|
Footscray by 5 points.
Upset potential: High. |
| Melbourne v GWS | ||
| 31 May @ Traeger Park | ||
|
Melbourne by 7 points.
Upset potential: High. |
| West Coast v Essendon | ||
| 31 May @ Perth Stadium | ||
|
West Coast by 7 points.
Upset potential: High. |
Tips are based on five models:
- A team rating model (Elo) that tracks performance over time. 1,500 is the league average Elo rating. Home ground advantage (HGA) represents (a) the difference in experience between the two teams at the game’s venue for the current season and the two before, and (b) how far the teams have to travel to the venue, penalising long distance travel.
- An expected scoring shots model (xSS) that predicts each team’s scoring shots based on past offensive and defensive performance, and uses the difference between teams to estimate win percent.
- A tiered contribution model (TiCo) that assesses the difference in how well elite (top 25%) players, standard players, and subpar (bottom 25%) players perform between teams. A higher standard provides more support for the elite players, and a larger and worse subpar tier is a drag on team performance. The numbers represent the amount, in performance scores, that that tier contributes to the team’s overall performance. A greater share of performance from the higher tiers is desirable.
- A chain model that models chains of play where each ‘link’ is a contest between the teams: for example, home ruck wins ⇒ away midfield wins, kicks forward ⇒ home defense wins, kicks to midfield ⇒ … This uses the relative line strengths, which are built up from predicting individual player performance, minus those on the injury list.
- An ensemble that uses the four above models to give an overall estimate.
Season predictions
| Ladder finish probabilities | ||||||
| Based on 1,000 simulations, from round 11, 2026. | ||||||
| Minor prem. | Top 4 | Top 6 | Wildcard | Bottom 4 | Wooden spoon | |
|---|---|---|---|---|---|---|
| Fremantle | 37% | 85% | 94% | 5% | 0% | 0% |
| Sydney | 32% | 84% | 96% | 4% | 0% | 0% |
| Geelong | 18% | 69% | 87% | 12% | 0% | 0% |
| Hawthorn | 6% | 54% | 74% | 22% | 0% | 0% |
| Brisbane | 4% | 41% | 69% | 26% | 0% | 0% |
| Adelaide | 2% | 16% | 39% | 45% | 0% | 0% |
| Gold Coast | 1% | 16% | 36% | 44% | 0% | 0% |
| Melbourne | 1% | 13% | 35% | 46% | 1% | 0% |
| St Kilda | 0% | 6% | 16% | 42% | 6% | 0% |
| Footscray | 0% | 8% | 23% | 45% | 1% | 0% |
| Collingwood | 0% | 8% | 24% | 48% | 1% | 0% |
| GWS | 0% | 1% | 5% | 25% | 14% | 0% |
| N. Melbourne | 0% | 0% | 1% | 12% | 30% | 1% |
| Port Adelaide | 0% | 0% | 1% | 14% | 30% | 0% |
| Carlton | 0% | 0% | 1% | 7% | 46% | 3% |
| West Coast | 0% | 0% | 0% | 1% | 85% | 12% |
| Essendon | 0% | 0% | 0% | 1% | 88% | 22% |
| Richmond | 0% | 0% | 0% | 0% | 98% | 62% |
Season projections are based on projecting each team’s Elo rating.