AFL | Finals Week 1

alphr.com.au

MCG • TUESDAY 24 FEB, 10:45 PM

AI Game Review

Our model correctly predicted Geelong Cats to win at 53% probability. The margin model missed here — predicting 0.5 but the actual margin was 38 points. Geelong Cats led 59–44 at the break and pulled away in the second half to win by 38. The model went 2/3 on this match. The over 169.5 total call was correct.

Model vs actual outcomes • Post-match analysis

Quarter-by-Quarter Win Probability

AI Win Probability

53%Geelong CatsFavourite

Geelong Cats

53%

Brisbane Lions

47%

AI Match Overview

This shapes up as one of the tightest matchups of the round. Our model gives Geelong Cats a marginal 53% edge, making this essentially a coin-flip contest. Both sides are evenly matched across the key prediction factors, which explains the tight margin between them. Brisbane Lions carry a 40-point ELO rating advantage (1803 vs 1763). Recent form favours Geelong Cats with 5 wins from their last 5 compared to 3 for Brisbane Lions.

Generated from model features • Pre-kick-off analysis

Edge Analysis

Each market is predicted by an independent model — H2H, margin, and totals may occasionally disagree.

H2H Recommendation

Geelong Cats to Win @1.75

Winner ✓

Edge

-4.4%

Line / Spread

Brisbane Lions -4.5 @1.91

Lost ✗

Edge

-4.4%

Total Points

Over 169.5 @1.91

Winner ✓

Edge

+2.6%

Form & History

TeamLast 5Avg Pts
Geelong Cats
WWWWW
125.2
Brisbane Lions
WWWLL
87.2

Avg Conceded

62.2

Geelong Cats

82.0

Brisbane Lions

Avg Margin

63.0

Geelong Cats

5.2

Brisbane Lions

Disposals

369.0

Geelong Cats

381.2

Brisbane Lions

Inside 50s

50.0

Geelong Cats

50.0

Brisbane Lions

H2H History (Last 5)Brisbane Lions lead 4-1
Sep 2025GEE 75 - 122 BRI
Jun 2025GEE 51 - 92 BRI
Mar 2025GEE 61 - 70 BRI
Sep 2024GEE 85 - 95 BRI
Apr 2024GEE 63 - 37 BRI
Prediction BreakdownPure Alpha Model

ELO–Market Disagreement

Brisbane Lions hold the ELO advantage (1803 vs 1763), but the market favours Geelong Cats (@1.75).

The model sides with the market — other factors override the ELO gap.

📊Team ELO Ratings

GEE
1763Overall1803
BRI
ELO difference: -40 in favour of Brisbane Lions

🏈Positional Matchups

Player ELO aggregated by position group — higher = stronger unit

1195Midfield1306
Best: 1235BRI +110Best: 1376
1280Forwards1169
Best: 1411GEE +110Best: 1429
1157Defence1329
Best: 1316BRI +172Best: 1453
1000Ruck1229
Best: 1000BRI +229Best: 1229

📈Recent Form (Last 5)

GEE
Stat
BRI
5.0
Wins (Last 5)
3.0
125.2pts
Avg Score
87.2pts
62.2pts
Avg Conceded
82.0pts
63.0pts
Avg Margin
5.2pts
369.0
Disposals
381.2
50.0
Inside 50s
50.0
60.8
Tackles
54.8
35.8
Clearances
41.0

🔑Key Prediction Factors

What the model weighted most in this prediction

1
ELO Difference14.0%
Lions
2
Midfield ELO11.0%
Lions
3
Recent Win Rate10.0%
Cats
4
Forward Line ELO9.0%
Cats
5
Defensive ELO8.0%
Lions
6
Scoring Form8.0%
Cats
7
Venue Advantage7.0%

Model Confidence

53%

Geelong Cats predicted to win by 0 points

Predicted total: 173 · Line: -0.5

Player Work Effort

Per-minute effort vs effectiveness (vs personal average)

Team Effort

+0.29

Team Effectiveness

+0.09

8
Elite
6
Hard Worker
4
Efficient
4
Poor Game
Sort:

Effort = pressure acts + tackles + contested possessions per minute on field, z-scored vs career avg. Effectiveness = disposal efficiency + fantasy/min + score involvements − errors, z-scored vs career avg.

2/3 predictions correct
Coming Soon

Goal Scorer Predictions

AI-powered goal scorer predictions and player prop markets — built on our 6-model player stats engine.

First / Anytime / Last ScorerPlayer Props