AFL | Round 23

alphr.com.au

NINJA STADIUM • TUESDAY 24 FEB, 10:45 PM

AI Game Review

Our model correctly predicted North Melbourne to win at 90% probability. The predicted margin of 37.2 was reasonable against the actual 48-point result. The game's 222 points came in 47 points higher than the predicted 176. North Melbourne led 47–39 at the break and pulled away in the second half to win by 48. A clean sweep — all 3 model picks hit for this match.

Model vs actual outcomes • Post-match analysis

Quarter-by-Quarter Win Probability

AI Win Probability

90%North MelbourneFavourite

North Melbourne

90%

Richmond

10%

AI Match Overview

North Melbourne are clear favourites here at 90%, with our model expecting a comfortable victory over Richmond. Both sides are evenly matched across the key prediction factors, which explains the tight margin between them. Recent form favours Richmond with 2 wins from their last 5 compared to 0 for North Melbourne. The margin model predicts North Melbourne by 37.2 points with a combined total of 176.

Generated from model features • Pre-kick-off analysis

Edge Analysis

2 ACTIVE EDGES

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

H2H Recommendation

North Melbourne to Win @1.72

Winner ✓

Edge

+31.7%

Line / Spread

North Melbourne -5.5 @1.91

Winner ✓

Edge

+31.7%

Total Points

Over 164.5 @1.91

Winner ✓

Edge

+2.6%

Form & History

TeamLast 5Avg Pts
North Melbourne
LLLLL
66.6
Richmond
WWLLL
56.6

Avg Conceded

112.8

North Melbourne

69.8

Richmond

Avg Margin

-46.2

North Melbourne

-13.2

Richmond

Disposals

337.6

North Melbourne

353.2

Richmond

Inside 50s

50.0

North Melbourne

50.0

Richmond

Prediction BreakdownPure Alpha Model

ELO–Market Disagreement

Richmond hold the ELO advantage (1184 vs 1165), but the market favours North Melbourne (@1.72).

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

📊Team ELO Ratings

NOR
1165Overall1184
RIC
ELO difference: -19 in favour of Richmond

🏈Positional Matchups

Player ELO aggregated by position group — higher = stronger unit

1166Midfield1108
Best: 1199NOR +58Best: 1108
1093Forwards968
Best: 1361NOR +126Best: 1317
1192Defence1235
Best: 1367RIC +43Best: 1362
1211Ruck1219
Best: 1211EvenBest: 1219

📈Recent Form (Last 5)

NOR
Stat
RIC
0.0
Wins (Last 5)
2.0
66.6pts
Avg Score
56.6pts
112.8pts
Avg Conceded
69.8pts
-46.2pts
Avg Margin
-13.2pts
337.6
Disposals
353.2
50.0
Inside 50s
50.0
58.6
Tackles
44.8
36.4
Clearances
30.8

🔑Key Prediction Factors

What the model weighted most in this prediction

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

Model Confidence

90%

North Melbourne predicted to win by 37 points

Predicted total: 176 · Line: +37.2

Player Work Effort

Per-minute effort vs effectiveness (vs personal average)

Team Effort

-0.18

Team Effectiveness

+0.32

6
Elite
2
Hard Worker
6
Efficient
6
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.

3/3 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