# North Melbourne v Geelong Cats — AFL Round 23 2026 AI Prediction by Alphr

## Full Time: North Melbourne 110 – 125 Geelong Cats

_Geelong Cats toy with North Melbourne._

Half time: 57 – 64 · Alphr AI pre-game win probability: North Melbourne 24% / Geelong Cats 76% · Marvel Stadium · Sat, 15 Aug, 03:45 pm AEST

**Goal Kickers** — North Melbourne: Jack Darling (2' ×4 1st Tipped ⚡), Nick Larkey (15' ×5 Tipped ⚡), Zac Banch (23'), Paul Curtis (26' Tipped ⚡), Jy Simpkin (28'), Harry Sheezel (53'), Cooper Trembath (83' ×3 Tipped ⚡) · Geelong Cats: Jay Polkinghorne (12' ×3 Tipped ⚡), Mitchell Edwards (36' ×2), Shaun Mannagh (37' ×3), Shannon Neale (41' ×2 Tipped ⚡), Mark Blicavs (47' ×3), Lawson Humphries (52'), Brad Close (57'), Oliver Henry (80' Tipped ⚡), Patrick Dangerfield (84' ×2 Tipped ⚡), Oliver Dempsey (85')

### Match Winner — AI Prediction Market (resolved)

| Team | Pre-game AI win probability | Result |
|---|---|---|
| Geelong Cats | 76% | Won |
| North Melbourne | 24% | Lost |

Model call: **Correct** · Margin: 36.1 predicted → 15 actual · Markets hit: 2/4

_AI win probability priced pre-game · Markets hit = core betting markets._

### Full-Time Report

**North Melbourne Kangaroos vs Geelong Cats Prediction & Tips | AFL Round 23 2026**

_By Ben Dunlop · Published: 13 Aug 2026, 07:50 pm · Last updated: 15 Aug 2026, 06:31 pm_

North Melbourne 110–125 Geelong Cats in AFL Round 23 at Marvel Stadium. Here's how the result stacked up against the model's call, with the win-probability story and where the value landed.

65 inside 50s. That was the key stat in Geelong Cats' 125–110 win over North Melbourne at Marvel Stadium. Despite trailing 89–88 at three-quarter time, Geelong's relentless forward pressure in the final quarter made the difference. Their ability to penetrate North Melbourne's defence was crucial.

North Melbourne had their moments. They dominated the clearances, winning 50 to Geelong's 37. Their midfield strength, rated higher at 1324 against Geelong's 1263, was evident early as they jumped to a 44–6 lead by the end of the first quarter. However, while North controlled much of the stoppage play, they struggled to convert those clearances into effective scoring opportunities.

Geelong's forward line was more efficient. They had 17 marks inside 50 compared to North Melbourne's 14, making the most of their forward entries. This efficiency kept the pressure on North Melbourne's backline throughout the match.

North Melbourne played a cleaner game in terms of disposal efficiency, hitting targets at 74.7% compared to Geelong's 71.5%. This precision highlighted their controlled gameplay. Yet, it couldn't counter Geelong's ability to read the play and intercept, with the Cats pulling down 62 intercepts to North's 50.

North Melbourne's first-quarter blitz gave them an unexpected lead, but by half-time, Geelong had turned it around to lead 64–57. North's forward line, rated at 1225 compared to Geelong's 1142, couldn't maintain their early scoring efficiency.

Geelong's experience and recent form, with four wins in their last five games, showed as the match progressed. Their average score of 101.2 points in recent games was a testament to their consistent performance. North Melbourne, in contrast, had only one win in their last five outings, averaging 81.2 points per game.

Our model had predicted Geelong as the favourites with a 76% win probability. While it got the winner right, the expected margin of 36.1 points underestimated North's competitiveness. Geelong's 15-point victory was tighter than anticipated, and the total points of 235 exceeded the predicted 170.

In the end, Geelong's persistent forward pressure and composure under pressure secured their victory. North Melbourne's early dominance was promising, but Geelong's offensive strategy and defensive reads proved superior.

**Scoring by Quarter**

| Team | Q1 | Q2 | Q3 | Q4 | T |
|---|---|---|---|---|---|
| North Melbourne | 44 | 13 | 32 | 21 | 110 |
| Geelong Cats | 6 | 58 | 24 | 37 | 125 |

**Key Match Stats**

| North Melbourne | Stat | Geelong Cats |
|---|---|---|
| **360** | Disposals | 344 |
| **133** | Contested poss. | 124 |
| **50** | Clearances | 37 |
| 45 | Inside 50s | **65** |
| 55 | Marks | **86** |
| 14 | Marks inside 50 | **17** |
| 71 | Tackles | **74** |
| **45** | Hit-outs | 40 |
| 50 | Intercepts | **62** |
| **74.7%** | Disposal eff. | 71.5% |

**Model Report Card**

Our model correctly predicted Geelong Cats to win at 76% probability. The margin model missed here, predicting 36.1 but the actual margin was 15 points. The game's 235 points came in 65 points higher than the predicted 170. Geelong Cats led 57–64 at the break and pulled away in the second half to win by 15. The model went 2/4 on this match. The 1-39 margin band call landed.

_Official AFL match stats · Generated by Alphr's model_

### Edge Analysis — the model's pre-game markets

- **Head to Head:** Geelong Cats to win @ $1.30 (edge -1.3%) — model probability 75.7% — result: WON
- **Line / Spread:** Geelong Cats -22.5 @ $1.89 (edge +13.6%) — result: LOST
- **Margin Band:** Geelong Cats 1-39 @ $3.30 (edge +0.0%) — result: WON
- **Total (Over/Under):** Under 183.5 @ $1.89 (edge +2.1%) — result: LOST
- Predicted margin: Geelong Cats by 36 · Predicted total: 170

### Match Preview (pre-match read)

The model is firm on Geelong Cats here: 76% to see off North Melbourne. The heaviest factor is the ratings gap: Geelong Cats sit 404 ELO points clear, 1767 to 1363. Form leans Geelong Cats' way: 4 from their last 5, against 1 for North Melbourne.

On paper North Melbourne shade it, ahead on 4 of 7 factors including Forward Line, Weather and Defence. The model still sides with Geelong Cats, which says ELO Rating and Lineup Strength carry the most weight. The margin model has Geelong Cats by 36.1, with the two sides combining for about 170. Geelong Cats to win, and win clearly. The model isn't hedging.

_Pre-match read · Alphr model_

### Recent Form (Last 5)

| North Melbourne | Stat | Geelong Cats |
|---|---|---|
| 1.0 | Wins (Last 5) | 4.0 |
| 81.2pts | Avg Score | 101.2pts |
| 90.0pts | Avg Conceded | 76.0pts |
| -8.8pts | Avg Margin | 25.2pts |
| 378.2 | Disposals | 373.6 |
| 50.0 | Inside 50s | 50.0 |
| 49.0 | Tackles | 58.2 |
| 32.8 | Clearances | 42.4 |

### Form & History

_Last 5 games, oldest → newest._

| Team | Last 5 | Avg Pts |
|---|---|---|
| North Melbourne | R18 L · R19 L · R20 L · R21 L · R22 W | 81.2 |
| Geelong Cats | R18 L · R19 W · R20 W · R21 W · R22 W | 101.2 |

### Positional Matchup

_Season-to-date production per game with league-wide attack/defence tiers (18 teams)._

**Forwards** (Key Forwards · Med/Mid Forwards)

|  | North Melbourne | Geelong Cats |
|---|---|---|
| Attack rank | 11th | 3rd (strong) |
| Defence rank | 5th (strong) | 10th |
| Goals scored · conceded | 186 · 175 | 224 · 185 |
| Goal Assists | 4.1/g | 5.5/g |
| Disposals | 95/g | 96/g |
| Inside 50s | 14.3/g | 19.8/g |
| Marks Inside 50 | 10/g | 10.7/g |
| Disposal Efficiency | 72.4% | 65.7% |

**Midfield & Ruck** (Midfielders · Rucks)

|  | North Melbourne | Geelong Cats |
|---|---|---|
| Attack rank | 14th (weak) | 12th |
| Defence rank | 17th (weak) | 2nd (strong) |
| Goals scored · conceded | 50 · 80 | 61 · 50 |
| Goal Assists | 2.8/g | 3.7/g |
| Disposals | 151/g | 144/g |
| Inside 50s | 23.8/g | 26.2/g |
| Marks Inside 50 | 3.1/g | 2.1/g |
| Disposal Efficiency | 73.1% | 70.9% |

**Defenders** (Key & Medium Defenders)

|  | North Melbourne | Geelong Cats |
|---|---|---|
| Attack rank | 9th | 5th (strong) |
| Defence rank | 17th (weak) | 7th |
| Goals scored · conceded | 14 · 22 | 22 · 15 |
| Goal Assists | 1.4/g | 1.6/g |
| Disposals | 122/g | 134/g |
| Inside 50s | 9.6/g | 12.8/g |
| Marks Inside 50 | 0.7/g | 1/g |
| Disposal Efficiency | 81.4% | 78.9% |

**Who scores on Geelong Cats** — Key Forwards 3.89/g (lg 3.87) +1% · Forwards 4.35/g (lg 4.47) -3% · Midfielders 2.14/g (lg 2.49) -14%
**Who scores on North Melbourne** — Defenders 1.4/g (lg 1.06) +32% · Key Forwards 5.04/g (lg 3.87) +30% · Rucks 0.67/g (lg 0.52) +29%

_Goals conceded by position, last 3 seasons; positive = concedes above league average to that position._

### Goal Scorer History — Who Kicks The Goals

_Last 10 games, career record vs the opponent and at Marvel Stadium. ⚡ = our AI backs them to score; 🎯 = our AI's first-goal pick. 🏉 = scored in this game. Goal % = share of games with a goal, last 10 weighted double vs the 30 prior — historical frequency, not a market price._

**North Melbourne** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Nick Larkey | KF | 39 in 21g | 14/10g (1·4·1·1·1·3·0·1·2·0) | 14/10g | 145/70g | 86% | ⚡ Anytime Goal $1.11 AI 77% ✓ Scored | 🏉 15' 77' 87' 76' 91' |
| – | Paul Curtis | FWD | 36 in 18g | 20/10g (1·3·2·0·0·3·3·2·2·4) | 7/7g | 74/45g | 84% | ⚡ Anytime Goal $1.10 AI 80% ✓ Scored; 🎯 First Goal $11.00 AI 7% ✗ Not first | 🏉 26' |
| – | Jack Darling | KF | 31 in 20g | 17/10g (1·4·0·2·2·1·2·3·0·2) | 26/16g | 79/51g | 78% | ⚡ Anytime Goal $1.22 AI 80% ✓ Scored | 🏉 2' 13' 59' 74' |
| – | Cooper Trembath | KF | 28 in 21g | 12/10g (1·1·4·1·0·1·1·0·3·0) | 0/1g | 19/12g | 71% | ⚡ Anytime Goal $1.24 AI 71% ✓ Scored | 🏉 83' 89' 93' |
| – | Charlie Spargo | FWD | 11 in 17g | 6/10g (0·0·0·2·0·1·2·0·0·1) | 5/9g | 14/19g | 40% | — | — |
| – | Harry Sheezel | MID | 11 in 21g | 6/10g (0·1·0·0·1·0·1·1·2·0) | 3/5g | 15/41g | 44% | — | 🏉 53' |
| – | Jy Simpkin | MID | 10 in 21g | 3/10g (0·0·0·1·1·0·0·0·0·1) | 6/14g | 37/90g | 38% | — | 🏉 28' |
| – | Cameron Zurhaar | DEF | 8 in 21g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 9/10g | 101/74g | 42% | — | — |
| – | Luke Davies-Uniacke | MID | 7 in 21g | 4/10g (0·0·0·1·1·0·0·0·0·2) | 5/8g | 28/67g | 30% | — | — |
| – | Tristan Xerri | RUC | 7 in 17g | 5/10g (1·0·0·1·0·1·1·0·0·1) | 1/7g | 18/40g | 34% | — | — |
| – | Colby McKercher | FWD | 6 in 21g | 2/10g (0·0·0·0·1·0·0·0·1·0) | 2/3g | 7/29g | 32% | — | — |
| – | George Wardlaw | MID | 6 in 14g | 6/10g (1·0·1·0·1·0·2·0·0·1) | 0/2g | 8/24g | 38% | — | — |
| – | Finn O'Sullivan | MID | 5 in 17g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 0/2g | 2/19g | 12% | — | — |
| – | Zac Banch | FWD | 5 in 6g | 6/10g (0·0·0·1·0·1·1·0·1·2) | 0/1g | 4/7g | 50% | — | 🏉 23' |
| – | Dylan Stephens | MID | 4 in 21g | 2/10g (0·0·1·0·0·0·0·0·1·0) | 2/9g | 4/33g | 20% | — | — |
| – | Luke Parker | DEF | 3 in 21g | 1/10g (0·0·0·0·0·0·0·0·0·1) | 15/22g | 37/52g | 24% | — | — |
| – | Charlie Comben | DEF | 1 in 20g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/4g | 6/33g | 2% | — | — |
| – | Riley Hardeman | DEF | 1 in 5g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 0/1g | 1/11g | 6% | — | — |
| – | Aidan Corr | DEF | 0 in 14g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/13g | 1/52g | 0% | — | — |
| – | Caleb Daniel | DEF | 0 in 21g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 2/14g | 30/109g | 0% | — | — |
| – | Griffin Logue | DEF | 0 in 14g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/8g | 2/30g | 4% | — | — |
| – | Tom Blamires | MID | 0 in 6g | 0/6g (0·0·0·0·0·0) | 0/0g | 0/4g | 0% | — | — |
| – | Wil Dawson | RUC | 0 in 8g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/1g | 0/7g | 0% | — | — |

**Geelong Cats** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Shannon Neale | KF | 41 in 21g | 19/10g (0·1·2·2·3·0·1·5·2·3) | 11/4g | 7/4g | 82% | ⚡ Anytime Goal $1.04 AI 82% ✓ Scored; 🎯 First Goal $9.00 AI 7% ✗ Not first | 🏉 41' 69' |
| – | Oliver Henry | FWD | 39 in 20g | 21/10g (2·1·2·2·0·1·2·4·3·4) | 8/6g | 7/9g | 84% | ⚡ Anytime Goal $1.11 AI 83% ✓ Scored; 🎯 First Goal $11.00 AI 7% ✗ Not first | 🏉 80' |
| – | Shaun Mannagh | FWD | 29 in 21g | 10/10g (1·1·0·0·0·4·1·1·1·1) | 6/3g | 2/2g | 72% | — | 🏉 37' 55' 97' |
| – | Oliver Dempsey | MID | 28 in 21g | 18/10g (2·1·2·0·2·3·2·0·2·4) | 6/6g | 3/3g | 74% | — | 🏉 85' |
| – | Patrick Dangerfield | FWD | 18 in 15g | 11/10g (1·1·1·1·1·0·5·0·1·0) | 14/19g | 32/27g | 70% | ⚡ Anytime Goal $1.20 AI 64% ✓ Scored | 🏉 84' 71' |
| – | Oliver Wiltshire | FWD | 13 in 13g | 11/10g (0·0·3·2·1·1·0·3·1·0) | 0/0g | 0/0g | 60% | — | — |
| – | Brad Close | FWD | 9 in 14g | 7/10g (1·0·2·1·2·0·0·1·0·0) | 12/10g | 5/8g | 56% | — | 🏉 57' |
| – | Bailey Smith | MID | 8 in 20g | 3/10g (1·0·0·0·0·1·1·0·0·0) | 2/8g | 17/48g | 34% | — | — |
| – | Jay Polkinghorne | KF | 8 in 4g | 8/4g (2·2·3·1) | 0/0g | 0/0g | 100% | ⚡ Anytime Goal $1.10 AI 80% ✓ Scored | 🏉 12' 49' 87' |
| – | Jack Henry | DEF | 6 in 17g | 4/10g (2·1·0·1·0·0·0·0·0·0) | 1/11g | 0/8g | 16% | — | — |
| – | Gryan Miers | FWD | 4 in 13g | 4/10g (0·0·0·0·0·0·3·0·1·0) | 10/10g | 4/9g | 38% | — | — |
| – | James Worpel | MID | 4 in 10g | 4/10g (0·1·0·1·1·0·1·0·0·0) | 3/10g | 8/23g | 28% | — | — |
| – | Mark O'Connor | DEF | 4 in 18g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 1/8g | 0/8g | 8% | — | — |
| – | Tom Atkins | MID | 4 in 21g | 3/10g (0·0·1·0·0·0·1·1·0·0) | 0/10g | 2/10g | 22% | — | — |
| – | Jhye Clark | DEF | 3 in 7g | 3/10g (0·0·0·1·1·0·0·0·0·1) | 0/1g | 0/1g | 21% | — | — |
| – | Lawson Humphries | DEF | 3 in 20g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 2/3g | 1/3g | 16% | — | 🏉 52' |
| – | Oisin Mullin | MID | 3 in 21g | 2/10g (0·0·0·1·1·0·0·0·0·0) | 0/3g | 0/4g | 14% | — | — |
| – | Mark Blicavs | MID | 2 in 17g | 1/10g (0·0·0·0·0·0·0·0·1·0) | 6/21g | 10/31g | 24% | — | 🏉 47' 68' 65' |
| – | Connor O'Sullivan | DEF | 1 in 21g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/3g | 0/2g | 2% | — | — |
| – | Tanner Bruhn | DEF | 1 in 19g | 1/10g (0·0·0·0·0·0·0·0·0·1) | 2/5g | 3/9g | 14% | — | — |
| – | Tom Stewart | DEF | 1 in 19g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/13g | 1/15g | 4% | — | — |
| – | Zach Guthrie | DEF | 1 in 21g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 4/8g | 1/8g | 2% | — | — |
| – | Mitchell Edwards | RUC | 0 in 16g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/1g | 0/0g | 0% | — | 🏉 36' 62' |

### Player Props — Disposal Counts

_Bookmaker disposal lines vs our model's read. ⚡ = the validated under signal (model ≥10 points past the price) — everything else is market intel, not a tip. The ⚡ under signal's verified record: 57.7% of 1,278 flags in 2025._

**North Melbourne**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Harry Sheezel | 26.5 | $1.98 | 30% | 16 ✓ |
| Luke Parker | 25.5 | $1.86 | 49% | 20 ✓ |
| Luke Davies-Uniacke | 24.5 | $1.92 | 53% | 20 ✓ |
| Colby McKercher | 24.5 | — | 71% | 19 ✓ |
| Caleb Daniel | 24.5 | $1.91 | 49% | 24 ✓ |
| Tristan Xerri | 20.5 | — | 86% | 17 ✓ |
| Thomas Stewart | 20.5 | $1.85 | — | — |
| Jy Simpkin | 19.5 | — | 37% | 26 ✗ |
| Dylan Stephens | 19.5 | — | 52% | 18 ✓ |
| Finn O'Sullivan | 18.5 | — | 50% | 25 ✗ |
| Cameron Zurhaar | 18.5 | — | 77% | 20 ✗ |
| Ollie Dempsey | 18.5 | — | — | — |
| Tom Blamires | 17.5 | — | 48% | 19 ✗ |
| Sam De Koning | 16.5 | — | 78% | — |

**Geelong Cats**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Bailey Smith | 29.5 | $1.87 | 56% | 34 ✗ |
| Tanner Bruhn ⚡ Under | 22.5 | $1.87 | 78% | 28 ✗ |
| James Worpel | 20.5 | — | 66% | 15 ✓ |
| Gryan Miers | 19.5 | — | 71% | 16 ✓ |
| Lawson Humphries | 19.5 | $1.85 | 60% | 20 ✗ |
| Jhye Clark | 18.5 | — | 90% | 11 ✓ |
| Tom Atkins | 18.5 | — | 61% | 17 ✓ |
| Zach Guthrie | 17.5 | — | 80% | 15 ✓ |
| Shaun Mannagh | 17.5 | — | 64% | 20 ✗ |
| Oisin Mullin | 17.5 | — | 88% | 17 ✓ |
| Connor O'Sullivan | 16.5 | — | 66% | 11 ✓ |
| Patrick Dangerfield | 15.5 | — | 47% | 9 ✓ |
| Mark O'Connor | 15.5 | — | 65% | 10 ✓ |
| Mark Blicavs | 14.5 | — | 66% | 18 ✗ |

### Prediction Breakdown — Pure Alpha Model

**Team ELO Ratings** — North Melbourne 1363 · Geelong Cats 1767 · ELO difference: 404 in favour of Geelong Cats

**Positional Matchups** — lineup ELO by unit

| Unit | North Melbourne | Geelong Cats | Edge |
|---|---|---|---|
| Midfield | 1324 (best 1324) | 1263 (best 1340) | North Melbourne +60 |
| Forwards | 1225 (best 1401) | 1142 (best 1361) | North Melbourne +83 |
| Defence | 1183 (best 1382) | 1156 (best 1293) | North Melbourne +28 |
| Ruck | 1268 (best 1268) | 1192 (best 1243) | North Melbourne +76 |

**Key Prediction Factors** — what the model weighted most

| # | Factor | Weight | Favours |
|---|---|---|---|
| 1 | ELO Rating | 60.2% | Geelong Cats |
| 2 | Forward Line | 10.7% | North Melbourne |
| 3 | Lineup Strength | 6.8% | Geelong Cats |
| 4 | Weather | 6.0% | North Melbourne |
| 5 | Defence | 4.3% | North Melbourne |
| 6 | Ruck | 3.2% | North Melbourne |
| 7 | Stat Profile | 2.6% | Geelong Cats |

**Model Confidence: 76%** — Geelong Cats predicted to win by 36 points · Predicted total: 170 pts

**Record:** 2/4 predictions correct

**Prediction by Alphr** (https://alphr.com.au) — free AI predictions for every AFL, NRL & Super League match, published before kick-off and never edited. Verified track record: https://alphr.com.au/accuracy

---
Canonical URL: https://alphr.com.au/afl/match/2026-r23-north-melbourne-v-geelong-cats
RSS feed: https://alphr.com.au/feed.xml
Prediction JSON API: today https://alphr.com.au/api/predictions/today · this week https://alphr.com.au/api/predictions/weekly
Markdown view for AI agents. Machine-readable index: https://alphr.com.au/llms.txt · full reference: https://alphr.com.au/llms-full.txt
All predictions are published before kick-off and verified after full time. Free, no login. 18+ gamble responsibly (AU).
Last updated: 2026-08-15 08:31 UTC (latest tip update)