# Adelaide Crows v Geelong Cats — AFL Round 13 2026 AI Prediction by Alphr

## Full Time: Adelaide Crows 75 – 74 Geelong Cats

_A point the difference as Adelaide Crows deny Geelong Cats._

Half time: 39 – 33 · Alphr AI pre-game win probability: Adelaide Crows 55% / Geelong Cats 45% · Adelaide Oval · Thu, 04 June, 07:30 pm AEST

**Goal Kickers** — Adelaide Crows: Zac Taylor (3'), Alex Neal-Bullen (9'), Sam Berry (24'), Taylor Walker (47' ×2 Tipped ⚡), Jordan Dawson (50' ×2), Ben Keays (60'), Callum Ah Chee (76'), Final quarter (34m 54s)Ben Keays (64') · Geelong Cats: Jack Martin (2' ×2 1st), Patrick Dangerfield (5' Tipped ⚡), Jack Henry (48'), Shannon Neale (80' Tipped ⚡), Oliver Dempsey (82'), Jack Bowes (86' ×2), Oliver Henry (74' Tipped ⚡), Shaun Mannagh (83' Tipped ⚡)

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

| Team | Pre-game AI win probability | Result |
|---|---|---|
| Adelaide Crows | 55% | Won |
| Geelong Cats | 45% | Lost |

Model call: **Correct** · Margin: 3.3 predicted → 1 actual · Markets hit: 4/4

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

### Full-Time Report

**Adelaide Crows vs Geelong Cats Prediction and Tips - AFL Round 13, 2026**

_By Ben Dunlop · Published: 3 June 2026, 08:40 pm · Last updated: 4 June 2026, 10:54 pm_

Adelaide Crows 75–74 Geelong Cats in AFL Round 13 at Adelaide Oval. Here's how the result stacked up against the model's call, with the win-probability story and where the value landed.

Adelaide Crows led by six points at half time. By the final siren that buffer was down to one. Geelong Cats spent the second half hunting it down and came agonisingly close, but the Crows got home 75-74 at Adelaide Oval.

The scoreboard tells the story of a game that kept trying to slip away from the home side. Adelaide led 20-18 at quarter time, stretched it to 39-33 by half time, then watched Geelong claw back with a 19-15 third term to make it 54-52 at the last change. The Cats did it again in the final quarter, outscoring Adelaide 22-21, but they'd left themselves too much to do. One point was the difference at the end, same as it so often is in these things.

Geelong actually won the underlying share of the ball. They had 389 disposals to 365, took 71 marks to Adelaide's 59, and won the contested possession count 171 to 153. On raw numbers, that's the sort of shape that should be winning games easily. It wasn't enough.

What flipped it was pressure and second efforts. Adelaide laid 88 tackles to Geelong's 62, a gap that big usually shows up on the scoreboard, and it did here. The Crows also won hit-outs 61 to 43, which is a strange one given Geelong went in rated the stronger ruck outfit, 1104 to 1089. Whatever went on around those contests, Adelaide's follow-up work turned it into first use plenty of times Geelong probably didn't expect.

Adelaide's defence rating, 1151 against Geel

**Scoring by Quarter**

| Team | Q1 | Q2 | Q3 | Q4 | T |
|---|---|---|---|---|---|
| Adelaide Crows | 20 | 19 | 15 | 21 | 75 |
| Geelong Cats | 18 | 15 | 19 | 22 | 74 |

**Key Match Stats**

| Adelaide Crows | Stat | Geelong Cats |
|---|---|---|
| 365 | Disposals | **389** |
| 153 | Contested poss. | **171** |
| 44 | Clearances | **46** |
| 50 | Inside 50s | **52** |
| 59 | Marks | **71** |
| **7** | Marks inside 50 | 5 |
| **88** | Tackles | 62 |
| **61** | Hit-outs | 43 |
| 73 | Intercepts | **80** |
| **68.8%** | Disposal eff. | 66.1% |

**Model Report Card**

Our model correctly predicted Adelaide Crows to win at 55% probability. The margin model was sharp, predicting Adelaide Crows by 3.3 vs the actual margin of 1 points. A clean sweep, all 4 model picks hit for this match.

_Official AFL match stats · Generated by Alphr's model_

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

- **Head to Head:** Adelaide Crows to win @ $2.34 (edge +11.8%) — model probability 54.5% — result: WON
- **Line / Spread:** Adelaide Crows +8.5 @ $1.90 (edge +11.8%) — result: WON
- **Margin Band:** Adelaide Crows 1-39 @ $3.30 (edge +0.0%) — result: WON
- **Total (Over/Under):** Under 166.5 @ $1.88 (edge +1.8%) — result: WON
- Predicted margin: Adelaide Crows by 3 · Predicted total: 143

### Match Preview (pre-match read)

Adelaide Crows are the call at 55%, but Geelong Cats stay live at 45%. The ratings say otherwise: Geelong Cats sit 199 ELO points clear, 1800 to 1601, so the model is backing Adelaide Crows against the ratings gap. Form leans Adelaide Crows' way: 4 from their last 5, against 3 for Geelong Cats.

The factors split evenly, which is why the margin stays tight. The margin model has Adelaide Crows by 3.3, with the two sides combining for about 143. Lean Adelaide Crows, but it shapes as a genuine contest.

_Pre-match read · Alphr model_

### Recent Form (Last 5)

| Adelaide Crows | Stat | Geelong Cats |
|---|---|---|
| 4.0 | Wins (Last 5) | 3.0 |
| 89.6pts | Avg Score | 100.8pts |
| 70.0pts | Avg Conceded | 77.4pts |
| 19.6pts | Avg Margin | 23.4pts |
| 350.0 | Disposals | 350.0 |
| 50.0 | Inside 50s | 50.0 |
| 60.0 | Tackles | 60.0 |
| 35.0 | Clearances | 35.0 |

### Form & History

_Last 5 games, oldest → newest._

| Team | Last 5 | Avg Pts |
|---|---|---|
| Adelaide Crows | R8 W · R9 W · R10 W · R11 L · R13 W | 89.6 |
| Geelong Cats | R9 W · R10 W · R11 W · R12 L · R13 L | 100.8 |

### H2H History (Last 5) — Geelong Cats lead 5-0

| Season | Round | Home | Score | Away |
|---|---|---|---|---|
| 2026 | R3 | Geelong Cats | 68 – 60 | Adelaide Crows |
| 2025 | R5 | Adelaide Crows | 100 – 119 | Geelong Cats |
| 2024 | R21 | Geelong Cats | 90 – 85 | Adelaide Crows |
| 2024 | R2 | Adelaide Crows | 77 – 96 | Geelong Cats |
| 2023 | R8 | Geelong Cats | 98 – 72 | Adelaide Crows |

### Positional Matchup

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

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

|  | Adelaide Crows | Geelong Cats |
|---|---|---|
| Attack rank | 11th | 5th (strong) |
| Defence rank | 4th (strong) | 12th |
| Goals scored · conceded | 92 · 91 | 129 · 109 |
| Goal Assists | 5.7/g | 4.9/g |
| Disposals | 109/g | 97/g |
| Inside 50s | 20.7/g | 19.8/g |
| Marks Inside 50 | 9/g | 11.3/g |
| Disposal Efficiency | 66.3% | 64.5% |

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

|  | Adelaide Crows | Geelong Cats |
|---|---|---|
| Attack rank | 3rd (strong) | 13th (weak) |
| Defence rank | 4th (strong) | 1st (strong) |
| Goals scored · conceded | 46 · 27 | 32 · 25 |
| Goal Assists | 3.7/g | 4.3/g |
| Disposals | 131/g | 149/g |
| Inside 50s | 22.5/g | 26/g |
| Marks Inside 50 | 2.3/g | 1.9/g |
| Disposal Efficiency | 70.8% | 72.8% |

**Defenders** (Key & Medium Defenders)

|  | Adelaide Crows | Geelong Cats |
|---|---|---|
| Attack rank | 15th (weak) | 3rd (strong) |
| Defence rank | 15th (weak) | 8th |
| Goals scored · conceded | 5 · 12 | 17 · 9 |
| Goal Assists | 0.6/g | 1.4/g |
| Disposals | 123/g | 135/g |
| Inside 50s | 9/g | 12.6/g |
| Marks Inside 50 | 0.2/g | 0.9/g |
| Disposal Efficiency | 81.2% | 78.7% |

**Who scores on Geelong Cats** — Key Forwards 3.97/g (lg 3.83) +4% · Forwards 4.25/g (lg 4.47) -5% · Midfielders 2.14/g (lg 2.48) -14%
**Who scores on Adelaide Crows** — Defenders 1.2/g (lg 1.13) +6% · Forwards 4.37/g (lg 4.47) -2% · Midfielders 2.22/g (lg 2.48) -10%

_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 Adelaide Oval. ⚡ = 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._

**Adelaide Crows** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Josh Rachele | FWD | 18 in 11g | 17/10g (2·1·1·4·1·0·2·2·3·1) | 5/4g | 70/46g | 86% | ⚡ Anytime Goal $1.36 AI 73% ✗ No goal | — |
| – | Ben Keays | FWD | 13 in 11g | 12/10g (0·0·0·3·2·1·3·1·2·0) | 5/9g | 75/82g | 70% | — | 🏉 60' |
| – | Taylor Walker | KF | 11 in 7g | 14/10g (1·2·0·0·3·1·1·5·1·0) | 29/17g | 299/135g | 80% | ⚡ Anytime Goal $1.13 AI 76% ✓ Scored | 🏉 47' 66' |
| – | Jordan Dawson | MID | 9 in 8g | 10/10g (1·0·0·1·2·1·2·1·1·1) | 4/9g | 35/60g | 58% | — | 🏉 50' 73' |
| – | Alex Neal-Bullen | FWD | 7 in 10g | 7/10g (1·0·1·1·2·0·0·2·0·0) | 11/14g | 19/33g | 50% | — | 🏉 9' |
| – | Darcy Fogarty | KF | 7 in 5g | 12/10g (1·2·1·0·1·2·2·0·2·1) | 10/7g | 120/75g | 80% | ⚡ Anytime Goal $1.12 AI 67% ✗ No goal | — |
| – | Brayden Cook | MID | 6 in 11g | 5/10g (0·0·1·0·1·1·1·0·1·0) | 0/1g | 10/22g | 42% | — | — |
| – | Jake Soligo | FWD | 6 in 9g | 7/10g (1·1·1·0·0·1·0·0·2·1) | 3/6g | 25/54g | 46% | — | — |
| – | Toby Murray | RUC | 5 in 6g | 5/6g (0·0·2·1·2·0) | 0/0g | 4/2g | 50% | — | — |
| – | Zac Taylor | FWD | 5 in 9g | 5/10g (0·3·1·0·0·0·0·0·0·1) | 4/3g | 3/22g | 27% | — | 🏉 3' |
| – | James Peatling | MID | 4 in 11g | 4/10g (0·0·1·0·1·0·0·0·2·0) | 0/6g | 11/21g | 34% | — | — |
| – | Lachlan McAndrew | RUC | 4 in 11g | 4/10g (0·0·0·0·0·0·0·1·2·1) | 0/1g | 2/6g | 26% | — | — |
| – | Callum Ah Chee | FWD | 2 in 3g | 5/10g (1·1·0·0·1·0·0·0·0·2) | 9/15g | 7/7g | 58% | — | 🏉 76' |
| – | Luke Nankervis | DEF | 2 in 5g | 2/10g (0·0·0·0·0·0·0·0·2·0) | 0/3g | 2/21g | 7% | — | — |
| – | Daniel Curtin | MID | 1 in 4g | 2/10g (0·0·1·0·0·0·0·1·0·0) | 1/2g | 8/22g | 30% | — | — |
| – | Jordon Butts | DEF | 1 in 8g | 1/10g (0·0·0·1·0·0·0·0·0·0) | 0/6g | 1/49g | 4% | — | — |
| – | Sam Berry | MID | 1 in 11g | 1/10g (0·0·1·0·0·0·0·0·0·0) | 0/5g | 8/49g | 18% | — | 🏉 24' |
| – | Hugo Hall-Kahan | DEF | no games | 0/0g | 0/0g | 0/0g | — | — | — |
| – | James Borlase | DEF | 0 in 6g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/0g | 1/12g | 3% | — | — |
| – | Josh Worrell | DEF | 0 in 11g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/4g | 0/38g | 0% | — | — |
| – | Max Michalanney | DEF | 0 in 11g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/5g | 1/45g | 4% | — | — |
| – | Rory Laird | DEF | 0 in 9g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/16g | 18/143g | 2% | — | — |
| – | Wayne Milera | DEF | 0 in 11g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/9g | 18/75g | 6% | — | — |

**Geelong Cats** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Jeremy Cameron | KF | 34 in 11g | 31/10g (0·1·3·10·3·3·1·3·3·4) | 39/18g | 56/21g | 90% | ⚡ Anytime Goal $1.02 AI 93% ✗ No goal; 🎯 First Goal $7.50 AI 11% ✗ Not first | — |
| – | Shannon Neale | KF | 22 in 12g | 16/10g (0·4·2·1·2·3·2·2·0·0) | 2/4g | 6/5g | 76% | ⚡ Anytime Goal $1.21 AI 77% ✓ Scored; 🎯 First Goal $12.00 AI 6% ✗ Not first | 🏉 80' |
| – | Oliver Henry | FWD | 20 in 11g | 18/10g (1·3·2·1·0·1·4·2·2·2) | 8/7g | 10/9g | 78% | ⚡ Anytime Goal $1.20 AI 78% ✓ Scored; 🎯 First Goal $11.50 AI 6% ✗ Not first | 🏉 74' |
| – | Shaun Mannagh | FWD | 20 in 12g | 16/10g (1·0·0·0·1·4·3·5·1·1) | 4/4g | 6/5g | 74% | ⚡ Anytime Goal $1.37 AI 73% ✓ Scored | 🏉 83' |
| – | Jack Martin | FWD | 12 in 10g | 12/10g (0·1·3·1·1·1·2·2·0·1) | 6/7g | 3/5g | 70% | — | 🏉 2' 40' |
| – | Oliver Dempsey | MID | 12 in 12g | 8/10g (2·1·0·1·0·1·1·0·0·2) | 4/5g | 5/6g | 70% | — | 🏉 82' |
| – | Patrick Dangerfield | FWD | 10 in 8g | 13/10g (3·0·1·2·1·1·2·1·1·1) | 14/14g | 39/44g | 76% | ⚡ Anytime Goal $1.45 AI 67% ✓ Scored | 🏉 5' |
| – | Bailey Smith | MID | 6 in 12g | 5/10g (0·0·1·1·0·0·0·2·1·0) | 1/7g | 8/9g | 36% | — | — |
| – | Jack Bowes | MID | 5 in 6g | 8/10g (1·1·0·1·2·1·0·0·1·1) | 1/8g | 8/13g | 58% | — | 🏉 86' 88' |
| – | Jack Henry | DEF | 4 in 8g | 4/10g (0·0·0·1·0·0·0·0·1·2) | 0/6g | 0/14g | 12% | — | 🏉 48' |
| – | Mark O'Connor | DEF | 3 in 10g | 3/10g (0·0·0·3·0·0·0·0·0·0) | 0/9g | 1/15g | 6% | — | — |
| – | Max Holmes | MID | 3 in 12g | 3/10g (1·0·0·0·0·2·0·0·0·0) | 3/5g | 4/9g | 32% | — | — |
| – | Oliver Wiltshire | FWD | 2 in 4g | 3/6g (0·1·0·1·1·0) | 0/1g | 0/0g | 50% | — | — |
| – | Connor O'Sullivan | DEF | 1 in 12g | 1/10g (0·0·0·0·0·0·0·0·1·0) | 0/2g | 0/3g | 4% | — | — |
| – | Jake Kolodjashnij | DEF | 1 in 6g | 1/10g (0·0·0·0·0·1·0·0·0·0) | 0/14g | 0/18g | 6% | — | — |
| – | Mark Blicavs | MID | 1 in 9g | 2/10g (1·0·0·0·1·0·0·0·0·0) | 5/19g | 6/24g | 28% | — | — |
| – | Oisin Mullin | MID | 1 in 12g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 0/3g | 0/5g | 8% | — | — |
| – | Sam De Koning | DEF | 1 in 11g | 1/10g (0·0·0·1·0·0·0·0·0·0) | 0/5g | 0/7g | 12% | — | — |
| – | Tom Atkins | MID | 1 in 12g | 1/10g (0·0·0·0·0·0·0·0·1·0) | 2/9g | 2/15g | 14% | — | — |
| – | Tom Stewart | DEF | 1 in 12g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 1/13g | 0/15g | 8% | — | — |
| – | Zach Guthrie | DEF | 1 in 12g | 1/10g (0·0·0·0·0·1·0·0·0·0) | 1/8g | 2/11g | 6% | — | — |
| – | Gryan Miers | FWD | 0 in 8g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 13/10g | 12/14g | 34% | — | — |
| – | Tanner Bruhn | DEF | 0 in 11g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 2/3g | 1/5g | 14% | — | — |

### 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._

**Adelaide Crows**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Wayne Milera ⚡ Under | 25.5 | $1.91 | 69% | 24 ✓ |
| Rory Laird | 24.5 | $1.91 | 45% | 23 ✓ |
| Josh Worrell | 23.5 | $1.91 | 61% | 22 ✓ |
| Jordan Dawson | 23.5 | $1.92 | 51% | 22 ✓ |
| Sam Berry | 21.5 | $1.92 | 60% | 20 ✓ |
| James Peatling ⚡ Under | 20.5 | $1.91 | 66% | 20 ✓ |
| Josh Rachele ⚡ Under | 19.5 | $1.87 | 67% | 12 ✓ |
| Alex Neal-Bullen | 17.5 | $1.92 | 57% | 15 ✓ |
| Jake Soligo ⚡ Under | 17.5 | $1.87 | 69% | 22 ✗ |
| Brayden Cook | 16.5 | $1.87 | 54% | 18 ✗ |
| Ben Keays | 15.5 | $1.94 | 52% | 16 ✗ |

**Geelong Cats**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Bailey Smith ⚡ Under | 33.5 | $1.94 | 67% | 34 ✗ |
| Max Holmes ⚡ Under | 28.5 | $1.92 | 65% | 30 ✗ |
| Tom Stewart | 20.5 | $1.90 | 56% | 15 ✓ |
| Gryan Miers | 20.5 | $1.93 | 60% | 25 ✗ |
| Tanner Bruhn ⚡ Under | 20.5 | $1.87 | 67% | 23 ✗ |
| Jack Bowes | 18.5 | $1.78 | 66% | 19 ✗ |
| Tom Atkins ⚡ Under | 18.5 | $1.89 | 65% | 16 ✓ |
| Oliver Dempsey | 17.5 | $1.90 | 44% | 14 ✓ |
| Zach Guthrie | 17.5 | $1.87 | 61% | 9 ✓ |
| Shaun Mannagh | 15.5 | $1.85 | 51% | 14 ✓ |
| Jeremy Cameron | 14.5 | $1.90 | 54% | 7 ✓ |

### Prediction Breakdown — Pure Alpha Model

**Team ELO Ratings** — Adelaide Crows 1601 · Geelong Cats 1800 · ELO difference: 199 in favour of Geelong Cats

**Positional Matchups** — lineup ELO by unit

| Unit | Adelaide Crows | Geelong Cats | Edge |
|---|---|---|---|
| Midfield | 1068 (best 1313) | 1085 (best 1478) | Geelong Cats +17 |
| Forwards | 974 (best 1396) | 981 (best 1472) | Geelong Cats +7 |
| Defence | 1151 (best 1538) | 1093 (best 1600) | Adelaide Crows +58 |
| Ruck | 1089 (best 1172) | 1104 (best 1302) | Geelong Cats +15 |

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

| # | Factor | Weight | Favours |
|---|---|---|---|
| 1 | ELO Difference | 14.0% | Geelong Cats |
| 2 | Midfield ELO | 11.0% | Geelong Cats |
| 3 | Recent Win Rate | 10.0% | Adelaide Crows |
| 4 | Forward Line ELO | 9.0% | Geelong Cats |
| 5 | Defensive ELO | 8.0% | Adelaide Crows |
| 6 | Scoring Form | 8.0% | Geelong Cats |
| 7 | Venue Advantage | 7.0% | Adelaide Crows |

**Model Confidence: 55%** — Adelaide Crows predicted to win by 3 points · Predicted total: 143 pts

**Record:** 4/4 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-r13-adelaide-crows-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: 2026-06-04 12:54 UTC (latest tip update)