# Geelong Cats v Sydney Swans — AFL Round 11 2026 AI Prediction by Alphr

## Full Time: Geelong Cats 107 – 80 Sydney Swans

_Geelong Cats toy with Sydney Swans._

Half time: 58 – 38 · Alphr AI pre-game win probability: Geelong Cats 39% / Sydney Swans 61% · GMHBA Stadium · Sat, 23 May, 04:15 pm AEST

**Goal Kickers** — Geelong Cats: Jeremy Cameron (9' ×3 1st Tipped 🎯), Oliver Henry (17' ×2 Tipped ⚡), Lawson Humphries (40'), Brad Close (43' ×2), Tom Atkins (47'), Shaun Mannagh (56' Tipped ⚡), Jack Martin (66'), Connor OSullivan (70'), Jack Henry (73'), Bailey Smith (82'), Patrick Dangerfield (67') · Sydney Swans: Joel Amartey (12' ×4 Tipped ⚡), Isaac Heeney (62' Tipped ⚡), Tom Hanily (77'), Charlie Curnow (86' ×2 Tipped ⚡), Logan McDonald (92' ×2 Tipped ⚡)

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

| Team | Pre-game AI win probability | Result |
|---|---|---|
| Sydney Swans | 61% | Lost |
| Geelong Cats | 39% | Won |

Model call: **Missed** · Margin: 0.5 predicted → 27 actual · Markets hit: 1/4

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

### Full-Time Report

**Geelong Cats vs Sydney Swans Prediction & Tips | AFL Round 11 2026**

_By Ben Dunlop · Published: 22 May 2026, 10:16 am · Last updated: 25 May 2026, 11:16 am_

Geelong Cats 107–80 Sydney Swans in AFL Round 11 at GMHBA Stadium. Here's how the result stacked up against the model's call, with the win-probability story and where the value landed.

Sydney Swans had the scoreboard pressure running their way to start. Quarter time at GMHBA Stadium had them up 26-22, the kind of margin that puts the chasing side, in this case Geelong, on notice early. It didn't last.

The second quarter flipped everything. Geelong outscored Sydney across that term and turned a four-point deficit into a 58-38 lead by half time, a 20-point swing built inside a single quarter. Whatever plan Sydney brought in, it stopped working the moment the Cats found their rhythm.

Three-quarter time had Geelong up 85-71. Still a healthy break, but with a quarter to play and Sydney's pressure game intact, not one that was locked away just yet. Geelong kept building through the last term and ran out winners 107-80, a 27-point margin at the final siren.

The numbers explain how it happened. Geelong finished with 410 disposals to 365, won clearances 38-34 and hit-outs 39-33, and went inside 50 an enormous 69 times to Sydney's 45. Add 105 marks to 76, 15 marks inside 50 to 13, and a disposal efficiency of 75.6% against 71.2%, and the picture is clear: Geelong had the ball more often and used it better once they had it. Intercepts were close, 72 to 66, but everything else in the possession count ran the Cats' way.

Sydney's one clear statistical win was tackles, 73 to 39. That's a lot of chasing and not much time in control, which tracks with a side that spent long stretches defending its own hurried turnovers rather than dictating terms going forward.

What makes the result notable is what it defied coming in. Sydney rated stronger across every key position: midfield 1188 to 1085, forwards 1001 to 981, defence 1140 to 1093, ruck 1153 to 1104. They'd also won five straight, against Geelong's 4-1 record in the same stretch, and were averaging 110 points a game to Geelong's 114 with a tighter average margin of victory. None of that form or ratings edge showed up on the scoreboard. Geelong's win at the clearances and hit-outs suggests the bigger, better-rated engine room simply got outworked at the source, and the rest of the afternoon flowed from there.

Alphr's model had Sydney as 61% favourites before the bounce, tipping a Geelong win by just half a point and a combined score near 193. The total wasn't far off the mark, 187 points in the end, within six of the projection. The margin prediction missed badly though, out by nearly 27 points, and the side installed as favourite lost by four goals. That leaves the model at one from four on this match, with only the draw margin band landing as forecast.

For Geelong, it's a result that will read well against a form line that already had them winning four of their last five. For Sydney, it's the kind of loss that undercuts a five-game winning streak coming in, built on a first quarter lead that had vanished by half time and never came back.

**Scoring by Quarter**

| Team | Q1 | Q2 | Q3 | Q4 | T |
|---|---|---|---|---|---|
| Geelong Cats | 22 | 36 | 27 | 22 | 107 |
| Sydney Swans | 26 | 12 | 33 | 9 | 80 |

**Key Match Stats**

| Geelong Cats | Stat | Sydney Swans |
|---|---|---|
| **410** | Disposals | 365 |
| **144** | Contested poss. | 129 |
| **38** | Clearances | 34 |
| **69** | Inside 50s | 45 |
| **105** | Marks | 76 |
| **15** | Marks inside 50 | 13 |
| 39 | Tackles | **73** |
| **39** | Hit-outs | 33 |
| **72** | Intercepts | 66 |
| **75.6%** | Disposal eff. | 71.2% |

**Model Report Card**

Geelong Cats defied the model's 61% prediction for Sydney Swans, a notable upset. The margin model missed here, predicting 0.5 but the actual margin was 27 points. Total score prediction of 193 was close to the actual 187, within 6 points. Geelong Cats led 58–38 at the break and pulled away in the second half to win by 27. The model went 1/4 on this match. The Draw margin band call landed.

_Official AFL match stats · Generated by Alphr's model_

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

- **Head to Head:** Sydney Swans to win @ $2.47 (edge +20.2%) — model probability 60.7% — result: LOST
- **Line / Spread:** Sydney Swans +11.5 @ $1.90 (edge +11.0%) — result: LOST
- **Margin Band:** Geelong Cats Draw @ $3.30 (edge +0.0%) — result: WON
- **Total (Over/Under):** Over 189.5 @ $1.88 (edge +1.8%) — result: LOST
- Predicted margin: Geelong Cats by 1 · Predicted total: 193

### Match Preview (pre-match read)

Sydney Swans are the call at 61%, but Geelong Cats stay live at 39%. Form leans Sydney Swans' way: 5 from their last 5, against 4 for Geelong Cats.

Sydney Swans own the matchup too, leading 4 of 7 factors including Midfield ELO, Recent Win Rate and Forward Line ELO. Lean Sydney Swans, but it shapes as a genuine contest.

_Pre-match read · Alphr model_

### Recent Form (Last 5)

| Geelong Cats | Stat | Sydney Swans |
|---|---|---|
| 4.0 | Wins (Last 5) | 5.0 |
| 114.0pts | Avg Score | 110.0pts |
| 76.2pts | Avg Conceded | 82.4pts |
| 37.8pts | Avg Margin | 27.6pts |
| 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 |
|---|---|---|
| Geelong Cats | R6 W · R7 L · R8 W · R9 W · R10 W | 114.0 |
| Sydney Swans | R6 W · R7 W · R8 W · R9 W · R10 W | 110.0 |

### H2H History (Last 5) — Geelong Cats lead 3-1

| Season | Round | Home | Score | Away |
|---|---|---|---|---|
| 2025 | R23 | Sydney Swans | 68 – 111 | Geelong Cats |
| 2024 | R13 | Sydney Swans | 112 – 82 | Geelong Cats |
| 2023 | R16 | Sydney Swans | 54 – 54 | Geelong Cats |
| 2023 | R6 | Geelong Cats | 130 – 37 | Sydney Swans |
| 2022 | SF | Geelong Cats | 133 – 52 | Sydney Swans |

### Positional Matchup

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

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

|  | Geelong Cats | Sydney Swans |
|---|---|---|
| Attack rank | 2nd (strong) | 6th (strong) |
| Defence rank | 11th | 1st (strong) |
| Goals scored · conceded | 111 · 91 | 101 · 66 |
| Goal Assists | 5/g | 4.1/g |
| Disposals | 94/g | 93/g |
| Inside 50s | 18.6/g | 18.2/g |
| Marks Inside 50 | 11.1/g | 10.7/g |
| Disposal Efficiency | 65.4% | 68.4% |

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

|  | Geelong Cats | Sydney Swans |
|---|---|---|
| Attack rank | 12th | 1st (strong) |
| Defence rank | 1st (strong) | 8th |
| Goals scored · conceded | 28 · 21 | 58 · 31 |
| Goal Assists | 4.4/g | 5.4/g |
| Disposals | 153/g | 161/g |
| Inside 50s | 26.7/g | 30.6/g |
| Marks Inside 50 | 2/g | 3/g |
| Disposal Efficiency | 71.5% | 70.4% |

**Defenders** (Key & Medium Defenders)

|  | Geelong Cats | Sydney Swans |
|---|---|---|
| Attack rank | 3rd (strong) | 10th |
| Defence rank | 10th | 3rd (strong) |
| Goals scored · conceded | 12 · 8 | 8 · 4 |
| Goal Assists | 1.3/g | 2.3/g |
| Disposals | 134/g | 138/g |
| Inside 50s | 12.5/g | 14.9/g |
| Marks Inside 50 | 0.8/g | 0.5/g |
| Disposal Efficiency | 77.7% | 79.1% |

**Who scores on Sydney Swans** — Rucks 0.64/g (lg 0.5) +28% · Midfielders 2.39/g (lg 2.5) -4% · Forwards 4/g (lg 4.45) -10%
**Who scores on Geelong Cats** — Key Forwards 3.95/g (lg 3.81) +4% · Forwards 4.23/g (lg 4.45) -5% · Midfielders 2.16/g (lg 2.5) -14%

_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 GMHBA 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._

**Geelong Cats** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Jeremy Cameron | KF | 27 in 9g | 27/10g (0·3·0·1·3·10·3·3·1·3) | 45/22g | 138/48g | 88% | ⚡ Anytime Goal $1.01 AI 89% ✓ Scored; 🎯 First Goal $8.00 AI 8% ✓ Scored first | 🏉 9' 41' 65' |
| – | Shannon Neale | KF | 22 in 10g | 22/10g (1·5·0·4·2·1·2·3·2·2) | 5/2g | 39/22g | 84% | ⚡ Anytime Goal $1.08 AI 81% ✗ No goal | — |
| – | Shaun Mannagh | FWD | 18 in 10g | 18/10g (1·3·1·0·0·0·1·4·3·5) | 3/1g | 23/18g | 74% | ⚡ Anytime Goal $1.20 AI 73% ✓ Scored | 🏉 56' |
| – | Oliver Henry | FWD | 16 in 9g | 17/10g (1·2·1·3·2·1·0·1·4·2) | 4/3g | 38/27g | 78% | ⚡ Anytime Goal $1.20 AI 73% ✓ Scored | 🏉 17' 24' |
| – | Jack Martin | FWD | 11 in 9g | 11/10g (0·0·1·3·1·1·1·2·2·0) | 5/8g | 17/12g | 68% | — | 🏉 66' |
| – | Oliver Dempsey | MID | 10 in 10g | 10/10g (4·0·2·1·0·1·0·1·1·0) | 1/2g | 24/27g | 72% | — | — |
| – | Patrick Dangerfield | FWD | 8 in 6g | 13/10g (2·0·3·0·1·2·1·1·2·1) | 19/18g | 78/73g | 70% | — | 🏉 67' |
| – | Brad Close | FWD | 6 in 8g | 7/10g (0·1·0·0·0·2·1·0·2·1) | 11/7g | 46/46g | 52% | — | 🏉 43' 73' |
| – | Bailey Smith | MID | 5 in 10g | 5/10g (0·1·0·0·1·1·0·0·0·2) | 1/5g | 3/15g | 34% | — | 🏉 82' |
| – | Mark O'Connor | DEF | 3 in 8g | 3/10g (0·0·0·0·0·3·0·0·0·0) | 0/7g | 4/54g | 6% | — | — |
| – | Max Holmes | MID | 3 in 10g | 3/10g (0·0·1·0·0·0·0·2·0·0) | 1/5g | 18/42g | 34% | — | — |
| – | Lawson Humphries | DEF | 2 in 10g | 2/10g (0·0·0·0·0·1·0·1·0·0) | 0/1g | 4/17g | 16% | — | 🏉 40' |
| – | Jack Henry | DEF | 1 in 6g | 1/10g (0·0·0·0·0·1·0·0·0·0) | 0/11g | 14/62g | 4% | — | 🏉 73' |
| – | Jake Kolodjashnij | DEF | 1 in 4g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 1/15g | 4/71g | 6% | — | — |
| – | Mark Blicavs | MID | 1 in 7g | 4/10g (1·1·1·0·0·0·1·0·0·0) | 5/20g | 22/99g | 32% | — | — |
| – | Oisin Mullin | MID | 1 in 10g | 1/10g (0·0·0·0·0·0·0·0·0·1) | 0/2g | 0/21g | 8% | — | — |
| – | Sam De Koning | DEF | 1 in 9g | 1/10g (0·0·0·0·0·1·0·0·0·0) | 1/5g | 4/37g | 14% | — | — |
| – | Tom Stewart | DEF | 1 in 10g | 1/10g (0·0·1·0·0·0·0·0·0·0) | 0/14g | 3/71g | 8% | — | — |
| – | Zach Guthrie | DEF | 1 in 10g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 0/10g | 6/49g | 6% | — | — |
| – | Connor O'Sullivan | DEF | 0 in 10g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/1g | 0/14g | 0% | — | — |
| – | Gryan Miers | FWD | 0 in 6g | 1/10g (0·0·1·0·0·0·0·0·0·0) | 6/9g | 42/56g | 38% | — | — |
| – | Mitchell Edwards | RUC | 0 in 8g | 0/8g (0·0·0·0·0·0·0·0) | 0/0g | 0/4g | 0% | — | — |
| – | Tom Atkins | MID | 0 in 10g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 2/9g | 10/56g | 10% | — | 🏉 47' |

**Sydney Swans** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Charlie Curnow | KF | 21 in 9g | 23/10g (2·3·0·2·4·0·3·7·1·1) | 21/7g | 1/1g | 80% | ⚡ Anytime Goal $1.05 AI 87% ✓ Scored; 🎯 First Goal $10.00 AI 7% ✗ Not first | 🏉 86' 76' |
| – | Joel Amartey | KF | 21 in 10g | 21/10g (3·5·1·2·0·2·3·4·1·0) | 3/2g | 2/1g | 76% | ⚡ Anytime Goal $1.15 AI 82% ✓ Scored; 🎯 First Goal $12.00 AI 6% ✗ Not first | 🏉 12' 26' 30' 79' |
| – | Logan McDonald | KF | 17 in 10g | 17/10g (1·2·3·0·1·2·0·3·3·2) | 2/4g | 0/1g | 82% | ⚡ Anytime Goal $1.27 AI 77% ✓ Scored | 🏉 92' 95' |
| – | Isaac Heeney | MID | 14 in 8g | 16/10g (1·1·2·2·4·2·0·0·3·1) | 17/14g | 7/6g | 78% | ⚡ Anytime Goal $1.26 AI 74% ✓ Scored | 🏉 62' |
| – | Tom Papley | FWD | 14 in 10g | 14/10g (1·0·1·2·3·1·1·1·2·2) | 24/14g | 9/6g | 82% | — | — |
| – | Malcolm Rosas | FWD | 13 in 9g | 13/10g (0·1·1·1·2·1·0·7·0·0) | 0/3g | 0/1g | 60% | — | — |
| – | Chad Warner | MID | 12 in 10g | 12/10g (1·0·1·2·2·1·3·0·1·1) | 5/6g | 0/1g | 66% | — | — |
| – | Justin McInerney | MID | 12 in 10g | 12/10g (3·2·1·1·1·2·0·1·0·1) | 4/6g | 0/2g | 54% | — | — |
| – | Brodie Grundy | RUC | 8 in 10g | 8/10g (1·1·1·1·0·0·2·1·0·1) | 6/14g | 0/1g | 42% | — | — |
| – | Jake Lloyd | FWD | 7 in 10g | 7/10g (0·0·0·3·0·1·1·1·1·0) | 3/19g | 1/7g | 32% | — | — |
| – | James Jordon | MID | 4 in 10g | 4/10g (0·0·1·1·0·2·0·0·0·0) | 1/7g | 0/3g | 26% | — | — |
| – | Nick Blakey | DEF | 4 in 10g | 4/10g (0·1·0·1·0·1·0·0·0·1) | 3/9g | 1/3g | 32% | — | — |
| – | Angus Sheldrick | MID | 3 in 9g | 3/10g (0·1·0·0·0·1·0·0·1·0) | 0/3g | 0/0g | 29% | — | — |
| – | Jai Serong | MID | 2 in 9g | 2/10g (0·0·0·0·1·0·0·0·0·1) | 0/0g | 0/0g | 17% | — | — |
| – | James Rowbottom | FWD | 1 in 10g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 2/9g | 0/2g | 26% | — | — |
| – | Riley Bice | DEF | 1 in 10g | 1/10g (0·0·0·0·1·0·0·0·0·0) | 0/0g | 0/0g | 8% | — | — |
| – | Sam Wicks | DEF | 1 in 10g | 1/10g (0·0·0·1·0·0·0·0·0·0) | 0/4g | 2/1g | 10% | — | — |
| – | Caiden Cleary | FWD | 0 in 1g | 1/10g (0·1·0·0·0·0·0·0·0·0) | 0/1g | 0/0g | 14% | — | — |
| – | Callum Mills | DEF | 0 in 10g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 4/13g | 1/6g | 12% | — | — |
| – | Lewis Melican | DEF | 0 in 7g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/8g | 0/2g | 2% | — | — |
| – | Tom Hanily | FWD | no games | 6/8g (0·1·1·2·2·0·0·0) | 0/0g | 0/0g | 50% | — | 🏉 77' |
| – | Tom McCartin | DEF | 0 in 8g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 2/9g | 0/2g | 8% | — | — |
| – | William Edwards | DEF | 0 in 4g | 0/4g (0·0·0·0) | 0/0g | 0/0g | 0% | — | — |

### 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._

**Geelong Cats**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Bailey Smith | 30.5 | $1.88 | 57% | 32 ✗ |
| Max Holmes | 25.5 | $1.95 | 47% | 35 ✗ |
| Tom Stewart ⚡ Under | 22.5 | $1.86 | 65% | 17 ✓ |
| Gryan Miers | 19.5 | $1.91 | 53% | 24 ✗ |
| Lawson Humphries ⚡ Under | 19.5 | $1.90 | 67% | 33 ✗ |
| Tom Atkins | 18.5 | $1.87 | 55% | 13 ✓ |
| Oliver Dempsey | 18.5 | $1.85 | 56% | 23 ✗ |
| Shaun Mannagh ⚡ Under | 17.5 | $1.82 | 68% | 15 ✓ |
| Zach Guthrie | 16.5 | $1.85 | 58% | 21 ✗ |
| Oisin Mullin ⚡ Under | 15.5 | $1.82 | 69% | 19 ✗ |
| Jeremy Cameron | 14.5 | $1.81 | 55% | 21 ✗ |

**Sydney Swans**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Justin McInerney | 25.5 | $1.93 | 59% | 18 ✓ |
| Nick Blakey | 24.5 | $1.91 | 61% | 22 ✓ |
| Isaac Heeney | 23.5 | $1.88 | 52% | 23 ✓ |
| Brodie Grundy ⚡ Under | 23.5 | $1.87 | 75% | 15 ✓ |
| Callum Mills | 22.5 | $1.91 | 60% | 24 ✗ |
| Chad Warner | 21.5 | $1.91 | 55% | 11 ✓ |
| Tom McCartin ⚡ Under | 19.5 | $1.90 | 64% | 18 ✓ |
| Angus Sheldrick | 19.5 | $1.87 | 62% | 14 ✓ |
| Jake Lloyd | 17.5 | $1.80 | 56% | 24 ✗ |
| Sam Wicks ⚡ Under | 17.5 | $1.87 | 64% | 16 ✓ |
| Riley Bice | 17.5 | $1.87 | 42% | 34 ✗ |
| Jai Serong | 16.5 | $1.87 | 47% | 26 ✗ |
| Tom Papley | 14.5 | $1.85 | 51% | 5 ✓ |

### Prediction Breakdown — Pure Alpha Model

**ELO–Market Disagreement:** Sydney Swans hold the ELO advantage (1809 vs 1800), but the market favours Geelong Cats (@1.68). The model sides with ELO, Sydney Swans predicted to win despite longer odds.

**Team ELO Ratings** — Geelong Cats 1800 · Sydney Swans 1809 · ELO difference: 10 in favour of Sydney Swans

**Positional Matchups** — lineup ELO by unit

| Unit | Geelong Cats | Sydney Swans | Edge |
|---|---|---|---|
| Midfield | 1085 (best 1478) | 1188 (best 1471) | Sydney Swans +103 |
| Forwards | 981 (best 1472) | 1001 (best 1600) | Sydney Swans +20 |
| Defence | 1093 (best 1600) | 1140 (best 1534) | Sydney Swans +47 |
| Ruck | 1104 (best 1302) | 1153 (best 1513) | Sydney Swans +49 |

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

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

**Model Confidence: 61%** — Sydney Swans predicted to win by 1 points · Predicted total: 193 pts

**Record:** 1/4 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-r11-geelong-cats-v-sydney-swans
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: 2026-05-25 01:16 UTC (latest tip update)