# Brisbane Lions v Geelong Cats — AFL Round 10 2026 AI Prediction by Alphr

## Full Time: Brisbane Lions 76 – 117 Geelong Cats

_Geelong Cats claw past Brisbane Lions._

Half time: 45 – 57 · Alphr AI pre-game win probability: Brisbane Lions 49% / Geelong Cats 51% · Gabba · Thu, 14 May, 07:30 pm AEST

**Goal Kickers** — Brisbane Lions: Cody Curtin (7'), Cam Rayner (28'), Charlie Cameron (38' ×3 Tipped ⚡), Logan Morris (46' ×2 Tipped ⚡), Levi Ashcroft (55'), Sam Draper (85'), Conor McKenna (82') · Geelong Cats: Brad Close (3' 1st), Shaun Mannagh (13' ×5 Tipped ⚡), Patrick Dangerfield (21'), Bailey Smith (24' ×2), Jeremy Cameron (33' ×3 Tipped ⚡), Oliver Henry (53' ×2 Tipped ⚡), Shannon Neale (59' ×2 Tipped ⚡), Oisin Mullin (71')

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

| Team | Pre-game AI win probability | Result |
|---|---|---|
| Geelong Cats | 51% | Won |
| Brisbane Lions | 49% | Lost |

Model call: **Correct** · Margin: 1.8 predicted → 41 actual · Markets hit: 3/4

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

### Full-Time Report

**Brisbane Lions vs Geelong Cats Prediction and Tips - AFL Round 10, 2026**

_By Ben Dunlop · Published: 14 May 2026, 10:11 am · Last updated: 14 May 2026, 10:44 pm_

Brisbane Lions 76–117 Geelong Cats in AFL Round 10 at Gabba. Here's how the result stacked up against the model's call, with the win-probability story and where the value landed.

Twelve points. That was the gap at half time at the Gabba, Brisbane Lions trailing Geelong Cats 45-57, and after being down by 22 at the first change, that looked like a side clawing its way back into a contest. It didn't last.

Geelong put the game away in the third term, extending the margin to 29 by three-quarter time, 95-66, and Brisbane never found an answer in the last quarter either. Final score: Geelong Cats 117, Brisbane Lions 76. A 41-point win, nowhere near as close as it looked at the main break.

Brisbane actually won the territory battle in the midfield sense, 45 clearances to 35, and had more looks at goal, 56 inside 50s to Geelong's 66... except Geelong's forward entries did more damage. Marks inside 50 went Brisbane's way, 11 to 9, but that was about the only scoreboard-adjacent stat Brisbane could claim.

Everywhere else, Geelong was cleaner and harder. Disposal efficiency, 74.5% to 69.5%, tells you who was actually using the ball when they had it. Marks, 80 to 69. Tackles, 64 to 45, a serious pressure gap that shows up in a team getting repeatedly turned over under duress. And intercepts, 77 to 63, which explains how Geelong kept generating the ball back so quickly after Brisbane's clearance wins. Winning the clearance count means little if the other side is picking you off on the rebound.

The pre-match numbers had this pegged as tight. Alphr's model gave Geelong a 51% chance, with the ratings gap thin, 1759 to 1728, and the ruck was flagged as Geelong's one clear edge, 1104 to 1076. Brisbane held the advantage in midfield, forwards and defence on paper. None of it mattered once the ball started finding Geelong hands more often than Brisbane's.

Form lines going in had these two level pegging, four wins apiece in the last five, and near-identical output across disposals, inside 50s, tackles and clearances. Geelong's scoring average sat a shade higher, 115 to 112.8, and their average winning margin, 38.8, turned out to be the closer read on what was coming than anything the head-to-head ratings suggested.

The model called the winner right but undercooked the gap badly, tipping Geelong by 1.8 when it finished at 41. The total was the bright spot: 192 predicted against 193 actual, near enough spot on. Three from four for the model on this one, and the lesson sits squarely in the margin call. Sometimes a tight rating gap just doesn't survive contact with a third quarter like that.

**Scoring by Quarter**

| Team | Q1 | Q2 | Q3 | Q4 | T |
|---|---|---|---|---|---|
| Brisbane Lions | 13 | 32 | 21 | 10 | 76 |
| Geelong Cats | 35 | 22 | 38 | 22 | 117 |

**Key Match Stats**

| Brisbane Lions | Stat | Geelong Cats |
|---|---|---|
| 381 | Disposals | **404** |
| **143** | Contested poss. | 138 |
| **45** | Clearances | 35 |
| 56 | Inside 50s | **66** |
| 69 | Marks | **80** |
| **11** | Marks inside 50 | 9 |
| 45 | Tackles | **64** |
| **43** | Hit-outs | 36 |
| 63 | Intercepts | **77** |
| 69.5% | Disposal eff. | **74.5%** |

**Model Report Card**

Our model correctly predicted Geelong Cats to win at 51% probability. The margin model missed here, predicting 1.8 but the actual margin was 41 points. Total score prediction of 192 was close to the actual 193, within 1 points. Geelong Cats led 45–57 at the break and pulled away in the second half to win by 41. The model went 3/4 on this match. Geelong Cats covered the 15.5-point line. The over 183.5 total call was correct.

_Official AFL match stats · Generated by Alphr's model_

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

- **Head to Head:** Geelong Cats to win @ $2.84 (edge +16.0%) — model probability 51.2% — result: WON
- **Line / Spread:** Geelong Cats +15.5 @ $1.90 (edge +17.3%) — result: WON
- **Margin Band:** Geelong Cats 1-39 @ $3.30 (edge +0.0%) — result: LOST
- **Total (Over/Under):** Over 183.5 @ $1.89 (edge +2.1%) — result: WON
- Predicted margin: Geelong Cats by 2 · Predicted total: 192

### Match Preview (pre-match read)

Line ball between Brisbane Lions and Geelong Cats. The model can't split them, landing on Geelong Cats at 51%. The ratings say otherwise: Brisbane Lions sit 31 ELO points clear, 1759 to 1728, so the model is backing Geelong Cats against the ratings gap.

On paper Brisbane Lions shade it, ahead on 5 of 7 factors including ELO Difference, Midfield ELO and Forward Line ELO. The model still sides with Geelong Cats, which says Recent Win Rate carry the most weight. The margin model has Geelong Cats by 1.8, with the two sides combining for about 192. Coin-flip on the win, so the value is where this one gets settled.

_Pre-match read · Alphr model_

### Recent Form (Last 5)

| Brisbane Lions | Stat | Geelong Cats |
|---|---|---|
| 4.0 | Wins (Last 5) | 4.0 |
| 112.8pts | Avg Score | 115.0pts |
| 82.6pts | Avg Conceded | 76.2pts |
| 30.2pts | Avg Margin | 38.8pts |
| 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 |
|---|---|---|
| Brisbane Lions | R5 W · R6 L · R7 W · R8 W · R9 W | 112.8 |
| Geelong Cats | R5 W · R6 W · R7 L · R8 W · R9 W | 115.0 |

### H2H History (Last 5) — Brisbane Lions lead 4-1

| Season | Round | Home | Score | Away |
|---|---|---|---|---|
| 2026 | R17 | Geelong Cats | 101 – 123 | Brisbane Lions |
| 2025 | PF | Geelong Cats | 75 – 122 | Brisbane Lions |
| 2025 | WF | Geelong Cats | 112 – 74 | Brisbane Lions |
| 2025 | R15 | Geelong Cats | 51 – 92 | Brisbane Lions |
| 2025 | R3 | Brisbane Lions | 70 – 61 | Geelong Cats |

### Positional Matchup

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

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

|  | Brisbane Lions | Geelong Cats |
|---|---|---|
| Attack rank | 2nd (strong) | 4th (strong) |
| Defence rank | 5th (strong) | 9th |
| Goals scored · conceded | 105 · 75 | 97 · 81 |
| Goal Assists | 6.3/g | 4.3/g |
| Disposals | 90/g | 91/g |
| Inside 50s | 18.9/g | 18.1/g |
| Marks Inside 50 | 10.4/g | 11.6/g |
| Disposal Efficiency | 67.1% | 64.7% |

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

|  | Brisbane Lions | Geelong Cats |
|---|---|---|
| Attack rank | 9th | 10th |
| Defence rank | 10th | 2nd (strong) |
| Goals scored · conceded | 27 · 29 | 25 · 19 |
| Goal Assists | 3.7/g | 4.8/g |
| Disposals | 165/g | 153/g |
| Inside 50s | 25.7/g | 26.8/g |
| Marks Inside 50 | 3.8/g | 2.1/g |
| Disposal Efficiency | 70.9% | 71.1% |

**Defenders** (Key & Medium Defenders)

|  | Brisbane Lions | Geelong Cats |
|---|---|---|
| Attack rank | 9th | 2nd (strong) |
| Defence rank | 9th | 11th |
| Goals scored · conceded | 8 · 7 | 12 · 8 |
| Goal Assists | 1.7/g | 1.4/g |
| Disposals | 123/g | 133/g |
| Inside 50s | 12.8/g | 12/g |
| Marks Inside 50 | 0.4/g | 0.8/g |
| Disposal Efficiency | 80% | 77.8% |

**Who scores on Geelong Cats** — Key Forwards 3.95/g (lg 3.81) +4% · Forwards 4.22/g (lg 4.47) -6% · Midfielders 2.17/g (lg 2.48) -12%
**Who scores on Brisbane Lions** — Rucks 0.49/g (lg 0.5) -2% · Forwards 4.24/g (lg 4.47) -5% · Midfielders 2.3/g (lg 2.48) -7%

_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 Gabba. ⚡ = 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._

**Brisbane Lions** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Logan Morris | KF | 21 in 8g | 23/10g (1·1·3·2·3·0·3·2·4·4) | 10/5g | 45/23g | 84% | ⚡ Anytime Goal $1.01 AI 85% ✓ Scored; 🎯 First Goal $8.50 AI 7% ✗ Not first | 🏉 46' 96' |
| – | Charlie Cameron | FWD | 20 in 9g | 24/10g (4·4·2·2·0·1·3·4·2·2) | 33/20g | 179/95g | 76% | ⚡ Anytime Goal $1.07 AI 86% ✓ Scored; 🎯 First Goal $10.00 AI 7% ✗ Not first | 🏉 38' 51' 91' |
| – | Kai Lohmann | FWD | 18 in 9g | 20/10g (2·2·1·2·4·1·1·1·4·2) | 7/7g | 36/29g | 80% | ⚡ Anytime Goal $1.14 AI 78% ✗ No goal | — |
| – | Zac Bailey | FWD | 14 in 8g | 19/10g (2·3·1·2·2·2·0·3·4·0) | 8/12g | 85/86g | 80% | ⚡ Anytime Goal $1.18 AI 78% ✓ Scored | — |
| – | Cam Rayner | FWD | 10 in 9g | 11/10g (1·1·1·2·0·1·2·1·2·0) | 15/13g | 79/86g | 74% | — | 🏉 28' |
| – | Hugh McCluggage | MID | 5 in 6g | 10/10g (0·0·1·4·0·0·1·2·1·1) | 10/16g | 71/106g | 50% | — | — |
| – | Sam Draper | RUC | 5 in 8g | 6/10g (0·1·0·0·0·2·1·1·0·1) | 1/5g | 4/9g | 56% | — | 🏉 85' |
| – | Bruce Reville | MID | 4 in 9g | 4/10g (0·0·2·0·1·0·0·0·1·0) | 1/3g | 4/16g | 27% | — | — |
| – | Conor McKenna | FWD | 4 in 3g | 6/10g (0·0·0·0·1·1·0·2·2·0) | 3/7g | 9/27g | 24% | — | 🏉 82' |
| – | Darcy Fort | RUC | 3 in 8g | 3/10g (0·0·1·0·0·0·0·1·0·1) | 0/5g | 9/25g | 26% | — | — |
| – | Levi Ashcroft | MID | 3 in 9g | 4/10g (1·0·0·1·0·0·0·0·0·2) | 3/4g | 7/16g | 35% | — | 🏉 55' |
| – | Will Ashcroft | MID | 3 in 9g | 4/10g (1·0·0·0·1·0·1·1·0·0) | 3/6g | 14/31g | 36% | — | — |
| – | Jaspa Fletcher | DEF | 2 in 9g | 2/10g (0·0·0·1·0·0·1·0·0·0) | 1/7g | 12/36g | 24% | — | — |
| – | Keidean Coleman | DEF | 2 in 9g | 2/10g (0·0·0·1·0·1·0·0·0·0) | 1/4g | 6/36g | 12% | — | — |
| – | Lachie Neale | MID | 2 in 9g | 3/10g (1·0·0·0·0·0·0·0·1·1) | 7/22g | 39/84g | 30% | — | — |
| – | Darcy Wilmot | DEF | 1 in 9g | 1/10g (0·0·0·0·0·0·0·0·1·0) | 1/8g | 8/42g | 14% | — | — |
| – | James Tunstill | MID | 1 in 3g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 0/1g | 1/7g | 12% | — | — |
| – | Cody Curtin | KF | 0 in 2g | 0/2g (0·0) | 0/0g | 0/1g | 0% | — | 🏉 7' |
| – | Darcy Gardiner | DEF | 0 in 2g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/11g | 10/92g | 10% | — | — |
| – | Harris Andrews | DEF | 0 in 6g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/19g | 4/120g | 0% | — | — |
| – | Josh Dunkley | MID | 0 in 9g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 7/15g | 7/45g | 14% | — | — |
| – | Ryan Lester | DEF | 0 in 9g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 3/19g | 23/116g | 2% | — | — |
| – | Sam Marshall | MID | no games | 1/10g (0·1·0·0·0·0·0·0·0·0) | 0/2g | 0/5g | 10% | — | — |

**Geelong Cats** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Jeremy Cameron | KF | 24 in 8g | 27/10g (3·0·3·0·1·3·10·3·3·1) | 41/21g | 24/13g | 88% | ⚡ Anytime Goal $1.03 AI 92% ✓ Scored; 🎯 First Goal $8.50 AI 9% ✗ Not first | 🏉 33' 89' 69' |
| – | Shannon Neale | KF | 20 in 9g | 21/10g (1·1·5·0·4·2·1·2·3·2) | 3/5g | 0/1g | 84% | ⚡ Anytime Goal $1.14 AI 83% ✓ Scored | 🏉 59' 76' |
| – | Oliver Henry | FWD | 14 in 8g | 16/10g (1·1·2·1·3·2·1·0·1·4) | 9/6g | 5/4g | 78% | ⚡ Anytime Goal $1.30 AI 76% ✓ Scored | 🏉 53' 79' |
| – | Shaun Mannagh | FWD | 13 in 9g | 14/10g (1·1·3·1·0·0·0·1·4·3) | 2/4g | 0/0g | 72% | ⚡ Anytime Goal $1.33 AI 70% ✓ Scored | 🏉 13' 73' 75' 76' 80' |
| – | Jack Martin | FWD | 11 in 8g | 12/10g (1·0·0·1·3·1·1·1·2·2) | 13/15g | 15/12g | 72% | — | — |
| – | Oliver Dempsey | MID | 10 in 9g | 14/10g (4·4·0·2·1·0·1·0·1·1) | 9/6g | 1/2g | 76% | — | — |
| – | Patrick Dangerfield | FWD | 7 in 5g | 13/10g (1·2·0·3·0·1·2·1·1·2) | 21/22g | 22/17g | 68% | — | 🏉 21' |
| – | Brad Close | FWD | 5 in 7g | 7/10g (1·0·1·0·0·0·2·1·0·2) | 5/10g | 2/7g | 52% | — | 🏉 3' |
| – | Bailey Smith | MID | 3 in 9g | 3/10g (0·0·1·0·0·1·1·0·0·0) | 5/10g | 3/5g | 30% | — | 🏉 24' 64' |
| – | Mark O'Connor | DEF | 3 in 7g | 3/10g (0·0·0·0·0·0·3·0·0·0) | 1/13g | 1/11g | 8% | — | — |
| – | Max Holmes | MID | 3 in 9g | 4/10g (1·0·0·1·0·0·0·0·2·0) | 4/9g | 1/3g | 36% | — | — |
| – | Lawson Humphries | DEF | 2 in 9g | 2/10g (0·0·0·0·0·0·1·0·1·0) | 0/5g | 0/1g | 18% | — | — |
| – | Jack Henry | DEF | 1 in 5g | 1/10g (0·0·0·0·0·0·1·0·0·0) | 4/15g | 1/11g | 4% | — | — |
| – | Mark Blicavs | MID | 1 in 6g | 4/10g (0·1·1·1·0·0·0·1·0·0) | 10/23g | 8/15g | 32% | — | — |
| – | Sam De Koning | DEF | 1 in 8g | 1/10g (0·0·0·0·0·0·1·0·0·0) | 1/7g | 0/3g | 14% | — | — |
| – | Tom Stewart | DEF | 1 in 9g | 1/10g (0·0·0·1·0·0·0·0·0·0) | 1/11g | 0/10g | 8% | — | — |
| – | Zach Guthrie | DEF | 1 in 9g | 1/10g (0·0·0·0·0·0·0·0·1·0) | 1/11g | 2/6g | 6% | — | — |
| – | Connor O'Sullivan | DEF | 0 in 9g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/4g | 0/1g | 0% | — | — |
| – | Gryan Miers | FWD | 0 in 5g | 3/10g (2·0·0·1·0·0·0·0·0·0) | 10/13g | 13/10g | 40% | — | — |
| – | Mitchell Edwards | RUC | 0 in 7g | 0/7g (0·0·0·0·0·0·0) | 0/0g | 0/0g | 0% | — | — |
| – | Oisin Mullin | MID | 0 in 9g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 2/6g | 0/2g | 6% | — | 🏉 71' |
| – | Tanner Bruhn | DEF | 0 in 9g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/5g | 0/3g | 18% | — | — |
| – | Tom Atkins | MID | 0 in 9g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 1/12g | 0/8g | 10% | — | — |

### 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._

**Brisbane Lions**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Will Ashcroft | 27.5 | $1.87 | 57% | 24 ✓ |
| Lachie Neale | 26.5 | $1.95 | 36% | 28 ✗ |
| Hugh McCluggage ⚡ Under | 24.5 | $1.88 | 72% | 16 ✓ |
| Darcy Wilmot ⚡ Under | 22.5 | $1.92 | 68% | 30 ✗ |
| Josh Dunkley | 21.5 | $1.85 | 60% | 22 ✗ |
| Jaspa Fletcher ⚡ Under | 20.5 | $1.87 | 68% | 18 ✓ |
| Levi Ashcroft | 20.5 | $1.94 | 57% | 28 ✗ |
| Keidean Coleman ⚡ Under | 19.5 | $1.90 | 69% | 18 ✓ |
| Bruce Reville | 16.5 | $1.85 | 61% | 17 ✗ |

**Geelong Cats**

| Player | Line | Under | AI Under | Actual |
|---|---|---|---|---|
| Bailey Smith | 29.5 | $1.95 | 58% | 34 ✗ |
| Max Holmes | 27.5 | $1.87 | 60% | 26 ✓ |
| Tom Stewart ⚡ Under | 21.5 | $1.87 | 68% | 28 ✗ |
| Lawson Humphries ⚡ Under | 18.5 | $1.87 | 64% | 22 ✗ |
| Tom Atkins | 17.5 | $1.87 | 54% | 26 ✗ |
| Zach Guthrie | 16.5 | $1.87 | 62% | 16 ✓ |
| Oliver Dempsey | 16.5 | $1.87 | 47% | 19 ✗ |
| Jeremy Cameron | 14.5 | $1.86 | 59% | 16 ✗ |

### Prediction Breakdown — Pure Alpha Model

**Team ELO Ratings** — Brisbane Lions 1759 · Geelong Cats 1728 · ELO difference: 31 in favour of Brisbane Lions

**Positional Matchups** — lineup ELO by unit

| Unit | Brisbane Lions | Geelong Cats | Edge |
|---|---|---|---|
| Midfield | 1125 (best 1600) | 1085 (best 1478) | Brisbane Lions +40 |
| Forwards | 1030 (best 1600) | 981 (best 1472) | Brisbane Lions +49 |
| Defence | 1113 (best 1463) | 1093 (best 1600) | Brisbane Lions +20 |
| Ruck | 1076 (best 1323) | 1104 (best 1302) | Geelong Cats +28 |

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

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

**Model Confidence: 51%** — Geelong Cats predicted to win by 2 points · Predicted total: 192 pts

**Record:** 3/4 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

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Last updated: 2026-05-14 12:44 UTC (latest tip update)