# Geelong Cats v Brisbane Lions — AFL Round 17 2026 AI Prediction by Alphr

## Full Time: Geelong Cats 101 – 123 Brisbane Lions

_Brisbane Lions devour Geelong Cats._

Half time: 53 – 60 · Alphr AI pre-game win probability: Geelong Cats 82% / Brisbane Lions 18% · GMHBA Stadium · Thu, 02 July, 07:30 pm AEST

**Goal Kickers** — Geelong Cats: Patrick Dangerfield (31' ×5), Shannon Neale (35' ×3), Jack Martin (47' ×2), Oliver Dempsey (70' ×2), Oliver Wiltshire (81'), Final quarter (30m 51s)Oisin Mullin (68') · Brisbane Lions: Charlie Cameron (2' 1st), Logan Morris (7' ×3), Levi Ashcroft (10'), Zac Bailey (12' ×3), Kai Lohmann (28' ×5), Josh Dunkley (74'), Cam Rayner (76'), Conor McKenna (84' ×2), Darcy Fort (97')

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

| Team | Pre-game AI win probability | Result |
|---|---|---|
| Geelong Cats | 82% | Lost |
| Brisbane Lions | 18% | Won |

Model call: **Missed** · Margin: 20.8 predicted → 22 actual · Markets hit: 0/4

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

### Full-Time Report

**Geelong Cats vs Brisbane Lions Prediction & Tips | AFL Round 17 2026**

_By Ben Dunlop · Published: 1 July 2026, 06:47 pm · Last updated: 2 July 2026, 10:46 pm_

Geelong Cats 101–123 Brisbane Lions in AFL Round 17 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.

The model had Geelong Cats at 82% to win this one, favoured by 20.8 points on the back of a 1767 to 1677 rating edge. Brisbane Lions won by 22. Get the direction right and you'd have still had the wrong team.

That's the thing about a 90 point read. It wasn't close to being close. Brisbane led 48 to 11 at quarter time and never gave that up, taking a 60 to 53 lead into the main break before extending it to 110 to 80 at three-quarter time. Final score: 123 to 101. The margin the model predicted, 20.8, ended up being almost identical to the actual 22. It just had the wrong side winning by it.

The positional numbers explain why. Brisbane came in rated ahead everywhere that matters, forwards 1248 to 1084, midfield 1236 to 1080, ruck 1175 to 1000, defence 1194 to 1140. That ruck gap showed up on the stat sheet, Brisbane winning hit-outs 48 to 40, and it fed a forward line that took 102 marks to Geelong's 66. That's not a minor gap. That's a team controlling territory in the air all day.

Geelong actually won the fight at the coalface. The Cats had more contested possessions, 154 to 143, more clearances, 42 to 40, and buried Brisbane on inside 50s, 69 to 52. On raw pressure numbers this looks like a Geelong performance. Problem is none of it translated, because Brisbane made every trip inside 50 count and Geelong didn't, evidenced by that marks-inside-50 count sitting almost level at 14 to 13 despite the huge gap in overall entries.

Disposal efficiency tells the rest of the story. Brisbane hit targets at 69.8%, Geelong at 66.8%. Add in Brisbane's edge in total disposals, 384 to 364, and you've got a side that used the ball better even while getting fewer looks at it through clearances and contested ball. Geelong's one clear form-line advantage, tackles, 57 to 55, barely moved the needle.

Geelong did win the intercept battle, 82 to 71, which usually points to a defence reading the play well. It wasn't enough to stop the scoreboard blowing out, because Brisbane's econonmy in front of goal from fewer entries did more damage than Geelong's volume from more of them.

Form lines pointed to this being tighter than the model's number suggested. Brisbane arrived on a three-game winning streak, WWW to finish their last five, averaging 102.6 points scored and just 1.2 average margin, a team living on the edge but finding ways to win. Geelong's five-game form had them at 92 points scored and an 11.6 average margin, tidier but not as battle-hardened. On the day, Brisbane's forward and ruck strength did the rest.

All four of the model's picks missed here. A useful reminder that a rating gap on paper doesn't override a genuine mismatch at ground level, particularly through the air and around the ruck contest. Wins and misses, all of it.

**Scoring by Quarter**

| Team | Q1 | Q2 | Q3 | Q4 | T |
|---|---|---|---|---|---|
| Geelong Cats | 11 | 42 | 27 | 21 | 101 |
| Brisbane Lions | 48 | 12 | 50 | 13 | 123 |

**Key Match Stats**

| Geelong Cats | Stat | Brisbane Lions |
|---|---|---|
| 364 | Disposals | **384** |
| **154** | Contested poss. | 143 |
| **42** | Clearances | 40 |
| **69** | Inside 50s | 52 |
| 66 | Marks | **102** |
| **14** | Marks inside 50 | 13 |
| **57** | Tackles | 55 |
| 40 | Hit-outs | **48** |
| **82** | Intercepts | 71 |
| 66.8% | Disposal eff. | **69.8%** |

**Model Report Card**

Brisbane Lions defied the model's 82% prediction for Geelong Cats, a notable upset. The margin model missed here, predicting 20.8 but the actual margin was 22 points. The game's 224 points came in 61 points higher than the predicted 163. Brisbane Lions led 53–60 at the break and pulled away in the second half to win by 22. A tough result for the model, all 4 picks missed on this one.

_Official AFL match stats · Generated by Alphr's model_

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

- **Head to Head:** Geelong Cats to win @ $1.47 (edge +13.6%) — model probability 81.6% — result: LOST
- **Line / Spread:** Geelong Cats -13.5 @ $1.90 (edge +7.3%) — result: LOST
- **Margin Band:** Geelong Cats 1-39 @ $3.30 (edge +0.0%) — result: LOST
- **Total (Over/Under):** Under 172.5 @ $1.89 (edge +2.1%) — result: LOST
- Predicted margin: Geelong Cats by 21 · Predicted total: 163

### Match Preview (pre-match read)

The model is firm on Geelong Cats here: 82% to see off Brisbane Lions. The heaviest factor is the ratings gap: Geelong Cats sit 89 ELO points clear, 1767 to 1677. Form leans Brisbane Lions' way: 3 from their last 5, against 2 for Geelong Cats.

On paper Brisbane Lions shade it, ahead on 5 of 7 factors including Midfield ELO, Recent Win Rate and Forward Line ELO. The model still sides with Geelong Cats, which says ELO Difference and Venue Advantage carry the most weight. The margin model has Geelong Cats by 20.8, with the two sides combining for about 163. Geelong Cats to win, and win clearly. The model isn't hedging.

_Pre-match read · Alphr model_

### Recent Form (Last 5)

| Geelong Cats | Stat | Brisbane Lions |
|---|---|---|
| 2.0 | Wins (Last 5) | 3.0 |
| 92.0pts | Avg Score | 102.6pts |
| 80.4pts | Avg Conceded | 101.4pts |
| 11.6pts | Avg Margin | 1.2pts |
| 379.8 | Disposals | 356.8 |
| 50.0 | Inside 50s | 50.0 |
| 58.0 | Tackles | 46.6 |
| 38.0 | Clearances | 40.6 |

### Form & History

_Last 5 games, oldest → newest._

| Team | Last 5 | Avg Pts |
|---|---|---|
| Geelong Cats | R11 W · R12 L · R13 L · R14 W · R15 L | 92.0 |
| Brisbane Lions | R11 L · R12 L · R13 W · R14 W · R16 W | 102.6 |

### H2H History (Last 5) — Brisbane Lions lead 3-2

| Season | Round | Home | Score | Away |
|---|---|---|---|---|
| 2026 | R10 | Brisbane Lions | 76 – 117 | Geelong Cats |
| 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)

|  | Geelong Cats | Brisbane Lions |
|---|---|---|
| Attack rank | 4th (strong) | 2nd (strong) |
| Defence rank | 9th | 15th (weak) |
| Goals scored · conceded | 157 · 132 | 167 · 149 |
| Goal Assists | 4.7/g | 5.6/g |
| Disposals | 96/g | 90/g |
| Inside 50s | 20.4/g | 19.5/g |
| Marks Inside 50 | 10.4/g | 9.2/g |
| Disposal Efficiency | 64.7% | 65.6% |

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

|  | Geelong Cats | Brisbane Lions |
|---|---|---|
| Attack rank | 12th | 8th |
| Defence rank | 2nd (strong) | 9th |
| Goals scored · conceded | 41 · 36 | 48 · 46 |
| Goal Assists | 4.1/g | 3.8/g |
| Disposals | 147/g | 166/g |
| Inside 50s | 24.9/g | 26.7/g |
| Marks Inside 50 | 1.7/g | 3.7/g |
| Disposal Efficiency | 72.6% | 69% |

**Defenders** (Key & Medium Defenders)

|  | Geelong Cats | Brisbane Lions |
|---|---|---|
| Attack rank | 2nd (strong) | 11th |
| Defence rank | 5th (strong) | 5th (strong) |
| Goals scored · conceded | 19 · 9 | 10 · 9 |
| Goal Assists | 1.6/g | 1.3/g |
| Disposals | 133/g | 114/g |
| Inside 50s | 12/g | 11.5/g |
| Marks Inside 50 | 0.9/g | 0.5/g |
| Disposal Efficiency | 78.5% | 80.3% |

**Who scores on Brisbane Lions** — Key Forwards 3.75/g (lg 3.83) -2% · Forwards 4.33/g (lg 4.45) -3% · Midfielders 2.35/g (lg 2.49) -6%
**Who scores on Geelong Cats** — Key Forwards 4/g (lg 3.83) +4% · Forwards 4.18/g (lg 4.45) -6% · Midfielders 2.18/g (lg 2.49) -12%

_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 | 39 in 14g | 32/10g (10·3·3·1·3·3·4·0·3·2) | 44/22g | 144/50g | 88% | — | — |
| – | Shannon Neale | KF | 27 in 15g | 15/10g (1·2·3·2·2·0·0·1·2·2) | 5/6g | 41/24g | 80% | — | 🏉 35' 45' 62' |
| – | Oliver Henry | FWD | 25 in 14g | 17/10g (1·0·1·4·2·2·2·1·2·2) | 11/7g | 42/29g | 82% | — | — |
| – | Shaun Mannagh | FWD | 21 in 15g | 16/10g (0·1·4·3·5·1·1·1·0·0) | 7/5g | 24/20g | 70% | — | — |
| – | Jack Martin | FWD | 17 in 13g | 13/10g (1·1·1·2·2·0·1·2·0·3) | 13/16g | 18/14g | 72% | — | 🏉 47' 57' |
| – | Oliver Dempsey | MID | 15 in 15g | 8/10g (1·0·1·1·0·0·2·1·2·0) | 9/7g | 26/29g | 70% | — | 🏉 70' 92' |
| – | Patrick Dangerfield | FWD | 12 in 11g | 11/10g (2·1·1·2·1·1·1·1·1·0) | 22/23g | 80/75g | 76% | — | 🏉 31' 37' 88' 92' 88' |
| – | Oliver Wiltshire | FWD | 7 in 7g | 8/9g (0·1·0·1·1·0·0·3·2) | 0/0g | 3/3g | 56% | — | 🏉 81' |
| – | Bailey Smith | MID | 6 in 14g | 5/10g (1·1·0·0·0·2·1·0·0·0) | 7/11g | 4/17g | 34% | — | — |
| – | Jack Henry | DEF | 6 in 11g | 6/10g (1·0·0·0·0·1·2·1·0·1) | 4/16g | 15/64g | 20% | — | — |
| – | Max Holmes | MID | 4 in 15g | 3/10g (0·0·2·0·0·0·0·0·1·0) | 4/10g | 19/44g | 32% | — | — |
| – | Lawson Humphries | DEF | 3 in 14g | 3/10g (0·1·0·1·0·0·1·0·0·0) | 0/6g | 5/19g | 20% | — | — |
| – | Mark O'Connor | DEF | 3 in 13g | 3/10g (3·0·0·0·0·0·0·0·0·0) | 1/14g | 4/56g | 6% | — | — |
| – | Oisin Mullin | MID | 2 in 15g | 2/10g (0·0·0·0·1·0·0·0·0·1) | 3/7g | 0/23g | 12% | — | — |
| – | Tom Atkins | MID | 2 in 15g | 2/10g (0·0·0·0·0·1·0·0·1·0) | 1/13g | 12/58g | 16% | — | — |
| – | Connor O'Sullivan | DEF | 1 in 15g | 1/10g (0·0·0·0·0·1·0·0·0·0) | 0/5g | 1/16g | 4% | — | — |
| – | Jake Kolodjashnij | DEF | 1 in 9g | 1/10g (0·0·1·0·0·0·0·0·0·0) | 0/15g | 4/73g | 6% | — | — |
| – | Mark Blicavs | MID | 1 in 12g | 1/10g (0·1·0·0·0·0·0·0·0·0) | 10/24g | 22/101g | 26% | — | — |
| – | Sam De Koning | DEF | 1 in 14g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 1/8g | 4/39g | 10% | — | — |
| – | Tom Stewart | DEF | 1 in 13g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 1/12g | 3/72g | 6% | — | — |
| – | Zach Guthrie | DEF | 1 in 15g | 1/10g (0·0·1·0·0·0·0·0·0·0) | 1/12g | 6/51g | 6% | — | — |
| – | Mitchell Edwards | RUC | 0 in 12g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/1g | 0/6g | 0% | — | — |
| – | Tanner Bruhn | DEF | 0 in 14g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/6g | 7/19g | 12% | — | — |

**Brisbane Lions** (team sheet)

| # | Player | Pos | 2026 | Last 10 | vs opp | Venue | Goal % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| – | Logan Morris | KF | 38 in 14g | 30/10g (3·2·4·4·2·1·1·7·3·3) | 12/6g | 5/1g | 90% | — | 🏉 7' 19' 72' |
| – | Charlie Cameron | FWD | 32 in 15g | 23/10g (3·4·2·2·3·2·2·2·1·2) | 36/21g | 5/6g | 78% | — | 🏉 2' |
| – | Kai Lohmann | FWD | 24 in 15g | 14/10g (1·1·4·2·0·3·0·0·1·2) | 7/8g | 2/1g | 72% | — | 🏉 28' 54' 90' 96' 83' |
| – | Zac Bailey | FWD | 20 in 14g | 13/10g (0·3·4·0·1·0·1·0·2·2) | 9/13g | 0/3g | 74% | — | 🏉 12' 14' 85' |
| – | Cam Rayner | FWD | 17 in 15g | 12/10g (2·1·2·0·1·3·0·0·0·3) | 16/14g | 5/3g | 70% | — | 🏉 76' |
| – | Conor McKenna | FWD | 12 in 9g | 12/10g (0·2·2·0·1·2·0·1·2·2) | 4/8g | 0/0g | 34% | — | 🏉 84' 100' |
| – | Sam Draper | RUC | 9 in 14g | 7/10g (1·1·0·1·1·0·1·1·0·1) | 2/6g | 0/2g | 60% | — | — |
| – | Will Ashcroft | MID | 7 in 15g | 6/10g (1·1·0·0·0·0·2·0·2·0) | 3/7g | 1/1g | 38% | — | — |
| – | Darcy Fort | RUC | 6 in 14g | 5/10g (0·1·0·1·0·0·0·1·1·1) | 0/6g | 3/4g | 32% | — | 🏉 97' |
| – | Levi Ashcroft | MID | 6 in 15g | 5/10g (0·0·0·2·1·0·1·0·0·1) | 4/5g | 1/1g | 40% | — | 🏉 10' |
| – | Bruce Reville | MID | 5 in 15g | 2/10g (0·0·1·0·0·0·0·0·1·0) | 1/4g | 0/1g | 24% | — | — |
| – | Lachie Neale | MID | 4 in 15g | 4/10g (0·0·1·1·0·1·0·0·1·0) | 7/23g | 1/8g | 28% | — | — |
| – | Eric Hipwood | KF | 3 in 2g | 7/10g (0·1·1·0·1·0·1·0·2·1) | 17/14g | 5/3g | 70% | — | — |
| – | Jarrod Berry | MID | 3 in 10g | 3/10g (0·0·1·0·0·0·0·1·0·1) | 4/13g | 0/3g | 30% | — | — |
| – | Jaspa Fletcher | DEF | 3 in 15g | 2/10g (1·0·0·0·0·0·1·0·0·0) | 1/8g | 0/1g | 22% | — | — |
| – | James Tunstill | MID | 2 in 8g | 2/10g (0·0·1·0·0·0·0·1·0·0) | 0/2g | 0/0g | 17% | — | — |
| – | Darcy Wilmot | DEF | 1 in 15g | 1/10g (0·0·1·0·0·0·0·0·0·0) | 1/9g | 1/1g | 14% | — | — |
| – | Josh Dunkley | MID | 1 in 15g | 1/10g (0·0·0·0·0·0·0·0·1·0) | 7/16g | 3/4g | 14% | — | 🏉 74' |
| – | Ty Gallop | DEF | 1 in 13g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 0/2g | 0/0g | 14% | — | — |
| – | Darcy Gardiner | DEF | 0 in 8g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/12g | 0/4g | 10% | — | — |
| – | Harris Andrews | DEF | 0 in 12g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/20g | 0/6g | 0% | — | — |
| – | Noah Answerth | DEF | 0 in 7g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/7g | 0/2g | 2% | — | — |
| – | Ryan Lester | DEF | 0 in 11g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 3/20g | 3/6g | 2% | — | — |

### Prediction Breakdown — Pure Alpha Model

**Team ELO Ratings** — Geelong Cats 1767 · Brisbane Lions 1677 · ELO difference: 89 in favour of Geelong Cats

**Positional Matchups** — lineup ELO by unit

| Unit | Geelong Cats | Brisbane Lions | Edge |
|---|---|---|---|
| Midfield | 1080 (best 1322) | 1236 (best 1538) | Brisbane Lions +156 |
| Forwards | 1084 (best 1296) | 1248 (best 1495) | Brisbane Lions +164 |
| Defence | 1140 (best 1455) | 1194 (best 1340) | Brisbane Lions +54 |
| Ruck | 1000 (best 1000) | 1175 (best 1203) | Brisbane Lions +175 |

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

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

**Model Confidence: 82%** — Geelong Cats predicted to win by 21 points · Predicted total: 163 pts

**Record:** 0/4 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: 2026-07-02 12:46 UTC (latest tip update)