# Sharks v Storm — NRL Round 11 2025 AI Prediction by Alphr

## Full Time: Sharks 31 – 26 Storm

_Sharks hunt down a gallant Storm._

Half time: 25 – 12 · Alphr AI pre-game win probability: Sharks 40% / Storm 60% · Sharks Stadium, Sydney · Sat, 17 May, 07:35 pm AEST

**Try Scorers** — Sharks: Ronaldo Mulitalo (8' Tipped ⚡), Addin Fonua-Blake (22'), Daniel Atkinson (27'), KL Iro (36'), Daniel Atkinson (52') · Storm: Grant Anderson (4' 1st Tipped ⚡), Xavier Coates (31' Tipped ⚡), Xavier Coates (44' Tipped ⚡), Nick Meaney (47'), Xavier Coates (67' Tipped ⚡)

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

| Team | Pre-game AI win probability | Result |
|---|---|---|
| Storm | 60% | Lost |
| Sharks | 40% | Won |

Model call: **Missed** · Margin: 5.8 predicted → 5 actual · Markets hit: 0/3

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

### Full-Time Report

**Cronulla Sharks vs Melbourne Storm Prediction & Tips | NRL Round 11 2025**

_By Ben Dunlop · Published: 28 Feb 2026, 07:36 pm · Last updated: 24 July 2026, 12:42 pm_

Sharks 31–26 Storm in NRL Round 11 at Sharks Stadium, Sydney. Here's how the result stacked up against the model's call, with the win-probability story and where the value landed.

Sharks were up 25-12 at the break against Storm and looking every bit the better side. By full time it was 31-26, a five-point squeak, and the second half was a completely different contest to the first.

The start belonged to Storm on the scoreboard for all of four minutes, Grant Anderson crossing early to make it 0-4. Then Sharks put together the best stretch of footy either side would manage all night. Ronaldo Mulitalo hit back inside three minutes, Addin Fonua-Blake and Daniel Atkinson piled on tries either side of the half-hour, and by the time Braydon Trindall slotted a field goal in the 39th minute, Sharks had run out to 25-12. Xavier Coates got one back for Storm at 31 minutes, but it barely slowed things down. KL Iro's try in the 35th made it four tries to one for the home side inside a brutal 30-minute window.

Storm came out after the break and made a genuine fist of it. Coates scored twice more, in the 44th and the 67th, and Nick Meaney added another in the 46th to drag it back to 25-22 within twenty minutes of the restart. Daniel Atkinson's second try in the 52nd was the only thing keeping Sharks in front through that stretch, and it turned out to be enough, just.

The stat sheet explains why it was that tight. Storm were the bigger, more direct side all night, out-gaining Sharks 1,637 metres to 1,530 and doubling up on post-contact yardage, 546 to 489. They offloaded 19 times to 11 and completed at a lower rate but still finished with the better defensive read, missing only 23 tackles to Sharks' 20 at an 88.5% effective clip. None of that is surprising given the pre-match numbers had Storm's forward pack rated 1096 to 1029 and their halves pairing at 1384 to 1294, clearly the stronger units on paper.

Where Sharks won it was in the moments that actually put points on the board. Five line breaks to four, 23 tackle breaks to 20, and a completion rate of 76% against Storm's 72% meant Sharks made better use of the ball they had, even with less of it, 49% to 51%. Discipline mattered too. Sharks gave away 7 penalties to Storm's 5, but it was the tries, not the penalty count, that decided this one.

Storm came in as the form side, averaging 34 points a game across their last five compared to Sharks' 26.8, and carrying a much healthier average margin of 15.6 points to Sharks' 10. Alphr's model had them backed at 60% to win, with a predicted margin of 5.8 points on a combined total of 44. The final margin landed at five points, so the model's read on how close it would be was sound. It just picked the wrong side to be ahead at the death, going 3 from 16 on the night.

Sharks got their scoring done early and made it stand up. Storm did all their damage after half-time and ran out of time doing it.

**Scoring by Half**

| Team | H1 | H2 | T |
|---|---|---|---|
| Sharks | 25 | 6 | 31 |
| Storm | 12 | 14 | 26 |

**Key Match Stats**

| Sharks | Stat | Storm |
|---|---|---|
| 49% | Possession | **51%** |
| **76%** | Completion rate | 72% |
| 1,530 | Run metres | **1,637** |
| 489 | Post-contact metres | **546** |
| **5** | Line breaks | 4 |
| **23** | Tackle breaks | 20 |
| 11 | Offloads | **19** |
| 85.1% | Effective tackle % | **88.5%** |
| **20** | Missed tackles | 23 |
| **11** | Errors | 12 |
| 7 | Penalties conceded | **5** |
| 419 | Kick metres | **489** |

**Model Report Card**

Sharks defied the model's 60% prediction for Storm, a notable upset. The predicted margin of 5.8 was reasonable against the actual 5-point result. The model went 3/16 on this match.

**Referee Watch**

Adam Gee officiated this match (313 career games). The combined score of 57 points was 14 points above Adam Gee's career average of 43. Sharks's home victory fits Adam Gee's profile, home teams win 58% of the time under this referee. Adam Gee averaged 12 penalties per game heading in, a whistle-heavy referee profile. 64% of his career sin bins go against away teams, a statistically significant away-team bias.

**Key moments (momentum model)**

- 4' Try — Grant Anderson (Storm) — 0-4 · win-prob swing -5 pts
- 7' Try — Ronaldo Mulitalo (Sharks) — 4-6 · win-prob swing +6 pts
- 21' Try — Addin Fonua-Blake (Sharks) — 10-6 · win-prob swing +5 pts
- 26' Try — Daniel Atkinson (Sharks) — 16-6 · win-prob swing +5 pts
- 31' Try — Xavier Coates (Storm) — 18-10 · win-prob swing -5 pts
- 35' Try — KL Iro (Sharks) — 22-12 · win-prob swing +14 pts
- 39' 1 Point Field Goal-Made — Braydon Trindall (Sharks) — 25-12 · win-prob swing +1 pts
- 44' Try — Xavier Coates (Storm) — 25-16 · win-prob swing -3 pts
- 46' Try — Nick Meaney (Storm) — 25-20 · win-prob swing -4 pts
- 52' Try — Daniel Atkinson (Sharks) — 29-22 · win-prob swing +5 pts
- 67' Try — Xavier Coates (Storm) — 31-26 · win-prob swing -3 pts

_Official NRL match stats · Generated by Alphr's model_

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

- **Head to Head:** Storm to win @ $1.60 (edge -6.9%) — model probability 59.8% — result: LOST
- **Line / Spread:** Storm +3.5 @ $1.91 (edge -6.9%) — result: LOST
- **Total (Over/Under):** Under 46.5 @ $1.91 (edge +4.9%) — result: LOST
- Predicted margin: Storm by 6 · Predicted total: 44

### Match Preview (pre-match read)

Storm are the call at 60%, but Sharks stay live at 40%. The heaviest factor is the ratings gap: Storm sit 79 ELO points clear, 1659 to 1580. Form leans Sharks' way: 4 from their last 5, against 3 for Storm.

Storm own the matchup too, leading 4 of 7 factors including ELO Difference, Forward Pack and Backline Quality. The margin model has Storm by 5.8, with the two sides combining for about 44. Lean Storm, but it shapes as a genuine contest.

Storm have won 7 of the last 10 between these two, and Storm took the most recent meeting 24-20 in 2026 Round 27.

Sharks are 11-2 at home this year. Storm have won 3 games this season after trailing at half-time.

On the ladder it's Sharks 5th against Storm 3rd.

**By the numbers**

|  |  |
|---|---|
| H2H (last 10) | Sharks 3 · Storm 7 |
| Last meeting | Storm 24-20 |
| Sharks last 4 | WWWL · 90 for, 50 against |
| Sharks at home | 11-2 this season |
| Storm last 4 | LWWL · 84 for, 88 against |
| Storm away | 8-4 this season |
| Ladder | Sharks 5th · Storm 3rd |
| Finals odds | Both locked into the eight |

_Pre-match read · Alphr model_

### Referee Indicator — Balanced

**Adam Gee** — 313 career games since 2013.

| Team | Record under Adam Gee | Win rate |
|---|---|---|
| Sharks | 30W–13L | 70% |
| Storm | 30W–14L | 68% |

Avg total: 43.2 pts · Home win %: 58% · Home bias: Leans home

Both sides have a similar record under Adam Gee, Sharks 30W–13L (70%) and Storm 30W–14L (68%). Home teams win 58% of his matches (vs ~52% league avg).

Adam Gee averages 12 penalties per game, above the league norm. Expect frequent stoppages. Penalises away teams more, 5.5 against home vs 6.6 against away. 64% of his 124 career sin bins go to away teams.

### Recent Form (Last 5)

| Sharks | Stat | Storm |
|---|---|---|
| 4.0 | Wins (Last 5) | 3.0 |
| 26.8pts | Avg Score | 34.0pts |
| 16.8pts | Avg Conceded | 18.4pts |
| 10.0pts | Avg Margin | 15.6pts |
| 1772.0m | Run Metres | 1739.4m |
| 4.2 | Line Breaks | 6.4 |
| 324.2 | Tackles | 318.6 |
| 11.2 | Errors | 13.4 |

### Form & History

| Team | Last 5 | Avg Pts |
|---|---|---|
| Sharks | 4W–1L | 26.8 |
| Storm | 3W–2L | 34.0 |

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

| Season | Round | Home | Score | Away |
|---|---|---|---|---|
| 2026 | R27 | Sharks | 20 – 24 | Storm |
| 2025 | PF | Storm | 22 – 14 | Sharks |
| 2025 | R17 | Storm | 30 – 6 | Sharks |
| 2024 | FW1 | Storm | 37 – 10 | Sharks |
| 2024 | R10 | Storm | 18 – 25 | Sharks |

### Positional Matchup

_Season-to-date production per game with league-wide attack/defence tiers (17 teams)._

**Field Matchup** — where one team attacks vs where the other concedes:
- Sharks' best path is the left edge: NRL's 1st-ranked left edge attack (2 tries/game) runs at a Storm defence ranked 3rd there (1 conceded/game). Key man: Iro, 7 tries in that channel this season.
- Storm's best path is the middle: NRL's 1st-ranked middle attack (3.11 tries/game) runs at a Sharks defence ranked 2nd there (1 conceded/game). Key man: Papenhuyzen, 12 tries in that channel this season.

| Channel | Sharks | Storm |
|---|---|---|
| Left | 2/g (att 1st (strong)) · concedes 1/g (def 3rd (strong)) | 1.44/g (att 6th (strong)) · concedes 1/g (def 3rd (strong)) |
| Middle | 1.4/g (att 10th) · concedes 1/g (def 2nd (strong)) | 3.11/g (att 1st (strong)) · concedes 1.11/g (def 3rd (strong)) |
| Right | 1/g (att 8th) · concedes 1.1/g (def 9th) | 1.11/g (att 6th (strong)) · concedes 1.11/g (def 11th) |

**Attack Spine** (Halfback · Five-Eighth · Hooker)

|  | Sharks | Storm |
|---|---|---|
| Attack rank | 16th (weak) | 7th |
| Defence rank | 5th (strong) | 2nd (strong) |
| Tries scored · conceded | 3 · 5 | 7 · 2 |
| Try Assists | 2.3/g | 2.4/g |
| Run Metres | 166m/g | 228m/g |
| Tackle Breaks | 2.3/g | 5.3/g |
| Line Breaks | 0.2/g | 1/g |
| Tackle Efficiency | 87.1% | 84.3% |

**Outside Backs** (Fullback · Wingers · Centres)

|  | Sharks | Storm |
|---|---|---|
| Attack rank | 2nd (strong) | 1st (strong) |
| Defence rank | 1st (strong) | 11th |
| Tries scored · conceded | 27 · 17 | 32 · 22 |
| Try Assists | 1/g | 2/g |
| Run Metres | 764m/g | 700m/g |
| Tackle Breaks | 17.3/g | 15.3/g |
| Line Breaks | 3/g | 4.3/g |
| Tackle Efficiency | 81.1% | 77.5% |

**Forwards** (Props · 2nd Rows · Lock)

|  | Sharks | Storm |
|---|---|---|
| Attack rank | 3rd (strong) | 4th (strong) |
| Defence rank | 6th (strong) | 1st (strong) |
| Tries scored · conceded | 13 · 6 | 10 · 0 |
| Try Assists | 0.3/g | 0.4/g |
| Run Metres | 552m/g | 539m/g |
| Tackle Breaks | 9.7/g | 8.9/g |
| Line Breaks | 1.2/g | 0.8/g |
| Tackle Efficiency | 90.9% | 91.2% |

**Who scores on Storm** — Wingers 1.27/g (lg 1.25) +2% · Centres 0.68/g (lg 0.67) +1% · Locks 0.08/g (lg 0.1) -20%
**Who scores on Sharks** — Locks 0.13/g (lg 0.1) +30% · Hookers 0.18/g (lg 0.14) +29% · Halfbacks 0.23/g (lg 0.21) +10%

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

### Try Scorer History — Who Crosses The Line

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

**Sharks** (team sheet)

| # | Player | Pos | 2025 | Last 10 | vs opp | Venue | Try % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| 1 | William Kennedy | FB | 4 in 10g | 4/10g (0·0·1·0·0·1·1·1·0·0) | 0/8g | 1/2g | 28% | ⚡ Anytime Try $3.90 AI 38% ✗ No try; 🎯 First Try $20.00 AI 5% ✗ Not first | — |
| 2 | Samuel Stonestreet | WG | 8 in 10g | 8/10g (0·2·0·0·0·2·2·0·2·0) | 0/0g | 0/2g | 48% | ⚡ Anytime Try $2.20 AI 65% ✗ No try; 🎯 First Try $11.00 AI 11% ✗ Not first | — |
| 3 | Jesse Ramien | CE | 1 in 10g | 1/10g (1·0·0·0·0·0·0·0·0·0) | 4/10g | 0/2g | 20% | — | — |
| 4 | KL Iro | CE | 7 in 6g | 7/10g (0·0·0·0·1·2·1·1·1·1) | 0/2g | 2/2g | 38% | — | 🏉 36' |
| 5 | Ronaldo Mulitalo | WG | 4 in 10g | 4/10g (0·1·0·0·0·0·0·1·0·2) | 4/6g | 0/2g | 46% | ⚡ Anytime Try $2.03 AI 43% ✓ Scored; 🎯 First Try $11.00 AI 6% ✗ Not first | 🏉 8' |
| 6 | Braydon Trindall | 5/8 | 2 in 10g | 2/10g (0·0·1·0·0·0·0·0·0·1) | 0/5g | 1/2g | 32% | — | — |
| 7 | Nicho Hynes | HB | 1 in 10g | 1/10g (0·0·1·0·0·0·0·0·0·0) | 0/3g | 1/2g | 16% | — | — |
| 8 | Addin Fonua-Blake | PR | 3 in 10g | 3/10g (1·0·0·0·0·0·1·0·0·1) | 2/15g | 0/2g | 32% | — | 🏉 22' |
| 9 | Blayke Brailey | HK | 0 in 10g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 1/10g | 0/2g | 6% | — | — |
| 10 | Oregon Kaufusi | PR | 1 in 10g | 1/10g (0·0·0·0·0·0·1·0·0·0) | 1/10g | 0/2g | 8% | — | — |
| 11 | Briton Nikora | 2R | 6 in 10g | 6/10g (1·1·1·0·2·0·0·0·1·0) | 3/8g | 1/2g | 38% | ⚡ Anytime Try $3.75 AI 34% ✗ No try | — |
| 12 | Billy Burns | 2R | 1 in 6g | 1/10g (0·0·0·0·0·0·0·1·0·0) | 2/3g | 0/0g | 12% | — | — |
| 13 | Cameron McInnes | LK | 1 in 10g | 1/10g (0·0·0·0·0·0·0·0·1·0) | 2/12g | 0/2g | 8% | — | — |
| 14 | Daniel Atkinson | INT | 0 in 10g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/3g | 0/2g | 11% | — | 🏉 27' 52' |
| 15 | Jesse Colquhoun | INT | 0 in 3g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/1g | 0/0g | 0% | — | — |
| 16 | Siosifa Talakai | INT | 0 in 8g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 2/5g | 0/2g | 12% | — | — |
| 17 | Braden Uele | INT | 0 in 5g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 1/9g | 0/1g | 4% | — | — |

**Storm** (team sheet)

| # | Player | Pos | 2025 | Last 10 | vs opp | Venue | Try % | Alphr play | This game |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Ryan Papenhuyzen | FB | 12 in 9g | 12/10g (0·2·1·1·1·0·1·1·1·4) | 5/7g | 0/0g | 64% | ⚡ Anytime Try $1.85 AI 72% ✗ No try; 🎯 First Try $7.50 AI 11% ✗ Not first | — |
| 2 | Sualauvi Faalogo | WG | 1 in 4g | 3/10g (0·0·0·2·0·0·0·0·1·0) | 0/1g | 0/0g | 29% | — | — |
| 3 | Grant Anderson | CE | 6 in 9g | 6/10g (0·0·1·0·3·1·0·0·1·0) | 0/3g | 0/0g | 32% | ⚡ Anytime Try $3.40 AI 39% ✓ Scored | 🏉 4' |
| 4 | Nick Meaney | CE | 2 in 5g | 2/10g (0·0·0·0·0·1·0·0·0·1) | 3/9g | 0/0g | 20% | — | 🏉 47' |
| 5 | Xavier Coates | WG | 7 in 9g | 7/10g (0·2·1·0·0·2·1·1·0·0) | 4/6g | 0/0g | 48% | ⚡ Anytime Try $1.77 AI 52% ✓ Scored; 🎯 First Try $8.50 AI 6% ✗ Not first | 🏉 31' 44' 67' |
| 6 | Cameron Munster | 5/8 | 2 in 9g | 2/10g (0·0·0·0·1·0·0·0·0·1) | 4/16g | 0/0g | 22% | — | — |
| 7 | Jahrome Hughes | HB | 2 in 8g | 5/10g (3·0·1·0·0·0·0·0·0·1) | 2/10g | 0/0g | 32% | — | — |
| 8 | Stefano Utoikamanu | PR | 1 in 9g | 1/10g (0·0·0·0·1·0·0·0·0·0) | 0/4g | 0/0g | 10% | — | — |
| 9 | Bronson Garlick | Replacement | 2 in 7g | 2/10g (0·0·0·0·1·0·0·0·0·1) | 0/1g | 0/0g | 10% | — | — |
| 10 | Josh King | PR | 3 in 9g | 3/10g (0·1·0·0·0·1·0·0·0·1) | 2/11g | 0/0g | 18% | — | — |
| 11 | Shawn Blore | 2R | 1 in 9g | 1/10g (0·0·0·0·0·1·0·0·0·0) | 1/4g | 0/0g | 10% | — | — |
| 12 | Eliesa Katoa | 2R | 4 in 9g | 4/10g (0·1·1·0·0·0·0·1·0·1) | 1/7g | 0/0g | 42% | — | — |
| 13 | Trent Loiero | LK | 1 in 9g | 1/10g (0·0·0·0·0·1·0·0·0·0) | 0/5g | 0/0g | 4% | — | — |
| 14 | Tyran Wishart | INT | 2 in 9g | 2/10g (0·0·1·0·0·0·0·1·0·0) | 1/5g | 0/0g | 30% | — | — |
| 16 | Tui Kamikamica | INT | 0 in 7g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 3/8g | 0/0g | 2% | — | — |
| 17 | Joe Chan | INT | 0 in 5g | 0/10g (0·0·0·0·0·0·0·0·0·0) | 0/0g | 0/0g | 4% | — | — |

### Prediction Breakdown — Pure Alpha Model

**Team ELO Ratings** — Sharks 1580 · Storm 1659 · ELO difference: 79 in favour of Storm

**Positional Matchups** — lineup ELO by unit

| Unit | Sharks | Storm | Edge |
|---|---|---|---|
| Forwards | 1029 (best 1266) | 1096 (best 1313) | Storm +67 |
| Backs | 1011 (best 1138) | 1031 (best 1134) | Storm +20 |
| Halves | 1294 (best 1294) | 1384 (best 1384) | Storm +90 |
| Hooker | 1024 | 1088 | Storm +64 |

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

| # | Factor | Weight | Favours |
|---|---|---|---|
| 1 | ELO Difference | 14.0% | Storm |
| 2 | Forward Pack | 12.0% | Storm |
| 3 | Backline Quality | 10.0% | Storm |
| 4 | Halves Control | 9.0% | Storm |
| 5 | Recent Win Rate | 9.0% | Sharks |
| 6 | Referee Tendency | 7.0% | Sharks |
| 7 | Venue Advantage | 7.0% | — |

**Model Confidence: 60%** — Storm predicted to win by 6 points · Predicted total: 44 pts

**Record:** 0/3 match 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: 2026-07-24 02:42 UTC (latest tip update)