These AFL Round 1 model value picks highlight how probability vs price can uncover consistent edges in player prop markets. Round 1 is where narratives dominate.
New season. New expectations. Strong opinions formed off limited information.
That’s where pricing inefficiencies tend to appear.
At Model Punt Club, we don’t react to noise. We measure probability vs price and let the numbers guide the decisions.
Round 1 delivered a clean example of how structured, repeatable logic can identify value across player prop markets.
📊 Round 1 Results — MVPs
The model identified 7 qualifying plays across Model Value 1 and Model Value 2 filters.
All 7 landed.
| Player | Market | Odds | Result | P&L |
|---|---|---|---|---|
| Jack Ross | 19+ Disposals | 1.67 | Win | +0.67 |
| Callum Mills | 22+ Disposals | 1.56 | Win | +0.56 |
| Conor Nash | 17+ Disposals | 1.41 | Win | +0.41 |
| Mason Redman | 22+ Disposals | 2.17 | Win | +1.17 |
| Marcus Bontempelli | 24+ Disposals | 1.95 | Win | +0.95 |
| Marcus Bontempelli | 25+ Disposals | 2.26 | Win | +1.26 |
| Marcus Bontempelli | 26+ Disposals | 2.67 | Win | +1.67 |
Total: +6.69 units
🔎 What the Model Is Identifying
These aren’t random picks.
Each selection passes structured filters based on:
- Recent performance consistency
- Role stability
- Market-implied probability
- Historical hit rates at similar price points
The focus is always the same:
Is the market underestimating the player’s true probability of clearing the line?
If yes, the bet qualifies.
🎯 The Bontempelli Example — Layered Value
Marcus Bontempelli is the clearest illustration of how value compounds.
Three separate lines were taken:
- 24+ disposals
- 25+ disposals
- 26+ disposals
This isn’t overexposure.
This is pricing inefficiency across multiple thresholds.
When a player projects comfortably above a baseline, the market often:
- Prices the lower line fairly
- Underprices the higher lines
That creates a ladder of value and all three lines landing is the outcome.
But the key point is this:
Each line stood on its own as a +EV decision.
📉 Short Odds vs Long Odds — Same Process
Round 1 included:
- Lower priced selections (1.41–1.67 range)
- Mid-range value (1.95–2.26)
- Higher-end pricing (2.67)
The model does not discriminate based on odds.
A $1.56 play can be value.
A $2.67 play can be value.
The only question is:
Does the implied probability match reality?
⚠️ Important Context — Results vs Expectation
A 7/7 result does not define the model. It’s a strong outcome but outcomes vary.
There will be rounds where:
- 3/7 land
- 4/7 land
- Variance swings results
That’s part of probability.
The goal is not perfection.
The goal is consistently identifying mispriced markets.
📊 Why Round 1 Creates Opportunity
Opening rounds are particularly valuable because:
- Roles are clearer internally than externally
- Markets rely more heavily on historical averages
- Public perception lags behind real usage
This creates gaps between:
What the market expects
vs
What the player is actually likely to produce
That gap is where value sits.
🧠 The Bigger Picture
This isn’t about tipping winners.
It’s about building a process that:
- Identifies value before the game
- Removes emotion from decision-making
- Scales across every game and market
Round 1 is just one sample. The edge comes from repetition.
📌 Final Takeaway
Round 1 AFL:
✔ 7 selections
✔ 7 wins
✔ +6.69 units
But more importantly:
✔ Clear alignment between probability and price
✔ Multiple markets identified correctly
✔ Process executed consistently
That’s what matters.
🔎 Access The Full Model
Access the full AFL & NRL player prop data:
- Every game-day sheet
- Every listed market
- Structured probability modelling
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This content is for educational and entertainment purposes only. Not financial advice. Gamble responsibly.