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Monte Carlo simulation · updated after each race · 2026
ANT beats LIN off pole at Japanese Grand Prix
Pole doesn't guarantee Sunday anymore — Arvid LINDBLAD started P1, Kimi ANTONELLI finished P1. It's the kind of reshuffle that makes Monte Carlo models cry.
R04 · 2026 · SPRINT
Miami Grand Prix
Miami Gardens
2025 PODIUM
POLE · ANT
| POS | DRIVER | PTS | TREND | FORM |
|---|---|---|---|---|
| 11 | LINArvid LINDBLAD | 4 | ▼ 74% | |
| 12 | HADIsack HADJAR | 4 | ▼ 74% | |
| 13 | SAICarlos SAINZ | 2 | ▼ 87% | |
| 14 | BORGabriel BORTOLETO | 2 | ▼ 87% | |
| 15 | OCOEsteban OCON | 1 | ▼ 94% | |
| 16 | COLFranco COLAPINTO | 1 | ▼ 94% | |
| 17 | ALBAlexander ALBON | 0 | ▼ 100% | |
| 18 | ALOFernando ALONSO | 0 | ▼ 100% | |
| 19 | STRLance STROLL | 0 | ▼ 100% | |
| 20 | HULNico HULKENBERG | 0 | ▼ 100% |
Delta vs season average · green = overperforming, red = under
SIMULATING · R04 · 2026
Miami Grand Prix
Play with pit stops and compounds. See how many seconds you'd win or lose vs the optimal call.
2 stints · At least 2 different compounds required (FIA Sporting Reg 30.5)
L1–22
L23–57HOW THE MATH WORKS▾
lap_time = base_lap + compound_offset + deg_rate × stint_age
Each lap's time is the sum of three factors:
- base_lap = 90.5s — reference lap time at this circuit with fresh tyres.
- compound_offset — compound-specific offset: Soft 0.0s · Medium +0.3s · Hard +0.6s. Soft is the fastest but degrades quickest.
- deg_rate × stint_age — linear degradation across the stint (S 0.12s/lap, M 0.07s/lap, H 0.03s/lap). That's why a long Soft stint ends up slower than a short one.
Then we add pit loss (22s per stop — the net time lost entering the pit lane, stopping, and rejoining the circuit).
total_time = Σ lap_time + (stops × pit_loss)
Simplified model calibrated from Miami 2025 lap data. Ignores safety cars, rain, and driver-to-driver variance.
Predict the Podium
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Head-to-Head Builder
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