Race Winner Prediction

5.412 km lap length15 cornersMedium overtaking difficulty

Race date October 4, 2026 · generated Oct 4, 2026, 8:53 PM UTC · rain scenario weighted at 10%

Predicted vs. Actual

Predicted winner

ANT (26.9%)

Actual winner

VER (missed)

Podium hits

2 / 3

Brier score (win)

0.0433

The model gave the actual winner (VER) a 10.5% chance beforehand. Predicted live, before the race. See the track record page for the model's accuracy across every graded race.

Our model: 0.0433 · Grid-based baseline (always pick the polesitter): 0.0000 (baseline beats the model this time — lower is better)

Where the podium call missed

RUS (predicted podium) didn't finish — Retired.
VER finished P1 — the model projected around P5.

Predicted vs. actual finishing position, every driver

Green, right — finished better than the model expected (underrated). Red, left — finished worse (overrated). Sorted by size of the miss.

Win Probability — Top 10

Error bars show ± 1 standard deviation of win probability across batches of the Monte Carlo simulation — how much this estimate would wobble on a re-run, not a formal confidence interval.

Full Prediction Table

Click a row to see what drove that driver's score.

Pos	Driver	Team	Win %	Podium %	Points %	Exp. Pos	Actual
1	▸ANT	Mercedes	26.9% ± 0.6%	60.2%	97.7%	3.55	2
2	▸HAM	Ferrari	19.6% ± 0.6%	51.3%	96.9%	4.07	3
3	▸RUS	Mercedes	15.2% ± 0.5%	42.4%	94.2%	4.77	20
4	▸VER	Red Bull	10.5% ± 0.4%	35.6%	93.7%	5.16	1
5	▸NOR	McLaren	9.7% ± 0.4%	32.7%	91.7%	5.5	9
6	▸LEC	Ferrari	8% ± 0.4%	28.4%	90.4%	5.84	4
7	▸HAD	Red Bull	3.6% ± 0.2%	16.2%	83.2%	7.16	5
8	▸PIA	McLaren	3.4% ± 0.2%	15.2%	79.6%	7.51	6
9	▸LAW	RB F1 Team	1.3% ± 0.1%	6.3%	59.5%	9.69	7
10	▸GAS	Alpine F1 Team	1% ± 0.2%	5.3%	56.9%	9.94	16
11	▸LIN	RB F1 Team	0.3% ± 0.1%	1.7%	34%	12.19	10
12	▸BOR	Audi	0.2% ± 0.1%	1.3%	27.8%	12.91	18
13	▸COL	Alpine F1 Team	0.2% ± 0.1%	1.4%	29.8%	12.64	13
14	▸SAI	Williams	0.1%	0.5%	14.2%	14.91	17
15	▸BEA	Haas F1 Team	0.1%	0.6%	18.6%	14	14
16	▸ALO	Aston Martin	0%	0.2%	7%	16.6	8
17	▸STR	Aston Martin	0%	0.1%	2.9%	18.12	12
18	▸HUL	Audi	0%	0.2%	9.3%	15.78	11
19	▸OCO	Haas F1 Team	0%	0.2%	7.3%	16.19	15
20	▸ALB	Williams	0%	0.1%	3.3%	17.62	21
21	▸BOT	Cadillac F1 Team	0%	0%	1.1%	19.35	22
22	▸PER	Cadillac F1 Team	0%	0%	0.9%	19.49	19

Methodology

Each driver's simulated race pace is sampled from a distribution weighted by qualifying pace percentile, top-speed ranking, season championship standings, historical finishing position at this circuit, tire degradation, and pit-stop delta. The simulation runs 100,000 times, with 10% of runs treated as a wet-race scenario (estimated from this circuit's own rainfall history).

This circuit's weighting — Bahrain Grand Prix: overtaking difficulty Medium, downforce dependency Medium, tire severity High. Higher overtaking difficulty shifts weight toward grid position; lower downforce dependency shifts weight toward straight-line top speed; higher tire severity shifts weight toward tire-degradation management. See circuit_profiles.py for every circuit's numbers and how they translate into weights.