Japanese Grand Prix

Round 3 · 2026

Suzuka

v 0.3.008 Jun 2026, 01:02 UTC

Based onQualifyingPracticeHistoryConstructor formWeatherRegulations

George Russell is the model's pick at 26.4% (80% CI 25.6–27.2%) for Japanese Grand Prix.

Top 10 drivers

bars are win / podium / points probabilitiesWeekend analytics →

1
RUSGeorge Russell
MercedesHIGH
WIN
26.4%
POD
51.2%
PTS
59.6%
Why · 7 factors
- Qualifying pacew 0.55
  Quali-pace score 0.93 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 1.00 (1.0 = fastest median stint).
- Constructor recent formw 0.17
  Team points trend score 0.98 across the last 5 races.
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.64 (1.0 = top of grid).
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.72, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.77 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.20
  Per-race DNF probability ≈ 40.0% (team × circuit).
2
ANTKimi Antonelli
MercedesHIGH
WIN
17.5%
POD
45.0%
PTS
59.9%
Why · 7 factors
- Qualifying pacew 0.55
  Quali-pace score 1.00 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.60 (1.0 = fastest median stint).
- Constructor recent formw 0.17
  Team points trend score 0.98 across the last 5 races.
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.26 (1.0 = top of grid).
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.74, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.77 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.20
  Per-race DNF probability ≈ 40.0% (team × circuit).
3
LECCharles Leclerc
FerrariHIGH
WIN
14.4%
POD
41.9%
PTS
70.6%
Why · 7 factors
- Qualifying pacew 0.55
  Quali-pace score 0.87 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.97 (1.0 = fastest median stint).
- Constructor recent formw 0.17
  Team points trend score 0.61 across the last 5 races.
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.65 (1.0 = top of grid).
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.85, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.86 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.20
  Per-race DNF probability ≈ 29.4% (team × circuit).
4
VERMax Verstappen
Red Bull RacingHIGH
WIN
7.0%
POD
25.2%
PTS
82.6%
Why · 6 factors
- Qualifying pacew 0.55
  Quali-pace score 0.64 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.95 (1.0 = fastest median stint).
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 1.00 (1.0 = top of grid). Familiarity discount ×0.85.
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 1.00, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 1.00 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.15
  Per-race DNF probability ≈ 15.0% (team × circuit).
5
HAMLewis Hamilton
FerrariHIGH
WIN
6.1%
POD
22.2%
PTS
68.8%
Why · 7 factors
- Qualifying pacew 0.55
  Quali-pace score 0.81 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.84 (1.0 = fastest median stint).
- Constructor recent formw 0.17
  Team points trend score 0.61 across the last 5 races.
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.23 (1.0 = top of grid).
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.70, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.86 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.20
  Per-race DNF probability ≈ 29.4% (team × circuit).
6
GASPierre Gasly
AlpineHIGH
WIN
5.6%
POD
20.6%
PTS
59.0%
Why · 6 factors
- Qualifying pacew 0.55
  Quali-pace score 0.78 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.67 (1.0 = fastest median stint).
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.60 (1.0 = top of grid).
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.34, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.39 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.20
  Per-race DNF probability ≈ 40.0% (team × circuit).
7
PIAOscar Piastri
McLarenHIGH
WIN
5.6%
POD
18.8%
PTS
58.9%
Why · 7 factors
- Qualifying pacew 0.55
  Quali-pace score 0.91 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.97 (1.0 = fastest median stint).
- Constructor recent formw 0.17
  Team points trend score 0.08 across the last 5 races.
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.44 (1.0 = top of grid).
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.82, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.89 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.20
  Per-race DNF probability ≈ 40.0% (team × circuit).
8
HADIsack Hadjar
Red Bull RacingHIGH
WIN
4.6%
POD
18.0%
PTS
79.7%
Why · 6 factors
- Qualifying pacew 0.55
  Quali-pace score 0.71 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.74 (1.0 = fastest median stint).
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.46 (1.0 = top of grid). Familiarity discount ×0.85.
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.63, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 1.00 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.15
  Per-race DNF probability ≈ 15.0% (team × circuit).
9
LINArvid Lindblad
Racing BullsHIGH
WIN
3.2%
POD
13.8%
PTS
75.0%
Why · 5 factors
- Qualifying pacew 0.55
  Quali-pace score 0.68 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.65 (1.0 = fastest median stint).
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.50 (1.0 = top of grid). Familiarity discount ×0.85.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.58 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.15
  Per-race DNF probability ≈ 15.0% (team × circuit).
10
NORLando Norris
McLarenHIGH
WIN
2.7%
POD
11.1%
PTS
54.6%
Why · 7 factors
- Qualifying pacew 0.55
  Quali-pace score 0.85 (1.0 = pole).
- Practice long-run pacew 0.13
  Long-run score 0.73 (1.0 = fastest median stint).
- Constructor recent formw 0.17
  Team points trend score 0.08 across the last 5 races.
- Driver skill (Elo)w 0.09
  Teammate-only Elo skill score 0.61 (1.0 = top of grid).
- Track history (time-weighted)w 0.00
  Recency-weighted finish score 0.86, 5-year window, 12-month half-life, reg-discounted ×0.07.
- Chassis at this circuitw 0.05
  Constructor-lineage best-finish score 0.89 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.
- DNF riskw 0.20
  Per-race DNF probability ≈ 40.0% (team × circuit).

Most-likely podium combinations

approximate · 1st-2nd-3rd

1
P1RUS·P2ANT·P3LEC
2.92%
2
P1RUS·P2LEC·P3ANT
2.84%
3
P1ANT·P2RUS·P3LEC
2.12%
4
P1ANT·P2LEC·P3RUS
1.96%
5
P1LEC·P2RUS·P3ANT
1.79%
6
P1RUS·P2ANT·P3VER
1.76%
7
P1LEC·P2ANT·P3RUS
1.70%
8
P1RUS·P2LEC·P3VER
1.59%
9
P1RUS·P2ANT·P3HAM
1.55%
10
P1RUS·P2VER·P3ANT
1.49%

Methodology

Probabilities come from a layered ensemble: historical base rates per circuit, current constructor form (rolling 6 races), qualifying outcome, and a weather adjustment. Confidence intervals are 80% credible bands from the win-share posterior. See 0.3.0 for the active weights.