Las Vegas Grand Prix
Round 20 · 2026- 1
VERMax Verstappen
Red Bull RacingLOWWIN35.5%POD69.7%PTS84.8%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 1.00 (1.0 = top of grid). Familiarity discount ×0.85.
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.93, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.95 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).
- 2
RUSGeorge Russell
MercedesLOWWIN10.6%POD35.2%PTS75.9%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.64 (1.0 = top of grid).
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.86, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.94 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 ≈ 23.9% (team × circuit).
- 3
LECCharles Leclerc
FerrariLOWWIN10.5%POD31.1%PTS68.6%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.65 (1.0 = top of grid).
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.84, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
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
GASPierre Gasly
AlpineLOWWIN4.8%POD17.3%PTS52.7%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.60 (1.0 = top of grid).
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.28, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.36 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).
- 5
NORLando Norris
McLarenLOWWIN4.7%POD15.8%PTS53.7%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.61 (1.0 = top of grid).
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.28, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.26 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).
- 6
ALOFernando Alonso
Aston MartinLOWWIN4.2%POD16.7%PTS66.8%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.57 (1.0 = top of grid). Familiarity discount ×0.85.
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.51, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.50 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).
- 7
SAICarlos Sainz
WilliamsLOWWIN3.7%POD12.9%PTS50.3%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.50 (1.0 = top of grid).
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.81, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.65 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
ALBAlexander Albon
WilliamsLOWWIN3.3%POD12.0%PTS49.5%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.55 (1.0 = top of grid).
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.19, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.65 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).
- 9
HADIsack Hadjar
Racing BullsLOWWIN3.0%POD11.5%PTS57.1%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.46 (1.0 = top of grid). Familiarity discount ×0.85.
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.74, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.67 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
HULNico Hulkenberg
Kick SauberLOWWIN2.9%POD9.8%PTS53.3%Why · 4 factors- Driver skill (Elo)w 0.58
Teammate-only Elo skill score 0.46 (1.0 = top of grid). Familiarity discount ×0.85.
- Track history (time-weighted)w 0.07
Recency-weighted finish score 0.58, 5-year window, 12-month half-life, reg-discounted ×0.24.
- Chassis at this circuitw 0.35
Constructor-lineage best-finish score 0.60 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).
Most-likely podium combinations
approximate · 1st-2nd-3rd- 1P1VER·P2RUS·P3LEC4.14%
- 2P1VER·P2LEC·P3RUS3.94%
- 3P1VER·P2RUS·P3GAS2.30%
- 4P1VER·P2RUS·P3ALO2.22%
- 5P1VER·P2RUS·P3NOR2.10%
- 6P1LEC·P2VER·P3RUS1.96%
- 7P1VER·P2LEC·P3GAS1.94%
- 8P1RUS·P2VER·P3LEC1.89%
- 9P1VER·P2GAS·P3RUS1.88%
- 10P1VER·P2LEC·P3ALO1.87%
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.