Skip to main content
F1

Monaco Grand Prix

Round 6 · 2026
Monte Carlo
v 0.3.004 Jun 2026, 22:35 UTC
Based onHistoryConstructor formRegulations
Max Verstappen is the model's pick at 38.9% (80% CI 38.1–39.7%) for Monaco Grand Prix.

Top 10 drivers

bars are win / podium / points probabilitiesWeekend analytics →
  1. 1
    Max Verstappen
    VERMax Verstappen
    Red Bull RacingRed Bull RacingLOW
    WIN
    38.9%
    POD
    77.4%
    PTS
    92.5%
    Why · 3 factors
    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 1.00 (1.0 = top of grid). Familiarity discount ×0.85.

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.97, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.96 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.

  2. 2
    George Russell
    RUSGeorge Russell
    MercedesMercedesLOW
    WIN
    18.7%
    POD
    57.8%
    PTS
    88.6%
    Why · 5 factors
    • Constructor recent formw 0.54

      Team points trend score 0.81 across the last 5 races.

    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.64 (1.0 = top of grid).

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.82, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.97 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.

    • DNF riskw 0.12

      Per-race DNF probability ≈ 11.9% (team × circuit).

  3. 3
    Kimi Antonelli
    ANTKimi Antonelli
    MercedesMercedesLOW
    WIN
    10.0%
    POD
    35.5%
    PTS
    86.1%
    Why · 5 factors
    • Constructor recent formw 0.54

      Team points trend score 0.81 across the last 5 races.

    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.26 (1.0 = top of grid).

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.89, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.97 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.

    • DNF riskw 0.12

      Per-race DNF probability ≈ 11.9% (team × circuit).

  4. 4
    Charles Leclerc
    LECCharles Leclerc
    FerrariFerrariLOW
    WIN
    6.6%
    POD
    23.9%
    PTS
    79.3%
    Why · 5 factors
    • Constructor recent formw 0.54

      Team points trend score 0.53 across the last 5 races.

    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.65 (1.0 = top of grid).

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.58, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.66 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 ≈ 14.7% (team × circuit).

  5. 5
    Pierre Gasly
    GASPierre Gasly
    AlpineAlpineLOW
    WIN
    5.3%
    POD
    20.4%
    PTS
    64.4%
    Why · 4 factors
    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.60 (1.0 = top of grid).

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.38, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.44 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 ≈ 31.2% (team × circuit).

  6. 6
    Lewis Hamilton
    HAMLewis Hamilton
    FerrariFerrariLOW
    WIN
    3.4%
    POD
    12.8%
    PTS
    67.4%
    Why · 5 factors
    • Constructor recent formw 0.54

      Team points trend score 0.53 across the last 5 races.

    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.23 (1.0 = top of grid).

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.79, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.66 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 ≈ 14.7% (team × circuit).

  7. 7
    Nico Hulkenberg
    HULNico Hulkenberg
    Kick SauberKick SauberLOW
    WIN
    2.7%
    POD
    10.6%
    PTS
    65.4%
    Why · 3 factors
    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.46 (1.0 = top of grid). Familiarity discount ×0.85.

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.53, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.56 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.

  8. 8
    Isack Hadjar
    HADIsack Hadjar
    Racing BullsRacing BullsLOW
    WIN
    2.2%
    POD
    9.2%
    PTS
    59.1%
    Why · 3 factors
    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.46 (1.0 = top of grid). Familiarity discount ×0.85.

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.21, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.32 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.

  9. 9
    Lando Norris
    NORLando Norris
    McLarenMcLarenLOW
    WIN
    2.2%
    POD
    8.6%
    PTS
    52.1%
    Why · 5 factors
    • Constructor recent formw 0.54

      Team points trend score 0.33 across the last 5 races.

    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.61 (1.0 = top of grid).

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.39, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.84 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 ≈ 28.6% (team × circuit).

  10. 10
    Gabriel Bortoleto
    BORGabriel Bortoleto
    Kick SauberKick SauberLOW
    WIN
    2.0%
    POD
    7.6%
    PTS
    55.6%
    Why · 3 factors
    • Driver skill (Elo)w 0.27

      Teammate-only Elo skill score 0.42 (1.0 = top of grid). Familiarity discount ×0.85.

    • Track history (time-weighted)w 0.03

      Recency-weighted finish score 0.32, 5-year window, 12-month half-life, reg-discounted ×0.24.

    • Chassis at this circuitw 0.16

      Constructor-lineage best-finish score 0.56 at this circuit across the last 5 seasons. Driver-agnostic — captures chassis-DNA fit independent of who drove.

Most-likely podium combinations

approximate · 1st-2nd-3rd
  1. 1
    P1VER·P2RUS·P3ANT
    5.73%
  2. 2
    P1VER·P2ANT·P3RUS
    4.62%
  3. 3
    P1VER·P2RUS·P3LEC
    3.86%
  4. 4
    P1VER·P2RUS·P3GAS
    3.29%
  5. 5
    P1RUS·P2VER·P3ANT
    3.26%
  6. 6
    P1VER·P2LEC·P3RUS
    2.82%
  7. 7
    P1VER·P2GAS·P3RUS
    2.35%
  8. 8
    P1RUS·P2ANT·P3VER
    2.25%
  9. 9
    P1RUS·P2VER·P3LEC
    2.20%
  10. 10
    P1VER·P2RUS·P3HAM
    2.07%

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.