Skip to main content
F1

Canadian Grand Prix

Round 5 · 2026
Montréal
v 0.3.008 Jun 2026, 01:27 UTC
Based onQualifyingPracticeHistoryConstructor formWeatherRegulations
Max Verstappen is the model's pick at 27.5% (80% CI 26.7–28.3%) for Canadian Grand Prix.

Top 10 drivers

bars are win / podium / points probabilitiesWeekend analytics →
  1. 1Max Verstappen
    VERMax Verstappen
    Red Bull RacingRed Bull RacingHIGH
    WIN
    27.5%
    POD
    63.3%
    PTS
    84.3%
    Why · 6 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.91 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 1.00 (1.0 = fastest median stint).

    • Driver skill (Elo)w 0.09

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

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.97, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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.

    • DNF riskw 0.15

      Per-race DNF probability ≈ 15.0% (team × circuit).

  2. 2George Russell
    RUSGeorge Russell
    MercedesMercedesHIGH
    WIN
    20.3%
    POD
    52.7%
    PTS
    76.0%
    Why · 7 factors
    • Qualifying pacew 0.54

      Quali-pace score 1.00 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.71 (1.0 = fastest median stint).

    • Constructor recent formw 0.17

      Team points trend score 0.89 across the last 5 races.

    • Driver skill (Elo)w 0.09

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

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.82, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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 0.20

      Per-race DNF probability ≈ 23.9% (team × circuit).

  3. 3Isack Hadjar
    HADIsack Hadjar
    Red Bull RacingRed Bull RacingHIGH
    WIN
    12.7%
    POD
    40.0%
    PTS
    84.5%
    Why · 6 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.90 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.97 (1.0 = fastest median stint).

    • Driver skill (Elo)w 0.09

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

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.21, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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.

    • DNF riskw 0.15

      Per-race DNF probability ≈ 15.0% (team × circuit).

  4. 4Arvid Lindblad
    LINArvid Lindblad
    Racing BullsRacing BullsHIGH
    WIN
    8.8%
    POD
    31.1%
    PTS
    84.4%
    Why · 5 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.81 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.98 (1.0 = fastest median stint).

    • Driver skill (Elo)w 0.09

      Teammate-only Elo skill score 0.50 (1.0 = top of grid). Rain-modulated. Familiarity discount ×0.85.

    • Chassis at this circuitw 0.05

      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.

    • DNF riskw 0.15

      Per-race DNF probability ≈ 15.0% (team × circuit).

  5. 5Kimi Antonelli
    ANTKimi Antonelli
    MercedesMercedesHIGH
    WIN
    6.5%
    POD
    23.0%
    PTS
    75.4%
    Why · 7 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.98 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.13 (1.0 = fastest median stint).

    • Constructor recent formw 0.17

      Team points trend score 0.89 across the last 5 races.

    • Driver skill (Elo)w 0.09

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

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.89, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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 0.20

      Per-race DNF probability ≈ 23.9% (team × circuit).

  6. 6Lewis Hamilton
    HAMLewis Hamilton
    FerrariFerrariHIGH
    WIN
    5.8%
    POD
    20.7%
    PTS
    69.8%
    Why · 7 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.92 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.90 (1.0 = fastest median stint).

    • Constructor recent formw 0.17

      Team points trend score 0.47 across the last 5 races.

    • Driver skill (Elo)w 0.09

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

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.79, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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 0.20

      Per-race DNF probability ≈ 29.4% (team × circuit).

  7. 7Oscar Piastri
    PIAOscar Piastri
    McLarenMcLarenHIGH
    WIN
    4.2%
    POD
    14.7%
    PTS
    57.5%
    Why · 7 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.95 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.58 (1.0 = fastest median stint).

    • Constructor recent formw 0.17

      Team points trend score 0.46 across the last 5 races.

    • Driver skill (Elo)w 0.09

      Teammate-only Elo skill score 0.44 (1.0 = top of grid). Rain-modulated.

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.77, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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 ≈ 40.0% (team × circuit).

  8. 8Lando Norris
    NORLando Norris
    McLarenMcLarenHIGH
    WIN
    4.1%
    POD
    16.4%
    PTS
    58.0%
    Why · 7 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.96 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.51 (1.0 = fastest median stint).

    • Constructor recent formw 0.17

      Team points trend score 0.46 across the last 5 races.

    • Driver skill (Elo)w 0.09

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

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.39, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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 ≈ 40.0% (team × circuit).

  9. 9Charles Leclerc
    LECCharles Leclerc
    FerrariFerrariHIGH
    WIN
    3.1%
    POD
    10.1%
    PTS
    64.6%
    Why · 7 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.89 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.18 (1.0 = fastest median stint).

    • Constructor recent formw 0.17

      Team points trend score 0.47 across the last 5 races.

    • Driver skill (Elo)w 0.09

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

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.58, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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 0.20

      Per-race DNF probability ≈ 29.4% (team × circuit).

  10. 10Franco Colapinto
    COLFranco Colapinto
    AlpineAlpineHIGH
    WIN
    2.4%
    POD
    8.8%
    PTS
    55.4%
    Why · 6 factors
    • Qualifying pacew 0.54

      Quali-pace score 0.70 (1.0 = pole).

    • Practice long-run pacew 0.13

      Long-run score 0.88 (1.0 = fastest median stint).

    • Driver skill (Elo)w 0.09

      Teammate-only Elo skill score 0.47 (1.0 = top of grid). Rain-modulated.

    • Track history (time-weighted)w 0.02

      Recency-weighted finish score 0.37, 5-year window, 12-month half-life, reg-discounted ×0.36.

    • Chassis at this circuitw 0.05

      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 ≈ 40.0% (team × circuit).

Most-likely podium combinations

approximate · 1st-2nd-3rd
  1. 1
    P1VER·P2RUS·P3HAD
    3.01%
  2. 2
    P1VER·P2HAD·P3RUS
    2.71%
  3. 3
    P1RUS·P2VER·P3HAD
    2.51%
  4. 4
    P1VER·P2RUS·P3LIN
    2.34%
  5. 5
    P1RUS·P2HAD·P3VER
    2.09%
  6. 6
    P1VER·P2LIN·P3RUS
    1.97%
  7. 7
    P1RUS·P2VER·P3LIN
    1.95%
  8. 8
    P1HAD·P2VER·P3RUS
    1.74%
  9. 9
    P1VER·P2RUS·P3ANT
    1.73%
  10. 10
    P1HAD·P2RUS·P3VER
    1.61%

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.