R03 — JAPANESE GRAND PRIX
Hamilton podium at Suzuka
7%
7% chance for Hamilton to finish on the podium at Suzuka. P4 in Australia, P3 in China (first Ferrari podium). Improving race by race.
7%Hamilton
25%7%40%
7% [25%–40%] (95% CI)
01 / KEY FACTORS
Impact by factor
China P3 (first Ferrari podium)
+7.8%
Experience at Suzuka (7x WDC)
+6.2%
Mercedes-Ferrari gap persists
-4.8%
Ferrari P2 constructors (67 pts)
+4.5%
Improving Ferrari adaptation
+3.5%
Suzuka favours downforce (Mercedes)
-3.2%
Leclerc intra-team battle
-1.8%
Impact total+12.2%
02 / MONTE CARLO SIMULATION
Distribution and quantitative analysis
10,000 simulations Monte Carlo
Position Distribution
10,000 simulationsDistribution Statistics
N Simulations10k paths
ExpectedP3.3
MedianP3
ModeP2
Std Dev2.13
Skewness+1.93 →
VaR 95%P8
CVaR 95%P9.7
Prob(P1)12.0%
Prob(Podium)66.2%
Prob(Points)98.8%
Prob(DNF)3.0%
Convergence
Scenario Analysis — Hamilton
| Scenario | Position | Prob. | Conditions |
|---|---|---|---|
| Best case (P5) | P1 | 12% | Rain at Shanghai, Hamilton mastery, overtakes on-track from P3-P4 grid |
| Optimistic (P25) | P3 | 25% | Qualifies P4, benefits from safety car restart to gain podium position |
| Base case (P50) | P5 | 30% | P5-P6 qualifying, consistent race pace, best of the rest behind Mercedes |
| Conservative (P75) | P7 | 14% | Struggles with Ferrari setup, loses positions to McLaren duo in race |
| Worst case (P95) | P11 | 5% | Qualifying error, first-corner contact, poor tyre strategy call |
Sensitivity Analysis
03 / FEATURE ANALYSIS
Variable analysis
Base value5.0%
Output7%
5.0%
7%
circuit_history_wins+10.5%
driver_experience+5.8%
circuit_knowledge+4.2%
constructor_ranking+3.2%
team_adaptation-5.4%
car_delta-4.1%
teammate_form-2.3%
Feature importance
circuit_history_wins
0.168
driver_experience
0.135
team_adaptation
0.118
car_delta
0.105
circuit_knowledge
0.092
constructor_ranking
0.078
teammate_form
0.065
qualifying_pace
0.055
race_pace_trend
0.042
pit_strategy
0.032
Feature correlations
form_score
constructor
quali_pace
circuit_hist
tyre_deg
reliability
form_score
constructor
quali_pace
circuit_hist
tyre_deg
reliability
-1.0
0
+1.0
04 / MODEL VALIDATION
Model performance
Model performance
Accuracy0.720+0.220 vs baseline
Brier Score0.041-0.006 vs baseline
Log Loss1.945
AUC-ROC0.798
Calibration curve
Confusion matrix
Predicted vs Actual72% accuracy
Track characteristics
Accuracy
72%
across 127 race winner predictions
Average Brier score
0.041
probability calibration
Last correct
Abu Dhabi 2025
Abu Dhabi 2025 — Hamilton P4
05 / CIRCUIT ANALYSIS
Circuit factors
Suzuka history
Last 5 races
2017
P1
2019
P1
2023
P5
2024
P2
2025
P3
Practice pace
Gap to leader (sec)
RUS
REF
LEC
+0.5s
HAM
+0.6s
NOR
+0.3s
Tyre degradation
Lap time, laps 1-20
Lap 1Cliff ~L12Lap 20
Lap time distribution
Hamilton
Leclerc
Russell
94.0s95.0s96.0s97.0s
06 / COMPARISON
Hamilton vs Leclerc vs Russell
Hamilton
Leclerc
Russell
Circuit history
98
72
75
Experience
98
78
72
Race pace
82
86
90
Car adaptation
60
92
95
Recent form
68
80
95
Head-to-head
| Driver | Quali avg | Race pace | Finishes | Podiums | DNFs |
|---|---|---|---|---|---|
| Hamilton | 3.2 | 1:34.5 | 17 | 10 | 1 |
| Leclerc | 4.1 | 1:34.8 | 4 | 1 | 0 |
| Verstappen | 2.8 | 1:34.3 | 5 | 2 | 0 |
07 / EVOLUTION & DATA
Probability over time
Training Data Sample4 rows x 8 cols