R03 — JAPANESE GRAND PRIX
McLaren double points finish in Japan
41%
Our model estimates a 41% probability for this prediction, based on the analysis of multiple factors and Monte Carlo simulations.
41%McLaren double points finish in Japan
38%41%52%
41% [38%–52%] (95% CI)
01 / KEY FACTORS
Impact by factor
Recent form
+6.1%
Constructor advantage
+4.8%
Historical record
+3.5%
Variance
-2.5%
Conditions
-1.8%
Impact total+10.1%
02 / MONTE CARLO SIMULATION
Distribution and quantitative analysis
10,000 simulations Monte Carlo
Position Distribution
10,000 simulationsDistribution Statistics
N Simulations10k paths
ExpectedP2.5
MedianP2
ModeP1
Std Dev2.05
Skewness+2.28 →
VaR 95%P7
CVaR 95%P8.7
Prob(P1)45.0%
Prob(Podium)78.8%
Prob(Points)99.2%
Prob(DNF)3.0%
Convergence
Scenario Analysis — McLaren double points finish in Japan
| Scenario | Position | Prob. | Conditions |
|---|---|---|---|
| Best case (P5) | P1 | 45% | Clean qualifying, optimal tyre strategy, no safety car disruption |
| Optimistic (P25) | P2 | 32% | Strong qualifying, competitive race pace, favourable pit window |
| Base case (P50) | P1 | 25% | Average qualifying, standard strategy, representative race pace |
| Conservative (P75) | P2 | 14% | Suboptimal qualifying, traffic in DRS zones, one extra pit stop |
| Worst case (P95) | P6 | 5% | Safety car at wrong time, poor start, high tyre degradation |
Sensitivity Analysis
03 / FEATURE ANALYSIS
Variable analysis
Base value5.0%
Output41%
5.0%
41%
primary_factor+6.1%
constructor_rank+4.8%
historical_data+3.5%
model_uncertainty-2.5%
external_conditions-1.8%
Feature importance
primary_factor
0.155
constructor_rank
0.132
historical_data
0.115
recent_form
0.098
external_conditions
0.082
model_uncertainty
0.068
reliability
0.055
teammate_delta
0.042
strategy_factor
0.035
weather
0.025
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
Accuracy0.650+0.170 vs baseline
Brier Score0.041-0.006 vs baseline
Log Loss0.750
AUC-ROC0.795
Calibration curve
Confusion matrix
Predicted vs Actual65% accuracy
Track characteristics
Accuracy
65%
across 127 race winner predictions
Average Brier score
0.041
probability calibration
Last correct
Australia R1
Australia R1
05 / CIRCUIT ANALYSIS
Circuit factors
Suzuka history
Last 3 races
2023
P3
2024
P2
2025
P4
Practice pace
Gap to leader (sec)
RUS
REF
NOR
+0.3s
LEC
+0.5s
Tyre degradation
Lap time, laps 1-20
Lap 1Cliff ~L12Lap 20
06 / EVOLUTION & DATA
Probability over time
Training Data Sample4 rows x 5 cols