ποΈ Nina's F1 Predictions: 2026 Japanese Grand Prix (Round 3)ΒΆ
Suzuka Circuit β March 27-29, 2026ΒΆ
Model version: v1.0+Q (Post-qualifying, HIGH confidence)
Data: 72 races (2023-2026), 1,442 results + lap telemetry + weather
Last updated: March 28, 2026
What This IsΒΆ
A machine learning model that predicts Formula 1 race results and optimizes F1 Fantasy lineups. The model analyzes 24 different factors β the same kinds of data a race engineer would consider when building a race strategy β and runs 10,000 simulated races to estimate each driver's probability of finishing on the podium, in the points, or beating their teammate.
The 2026 season introduced massive regulation changes β new power units (50/50 electric/ICE), active aerodynamics that replace DRS, smaller and lighter cars, and 100% sustainable fuels. The entire competitive order has been reshuffled. Mercedes went from struggling to dominant. McLaren went from champions to backmarkers. Red Bull went from winning everything to Tier 4. This model accounts for that by weighting 2026 data 10x more heavily than historical data.
The 24 FeaturesΒΆ
The model looks at every driver through these lenses:
Car Performance (2026 only):
- ποΈ Constructor pace β average finish position by team this season
- β‘ Straight-line speed β speed trap data, critical for Suzuka's 1.2km back straight
Driver Skill (all years, car-independent):
- π€ Teammate delta β how much better/worse than their teammate
- π Recent form β rolling average finish position
- π First lap performance β who consistently gains/loses positions at the start
- π Season momentum β are they trending up or down? (uses current team only for drivers who switched)
- π― Positions gained per race β racecraft and overtaking ability
- β±οΈ Qualifying vs race pace β "Saturday car" vs "Sunday car"
Tire & Strategy:
- π Tire degradation rate β who's gentle on tires (longer stints, fewer stops)
- π§ Pit stop frequency β driver and team pit stop patterns
Track-Specific (Suzuka):
- πΎ Sector 1 pace β technical corners through The Esses
- πΎ Sector 2 pace β power sector (back straight + Degner curves)
- πΎ Sector 3 pace β mixed character (Spoon, 130R, chicane)
- π Track experience β how many times they've raced here
Conditions & Context:
- π‘οΈ Weather β temperature, humidity, rainfall
- π§οΈ Wet-weather skill β positions gained in historical rain races
- π‘ Safety car β 33% probability at Suzuka, wired into simulations
- π Team changed β 9 of 22 drivers switched teams for 2026 (adds uncertainty)
- π Consistency β lap time variation (lower = more reliable)
- ποΈ DNF rate β reliability factor
- π¬ 2026 flag β tells the model this is a regulation-change year
How It WorksΒΆ
- Two-model approach: Car pace comes ONLY from 2026 data. Driver skill uses all 72 races but measures performance relative to the car β so it transfers across regulation changes.
- XGBoost machine learning β the gold standard algorithm for F1 prediction (77-82% winner accuracy in published research). It automatically learns which features matter most.
- 10,000 simulated races β each simulation adds realistic randomness (safety cars, incidents, mechanical failures) calibrated to the model's actual prediction error. This produces probabilities, not just a single prediction.
- Honest validation β we use leave-one-out cross-validation on 2026 data. The accuracy we report (MAE 2.39 positions) is real β the model never saw the data it was tested on.
1. New Feature Deep DiveΒΆ
Four charts showing what makes each driver unique β their first-lap performance (who gains positions at the start), how gently they treat their tires, whether they're trending up or down this season, and how fast their car is on the straights. These differences matter at Suzuka.
2. Suzuka Sector AnalysisΒΆ
Suzuka has three distinct sectors that test different car characteristics:
- S1 (Turns 1-9): High-speed technical corners through 'The Esses' β rewards downforce and driver confidence
- S2 (Back straight + Degner): Pure power β the 1.2km straight is where active aero overtakes happen
- S3 (Spoon, 130R, chicane): Mixed character β late braking and car balance
=========================================================================== πΎ SUZUKA SECTOR PROFILES β Who's Fast Where? =========================================================================== S1: Technical (The Esses) | S2: Power (Back Straight) | S3: Mixed Driver S1 (tech) S2 (power) S3 (mixed) Best Sector ---------------------------------------------------------------------- George Russell -0.191s -0.067s -0.010s S1 Kimi Antonelli -2.128s -1.042s -0.576s S1 Charles Leclerc -0.210s -0.227s -0.077s S2 Lewis Hamilton -0.231s -0.121s -0.057s S1 Lando Norris -0.503s -0.354s -0.079s S1 Max Verstappen -0.584s -0.487s -0.154s S1 Oliver Bearman -1.925s -0.768s -0.379s S1 Arvid Lindblad no data no data no data No Suzuka data Gabriel Bortoleto -1.586s -0.641s -0.396s S1 Pierre Gasly +0.466s +0.270s +0.138s S3 Esteban Ocon +0.575s +0.374s +0.174s S3 Alexander Albon +0.005s +0.208s +0.109s S1 Liam Lawson -0.025s +0.119s +0.037s S1 Franco Colapinto no data no data no data No Suzuka data Carlos Sainz -0.098s -0.097s -0.099s S3 Sergio Perez +0.892s +0.674s +0.322s S3 Lance Stroll +0.283s +0.226s +0.192s S3 Fernando Alonso -0.093s -0.079s +0.061s S1 Valtteri Bottas +1.903s +0.675s +0.233s S3 Isack Hadjar -1.995s -0.943s -0.475s S1 Oscar Piastri -0.377s -0.241s -0.006s S1 Nico Hulkenberg +0.215s +0.178s +0.020s S3
3. Car Pace (2026 Only)ΒΆ
The most important factor in F1: which car are you driving? This section uses ONLY 2026 results because the new regulations completely reshuffled the pecking order. Mercedes went from struggling to dominant. McLaren went from champions to backmarkers. Historical speed means nothing when the cars are fundamentally different.
====================================================================== ποΈ CONSTRUCTOR PACE (2026 Only) ====================================================================== Team Avg Fin Speed Tier -------------------------------------------------- Mercedes P 1.5 298 Tier 1 Ferrari P 3.5 296 Tier 2 Haas F1 Team P 9.2 291 Tier 3 Alpine P 10.0 295 Tier 3 Racing Bulls P 10.0 292 Tier 3 Red Bull Racing P 12.5 298 Tier 4 Williams P 14.5 290 Tier 4 Audi P 15.8 295 Tier 4 Cadillac P 15.8 285 Tier 4 McLaren P 16.2 279 Tier 5 Aston Martin P 17.5 282 Tier 5
3b. FP1 Practice Data (Live)ΒΆ
Actual practice session data from Suzuka, pulled via FastF1. This updates car pace and speed estimates with real 2026 Suzuka performance, and provides actual weather conditions for the prediction model.
core INFO Loading data for Japanese Grand Prix - Practice 1 [v3.8.1]
req INFO Using cached data for session_info
req INFO Using cached data for driver_info
core WARNING No result data for this session available on Ergast! (This is expected for recent sessions)
req INFO Using cached data for session_status_data
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core INFO Processing timing data...
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core INFO Finished loading data for 22 drivers: ['1', '3', '5', '6', '10', '11', '12', '16', '18', '23', '27', '30', '31', '34', '41', '43', '44', '55', '63', '77', '81', '87']
================================================================================ π FP1 RESULTS β Suzuka (Live Data) ================================================================================ Pos Driver Team Best Lap Gap Top Spd ------------------------------------------------------------------------ P 1 George Russell Mercedes 1:31.666 FASTEST 285 P 2 Kimi Antonelli Mercedes 1:31.692 +0.026 285 P 3 Lando Norris McLaren 1:31.798 +0.132 281 P 4 Oscar Piastri McLaren 1:31.865 +0.199 297 P 5 Charles Leclerc Ferrari 1:31.955 +0.289 290 P 6 Lewis Hamilton Ferrari 1:32.040 +0.374 284 P 7 Max Verstappen Red Bull Racing 1:32.457 +0.791 290 P 8 Liam Lawson Racing Bulls 1:32.529 +0.863 286 P 9 Esteban Ocon Haas F1 Team 1:32.601 +0.935 281 P10 Arvid Lindblad Racing Bulls 1:32.665 +0.999 297 P11 Gabriel Bortoleto Audi 1:32.759 +1.093 286 P12 Nico Hulkenberg Audi 1:32.798 +1.132 284 P13 Isack Hadjar Red Bull Racing 1:32.803 +1.137 290 P14 Oliver Bearman Haas F1 Team 1:32.900 +1.234 281 P15 Pierre Gasly Alpine 1:32.978 +1.312 291 P16 Franco Colapinto Alpine 1:33.361 +1.695 284 P17 Carlos Sainz Williams 1:33.383 +1.717 294 P18 Alexander Albon Williams 1:33.697 +2.031 281 P19 Sergio Perez Cadillac 1:34.221 +2.555 288 P20 Valtteri Bottas Cadillac 1:34.490 +2.824 293 P21 Lance Stroll Aston Martin 1:35.294 +3.628 277 P22 Jak Crawford Aston Martin 1:36.362 +4.696 269 π BLENDED CAR PACE (60% season + 40% FP1): Team Season FP1 Blended FP1 Spd ------------------------------------------------------- Mercedes P 1.5 P1.5 P 1.5 293 Ferrari P 3.5 P5.5 P 4.3 292 Haas F1 Team P 9.2 P11.5 P 10.2 287 Alpine P 10.0 P15.5 P 12.2 292 Racing Bulls P 10.0 P7.5 P 9.0 292 Red Bull Racing P 12.5 P9.5 P 11.3 295 Williams P 14.5 P17.5 P 15.7 289 Audi P 15.8 P13.5 P 14.8 291 Cadillac P 15.8 P19.5 P 17.2 287 McLaren P 16.2 P3.5 P 11.2 283 Aston Martin P 17.5 P21.5 P 19.1 278 π‘οΈ Actual conditions: 16.4Β°C, 49% humidity, DRY π TIRE STINTS: George Russell HARD(17), SOFT(10) Kimi Antonelli HARD(12), SOFT(14) Lando Norris MEDIUM(11), SOFT(9) Oscar Piastri MEDIUM(17), SOFT(6) Charles Leclerc HARD(10), SOFT(15) Lewis Hamilton HARD(11), SOFT(12) Max Verstappen MEDIUM(21), SOFT(6) Liam Lawson HARD(11), SOFT(16) Esteban Ocon HARD(17), SOFT(6) Arvid Lindblad HARD(19), SOFT(10)
3c. FP2 Practice Data (Live)ΒΆ
Second practice session β longer runs, race fuel simulations, and more representative pace. FP2 gets the highest weight in the blend since it best reflects race conditions.
Updated blend: 30% season + 30% FP1 + 40% FP2
core INFO Loading data for Japanese Grand Prix - Practice 2 [v3.8.1]
req INFO Using cached data for session_info
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core WARNING No result data for this session available on Ergast! (This is expected for recent sessions)
req INFO Using cached data for session_status_data
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core INFO Processing timing data...
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core INFO Finished loading data for 22 drivers: ['1', '3', '5', '6', '10', '11', '12', '14', '16', '18', '23', '27', '30', '31', '41', '43', '44', '55', '63', '77', '81', '87']
================================================================================ π FP2 RESULTS β Suzuka (Live Data) ================================================================================ Pos Driver Team Best Lap Gap Top Spd ------------------------------------------------------------------------ P 1 Oscar Piastri McLaren 1:30.133 FASTEST 292 P 2 Kimi Antonelli Mercedes 1:30.225 +0.092 288 P 3 George Russell Mercedes 1:30.338 +0.205 281 P 4 Lando Norris McLaren 1:30.649 +0.516 289 P 5 Charles Leclerc Ferrari 1:30.846 +0.713 293 P 6 Lewis Hamilton Ferrari 1:30.980 +0.847 280 P 7 Nico Hulkenberg Audi 1:31.441 +1.308 295 P 8 Alexander Albon Williams 1:31.496 +1.363 285 P 9 Oliver Bearman Haas F1 Team 1:31.498 +1.365 295 P10 Max Verstappen Red Bull Racing 1:31.509 +1.376 288 P11 Esteban Ocon Haas F1 Team 1:31.532 +1.399 283 P12 Liam Lawson Racing Bulls 1:31.590 +1.457 289 P13 Carlos Sainz Williams 1:31.608 +1.475 289 P14 Pierre Gasly Alpine 1:31.734 +1.601 291 P15 Isack Hadjar Red Bull Racing 1:31.759 +1.626 284 P16 Gabriel Bortoleto Audi 1:31.933 +1.800 284 P17 Franco Colapinto Alpine 1:32.438 +2.305 288 P18 Valtteri Bottas Cadillac 1:32.615 +2.482 290 P19 Fernando Alonso Aston Martin 1:33.596 +3.463 288 P20 Sergio Perez Cadillac 1:33.689 +3.556 286 P21 Lance Stroll Aston Martin 1:33.951 +3.818 280 π BLENDED CAR PACE (30% season + 30% FP1 + 40% FP2): Team Season FP1 FP2 Blended FP2 Spd -------------------------------------------------------------- Mercedes P 1.5 P1.5 P1.5 P 1.5 289 Ferrari P 3.5 P5.5 P5.5 P 4.9 289 Haas F1 Team P 9.2 P11.5 P7.5 P 9.2 287 Alpine P 10.0 P15.5 P17.5 P 14.6 291 Racing Bulls P 10.0 P7.5 P11.5 P 9.9 291 Red Bull Racing P 12.5 P9.5 P13.5 P 12.0 291 Williams P 14.5 P17.5 P9.5 P 13.4 288 Audi P 15.8 P13.5 P15.5 P 15.0 290 Cadillac P 15.8 P19.5 P19.5 P 18.4 288 McLaren P 16.2 P3.5 P3.5 P 7.3 287 Aston Martin P 17.5 P21.5 P21.5 P 20.3 280 π‘οΈ FP2 conditions: 17.2Β°C, 46% humidity, DRY π FP2 TIRE STINTS: Oscar Piastri MEDIUM(17), SOFT(12) Kimi Antonelli MEDIUM(18), SOFT(10) George Russell MEDIUM(18), SOFT(11) Lando Norris MEDIUM(8), SOFT(9) Charles Leclerc MEDIUM(19), SOFT(9) Lewis Hamilton MEDIUM(18), SOFT(9) Nico Hulkenberg HARD(15), SOFT(12) Alexander Albon MEDIUM(21), SOFT(9) Oliver Bearman MEDIUM(22), SOFT(6) Max Verstappen HARD(26), SOFT(3) π FP2 LONG RUN PACE (5+ consecutive laps on same compound): Driver Team Compound Laps Avg Pace -------------------------------------------------------------------- Lewis Hamilton Ferrari SOFT 4 1:33.617 FASTEST Nico Hulkenberg Audi SOFT 5 1:33.638 +0.022 Kimi Antonelli Mercedes MEDIUM 11 1:34.069 +0.452 George Russell Mercedes MEDIUM 11 1:34.317 +0.701 Charles Leclerc Ferrari MEDIUM 11 1:34.810 +1.194 Oscar Piastri McLaren MEDIUM 12 1:35.018 +1.402 Pierre Gasly Alpine HARD 13 1:35.303 +1.686 Lance Stroll Aston Martin MEDIUM 4 1:35.356 +1.740 Lewis Hamilton Ferrari MEDIUM 9 1:35.540 +1.923 Nico Hulkenberg Audi HARD 10 1:35.612 +1.996 Esteban Ocon Haas F1 Team MEDIUM 15 1:35.726 +2.110 Oliver Bearman Haas F1 Team MEDIUM 14 1:35.747 +2.131 Liam Lawson Racing Bulls MEDIUM 11 1:35.793 +2.176 Alexander Albon Williams MEDIUM 13 1:35.961 +2.344 Franco Colapinto Alpine MEDIUM 13 1:35.991 +2.374 Isack Hadjar Red Bull Racing HARD 13 1:36.068 +2.452 Max Verstappen Red Bull Racing HARD 17 1:36.345 +2.728 Fernando Alonso Aston Martin SOFT 10 1:36.403 +2.787 Carlos Sainz Williams HARD 13 1:36.531 +2.915 Pierre Gasly Alpine SOFT 3 1:37.129 +3.512 Valtteri Bottas Cadillac MEDIUM 14 1:37.271 +3.655 Kimi Antonelli Mercedes SOFT 3 1:37.878 +4.261 Lando Norris McLaren SOFT 4 1:38.010 +4.393 Sergio Perez Cadillac HARD 5 1:38.149 +4.532 Charles Leclerc Ferrari SOFT 5 1:39.002 +5.385 Lando Norris McLaren MEDIUM 4 1:39.216 +5.600 Oscar Piastri McLaren SOFT 6 1:41.791 +8.174 Valtteri Bottas Cadillac SOFT 3 1:42.285 +8.669 George Russell Mercedes SOFT 5 1:42.897 +9.281 Liam Lawson Racing Bulls SOFT 4 1:44.219 +10.602 Lance Stroll Aston Martin SOFT 6 1:46.649 +13.032 Carlos Sainz Williams SOFT 4 1:49.678 +16.061 Gabriel Bortoleto Audi SOFT 5 1:51.852 +18.235 Alexander Albon Williams SOFT 5 1:55.146 +21.529 π FP1 vs FP2 TEAM MOVEMENT: Team FP1 Pos FP2 Pos Change ------------------------------------------------ Mercedes P 1.5 P 1.5 β‘οΈ +0.0 Ferrari P 5.5 P 5.5 β‘οΈ +0.0 McLaren P 3.5 P 3.5 β‘οΈ +0.0 Haas F1 Team P 11.5 P 7.5 β¬οΈ +4.0 Racing Bulls P 7.5 P 11.5 β¬οΈ -4.0 Red Bull Racing P 9.5 P 13.5 β¬οΈ -4.0 Williams P 17.5 P 9.5 β¬οΈ +8.0 Alpine P 15.5 P 17.5 β¬οΈ -2.0 Audi P 13.5 P 15.5 β¬οΈ -2.0 Cadillac P 19.5 P 19.5 β‘οΈ +0.0 Aston Martin P 21.5 P 21.5 β‘οΈ +0.0
3d. FP3 Practice Data (Live)ΒΆ
Final practice before qualifying β same track conditions, teams in full qualifying preparation mode. This session is the closest practice analog to qualifying pace.
core INFO Loading data for Japanese Grand Prix - Practice 3 [v3.8.1]
req INFO Using cached data for session_info
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core WARNING No result data for this session available on Ergast! (This is expected for recent sessions)
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core WARNING Driver 30: Lap timing integrity check failed for 1 lap(s)
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core INFO Finished loading data for 22 drivers: ['1', '3', '5', '6', '10', '11', '12', '14', '16', '18', '23', '27', '30', '31', '41', '43', '44', '55', '63', '77', '81', '87']
================================================================================ π FP3 RESULTS β Suzuka (Live Data) ================================================================================ Pos Driver Team Best Lap Gap Top Spd ------------------------------------------------------------------------ P 1 Kimi Antonelli Mercedes 1:29.362 FASTEST 281 P 2 George Russell Mercedes 1:29.616 +0.254 282 P 3 Charles Leclerc Ferrari 1:30.229 +0.867 286 P 4 Oscar Piastri McLaren 1:30.364 +1.002 282 P 5 Lewis Hamilton Ferrari 1:30.383 +1.021 283 P 6 Lando Norris McLaren 1:30.600 +1.238 279 P 7 Nico Hulkenberg Audi 1:30.658 +1.296 286 P 8 Max Verstappen Red Bull Racing 1:30.910 +1.548 288 P 9 Gabriel Bortoleto Audi 1:31.000 +1.638 288 P10 Pierre Gasly Alpine 1:31.082 +1.720 282 P11 Isack Hadjar Red Bull Racing 1:31.094 +1.732 287 P12 Liam Lawson Racing Bulls 1:31.097 +1.735 287 P13 Arvid Lindblad Racing Bulls 1:31.288 +1.926 285 P14 Esteban Ocon Haas F1 Team 1:31.326 +1.964 285 P15 Oliver Bearman Haas F1 Team 1:31.558 +2.196 281 P16 Alexander Albon Williams 1:31.733 +2.371 285 P17 Franco Colapinto Alpine 1:31.759 +2.397 279 P18 Carlos Sainz Williams 1:31.829 +2.467 309 P19 Valtteri Bottas Cadillac 1:32.503 +3.141 289 P20 Sergio Perez Cadillac 1:32.540 +3.178 283 P21 Lance Stroll Aston Martin 1:33.485 +4.123 276 P22 Fernando Alonso Aston Martin 1:33.529 +4.167 282 π BLENDED CAR PACE (20% season + 20% FP1 + 30% FP2 + 30% FP3): Team Season FP1 FP2 FP3 Blended ----------------------------------------------------------------- Mercedes P 1.5 P1.5 P1.5 P1.5 P 1.5 Ferrari P 3.5 P5.5 P5.5 P3.5 P 4.5 Haas F1 Team P 9.2 P11.5 P7.5 P15.5 P 11.1 Alpine P 10.0 P15.5 P17.5 P13.5 P 14.4 Racing Bulls P 10.0 P7.5 P11.5 P11.5 P 10.4 Red Bull Racing P 12.5 P9.5 P13.5 P9.5 P 11.3 Williams P 14.5 P17.5 P9.5 P17.5 P 14.5 Audi P 15.8 P13.5 P15.5 P7.5 P 12.8 Cadillac P 15.8 P19.5 P19.5 P19.5 P 18.8 McLaren P 16.2 P3.5 P3.5 P5.5 P 6.7 Aston Martin P 17.5 P21.5 P21.5 P21.5 P 20.7 π‘οΈ FP3 conditions: 16.1Β°C, 54% humidity, DRY π FP2 vs FP3 TEAM MOVEMENT: Team FP2 Pos FP3 Pos Change ------------------------------------------------ Mercedes P 1.5 P 1.5 β‘οΈ +0.0 Ferrari P 5.5 P 3.5 β¬οΈ +2.0 McLaren P 3.5 P 5.5 β¬οΈ -2.0 Racing Bulls P 11.5 P 11.5 β‘οΈ +0.0 Haas F1 Team P 7.5 P 15.5 β¬οΈ -8.0 Red Bull Racing P 13.5 P 9.5 β¬οΈ +4.0 Audi P 15.5 P 7.5 β¬οΈ +8.0 Alpine P 17.5 P 13.5 β¬οΈ +4.0 Williams P 9.5 P 17.5 β¬οΈ -8.0 Cadillac P 19.5 P 19.5 β‘οΈ +0.0 Aston Martin P 21.5 P 21.5 β‘οΈ +0.0
3e. Qualifying Data (Live)ΒΆ
The single biggest accuracy upgrade. Grid position is the model's #1 predictor (0.160 importance) and qualifying gives us actual starting positions instead of estimates. This cell also extracts live qualifying sector times, speed traps, and updates car pace with the strongest single-session performance signal of the weekend.
core INFO Loading data for Japanese Grand Prix - Qualifying [v3.8.1]
req INFO Using cached data for session_info
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core INFO Processing timing data...
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req INFO Using cached data for race_control_messages
core INFO Finished loading data for 22 drivers: ['12', '63', '81', '16', '1', '44', '10', '6', '5', '41', '3', '31', '27', '30', '43', '55', '23', '87', '11', '77', '14', '18']
========================================================================================== π QUALIFYING RESULTS β Suzuka (Actual Grid) ========================================================================================== Pos Driver Team Q1 Q2 Q3 Gap ------------------------------------------------------------------------------------- P 1 Kimi Antonelli Mercedes 1:30.035 1:29.048 1:28.778 POLE P 2 George Russell Mercedes 1:29.967 1:29.686 1:29.076 +0.298 P 3 Oscar Piastri McLaren 1:30.200 1:29.451 1:29.132 +0.354 P 4 Charles Leclerc Ferrari 1:29.915 1:29.303 1:29.405 +0.627 P 5 Lando Norris McLaren 1:30.401 1:29.795 1:29.409 +0.631 P 6 Lewis Hamilton Ferrari 1:30.309 1:29.589 1:29.567 +0.789 P 7 Pierre Gasly Alpine 1:30.584 1:29.874 1:29.691 +0.913 P 8 Isack Hadjar Red Bull Racing 1:30.662 1:30.104 1:29.978 +1.200 P 9 Gabriel Bortoleto Audi 1:30.359 1:29.990 1:30.274 +1.496 P10 Arvid Lindblad Racing Bulls 1:30.781 1:30.109 1:30.319 +1.541 P11 Max Verstappen Red Bull Racing 1:30.519 1:30.262 - +1.484 βQ2 P12 Esteban Ocon Haas F1 Team 1:30.915 1:30.309 - +1.531 βQ2 P13 Nico Hulkenberg Audi 1:30.358 1:30.387 - +1.609 βQ2 P14 Liam Lawson Racing Bulls 1:30.657 1:30.495 - +1.717 βQ2 P15 Franco Colapinto Alpine 1:30.931 1:30.627 - +1.849 βQ2 P16 Carlos Sainz Williams 1:30.927 1:31.033 - +2.255 βQ2 P17 Alexander Albon Williams 1:31.088 - - +2.310 βQ1 P18 Oliver Bearman Haas F1 Team 1:31.090 - - +2.312 βQ1 P19 Sergio Perez Cadillac 1:32.206 - - +3.428 βQ1 P20 Valtteri Bottas Cadillac 1:32.330 - - +3.552 βQ1 P21 Fernando Alonso Aston Martin 1:32.646 - - +3.868 βQ1 P22 Lance Stroll Aston Martin 1:32.920 - - +4.142 βQ1 π QUALIFYING SECTOR DELTAS (vs field average): Driver S1 Ξ S2 Ξ S3 Ξ Total Ξ Top Spd -------------------------------------------------------------- Kimi Antonelli -0.686 -0.794 -0.209 -1.690 282 George Russell -0.688 -0.626 -0.077 -1.392 282 Oscar Piastri -0.578 -0.676 -0.081 -1.336 283 Charles Leclerc -0.763 -0.378 -0.023 -1.165 283 Lando Norris -0.492 -0.517 -0.049 -1.059 281 Lewis Hamilton -0.779 -0.299 +0.178 -0.901 276 Pierre Gasly -0.398 -0.204 -0.174 -0.777 285 Isack Hadjar -0.377 -0.096 -0.016 -0.490 285 Gabriel Bortoleto -0.192 -0.084 -0.201 -0.478 285 Arvid Lindblad +0.024 -0.190 -0.192 -0.359 287 Max Verstappen -0.172 -0.037 +0.004 -0.206 283 Esteban Ocon +0.020 -0.185 +0.007 -0.159 281 Nico Hulkenberg -0.055 -0.002 -0.052 -0.110 282 Liam Lawson +0.250 -0.058 -0.164 +0.027 285 Franco Colapinto +0.043 +0.200 -0.083 +0.159 282 Carlos Sainz +0.376 +0.201 -0.117 +0.459 291 Alexander Albon +0.317 +0.256 +0.048 +0.620 283 Oliver Bearman +0.283 +0.188 +0.152 +0.622 277 Sergio Perez +0.971 +0.434 +0.334 +1.738 283 Valtteri Bottas +0.821 +0.788 +0.254 +1.862 285 Fernando Alonso +0.995 +0.973 +0.211 +2.178 280 Lance Stroll +1.090 +1.108 +0.255 +2.452 277 ποΈ FINAL CAR PACE (10% season + 15% FP1 + 20% FP2 + 20% FP3 + 35% qualifying): Team Season FP1 FP2 FP3 Quali Final ---------------------------------------------------------------------- Mercedes P 1.5 P1.5 P1.5 P1.5 P1.5 P 1.5 Ferrari P 3.5 P5.5 P5.5 P3.5 P5.0 P 4.7 Haas F1 Team P 9.2 P11.5 P7.5 P15.5 P15.0 P 12.5 Alpine P 10.0 P15.5 P17.5 P13.5 P11.0 P 13.4 Racing Bulls P 10.0 P7.5 P11.5 P11.5 P12.0 P 10.9 Red Bull Racing P 12.5 P9.5 P13.5 P9.5 P9.5 P 10.6 Williams P 14.5 P17.5 P9.5 P17.5 P16.5 P 15.2 Audi P 15.8 P13.5 P15.5 P7.5 P11.0 P 12.0 Cadillac P 15.8 P19.5 P19.5 P19.5 P19.5 P 19.1 McLaren P 16.2 P3.5 P3.5 P5.5 P4.0 P 5.3 Aston Martin P 17.5 P21.5 P21.5 P21.5 P21.5 P 21.1 π‘οΈ Qualifying conditions: 16.5Β°C, 52% humidity, DRY β οΈ RACE CONTROL NOTES: TURN 14 INCIDENT INVOLVING CARS 55 (SAI) AND 6 (HAD) NOTED - IMPEDING FIA STEWARDS: TURN 14 INCIDENT INVOLVING CARS 55 (SAI) AND 6 (HAD) REVIEWED NO FURTHER INVESTIGATION - IMPEDING FIA STEWARDS: Q1 INCIDENT INVOLVING CARS 41 (LIN) AND 5 (BOR) NOTED - FAILING TO FOLLOW RACE DIRECTORS INSTRUCTIONS - MAXIMUM DELTA TIME FIA STEWARDS: Q1 INCIDENT INVOLVING CARS 41 (LIN) AND 5 (BOR) WILL BE INVESTIGATED AFTER THE SESSION - FAILING TO FOLLOW RACE DIRECTORS INSTRUCTIONS - MAXIMUM DELTA TIME FIA STEWARDS: Q2 INCIDENT INVOLVING CAR 44 (HAM) NOTED - FAILING TO FOLLOW RACE DIRECTORS INSTRUCTIONS - MAXIMUM DELTA TIME FIA STEWARDS: Q2 INCIDENT INVOLVING CAR 44 (HAM) WILL BE INVESTIGATED AFTER THE SESSION - FAILING TO FOLLOW RACE DIRECTORS INSTRUCTIONS - MAXIMUM DELTA TIME FIA STEWARDS: Q1 INCIDENT INVOLVING CARS 41 (LIN) AND 5 (BOR) NO FURTHER ACTION - FAILING TO FOLLOW RACE DIRECTORS INSTRUCTIONS - MAXIMUM DELTA TIME FIA STEWARDS: Q2 INCIDENT INVOLVING CAR 44 (HAM) NO FURTHER ACTION - FAILING TO FOLLOW RACE DIRECTORS INSTRUCTIONS - MAXIMUM DELTA TIME β Grid positions, sector deltas, car pace, speeds, and weather all updated from qualifying. β 22 drivers on the grid. No penalties applied.
4. XGBoost v1.0 β 24 FeaturesΒΆ
The brain of the model. XGBoost is a machine learning algorithm that learns which factors best predict race results by analyzing patterns across 72 historical races. It automatically figures out that grid position matters more than track temperature, or that car pace matters more than first-lap skill. The feature importance chart below shows exactly what the model thinks matters most.
Feature matrix: 1441 entries Γ 24 features
=================================================================
π€ XGBOOST v1.0 β 24 Features, Properly Validated
=================================================================
Leave-one-out MAE: 2.26 positions (HONEST metric)
Residual StdDev: 2.54
Features: 24 (all kept β race engineer approach)
2026 weight: 10x
This MAE is real β the model never saw the data it's predicting.
Top features:
grid_position 0.167
team_pit_strategy 0.104
is_2026 0.100
car_speed 0.095
team_changed 0.086
sector3_delta 0.071
driver_avg_finish 0.062
sector1_delta 0.037
5. Japan GP Predictions (v1.0)ΒΆ
The main event β predicted finishing order for Suzuka. Each column tells part of the story: Grid (actual qualifying position), Car (blended pace from all sessions), Spd (speed traps), Skill (teammate delta), Lap1 (first-corner performance), Tire (degradation rate), and Mom (improving/declining/stable).
Qualifying data is now integrated β actual grid positions, live Suzuka sector deltas, and 5-way blended car pace (10% season + 15% FP1 + 20% FP2 + 20% FP3 + 35% qualifying).
==================================================================================================== π PREDICTED FINISH β 2026 JAPANESE GP (v1.0 + Qualifying Data) ==================================================================================================== Pos Driver Team Grid Car Spd Skill Lap1 Tire Mom Pred ΞGrid ---------------------------------------------------------------------------------------------------- P 1 Kimi Antonelli Mercedes P 1 P 2 284 -1.8 -1.0 -0.032 π P 1.6 = P 2 George Russell Mercedes P 2 P 2 284 +1.8 -0.8 -0.011 π P 2.3 = P 3 Charles Leclerc Ferrari P 4 P 5 285 +2.4 +0.7 -0.027 π P 3.5 +1 P 4 Lando Norris McLaren P 5 P 5 284 +3.6 -0.3 -0.016 β‘οΈ P 4.6 +1 P 5 Oscar Piastri McLaren P 3 P 5 284 -3.6 -0.3 -0.007 π P 5.2 -2 P 6 Lewis Hamilton Ferrari P 6 P 5 285 -2.4 +1.1 +0.021 π P 5.6 = P 7 Gabriel Bortoleto Audi P 9 P12 287 +13.0 -0.5 -0.012 β‘οΈ P 7.5 +2 P 8 Isack Hadjar Red Bull Racing P 8 P11 287 -11.4 -0.6 -0.028 π P 8.3 = P 9 Max Verstappen Red Bull Racing P11 P11 287 +12.2 +0.3 -0.010 π P 8.8 +2 P10 Arvid Lindblad Racing Bulls P10 P11 288 +5.0 +5.5 +0.018 β‘οΈ P 8.8 = P11 Pierre Gasly Alpine P 7 P13 286 +2.0 +0.5 -0.020 π P 9.0 -4 P12 Liam Lawson Racing Bulls P14 P11 288 -0.8 +0.1 -0.024 π P 9.3 +2 P13 Nico Hulkenberg Audi P13 P12 287 -13.0 -0.1 +0.005 π P 9.9 = P14 Carlos Sainz Williams P16 P15 289 +3.4 +1.1 -0.001 π P11.1 +2 P15 Esteban Ocon Haas F1 Team P12 P12 283 0.0 +1.1 -0.034 π P11.9 -3 P16 Alexander Albon Williams P17 P15 289 -3.4 +0.2 -0.016 π P12.1 +1 P17 Oliver Bearman Haas F1 Team P18 P12 283 0.0 +0.2 -0.033 π P12.2 +1 P18 Franco Colapinto Alpine P15 P13 286 -2.0 +0.7 +0.006 π P12.5 -3 P19 Fernando Alonso Aston Martin P21 P21 279 +4.4 +1.1 -0.029 π P13.9 +2 P20 Valtteri Bottas Cadillac P20 P19 286 -3.0 +1.8 -0.012 π P14.3 = P21 Lance Stroll Aston Martin P22 P21 279 -4.4 +0.9 -0.005 β‘οΈ P15.0 +1 P22 Sergio Perez Cadillac P19 P19 286 +3.0 +0.2 +0.036 β‘οΈ P15.1 -3
6. Rain ScenarioΒΆ
Suzuka has been dry for the last 2 Japanese GPs, but 2023 had a safety car and rain is always possible in March. This shows how predictions shift in wet conditions β some drivers gain positions in the rain (strong wet-weather skills) while others lose out. Green arrows = gains in rain, red = loses.
====================================================================== π§οΈ RAIN SCENARIO ====================================================================== Driver Team Dry Wet Shift ------------------------------------------------------------ π’ Valtteri Bottas Cadillac P14.3 P13.2 +1.1 π’ Liam Lawson Racing Bulls P9.3 P8.7 +0.6 π’ Sergio Perez Cadillac P15.1 P14.6 +0.6 βͺ Franco Colapinto Alpine P12.5 P12.2 +0.3 βͺ Lance Stroll Aston Martin P15.0 P14.7 +0.3 βͺ Pierre Gasly Alpine P9.0 P8.8 +0.3 βͺ Alexander Albon Williams P12.1 P12.0 +0.1 βͺ Isack Hadjar Red Bull Racing P8.3 P8.4 -0.1 βͺ Max Verstappen Red Bull Racing P8.8 P9.1 -0.3 βͺ Fernando Alonso Aston Martin P13.9 P14.3 -0.4 π΄ George Russell Mercedes P2.3 P2.9 -0.5 π΄ Kimi Antonelli Mercedes P1.6 P2.2 -0.6 π΄ Oliver Bearman Haas F1 Team P12.2 P12.8 -0.6 π΄ Carlos Sainz Williams P11.1 P11.7 -0.6 π΄ Lando Norris McLaren P4.6 P5.3 -0.6 π΄ Nico Hulkenberg Audi P9.9 P11.0 -1.1 π΄ Gabriel Bortoleto Audi P7.5 P8.8 -1.3 π΄ Oscar Piastri McLaren P5.2 P6.6 -1.4 π΄ Charles Leclerc Ferrari P3.5 P5.2 -1.6 π΄ Arvid Lindblad Racing Bulls P8.8 P10.5 -1.8 π΄ Esteban Ocon Haas F1 Team P11.9 P13.8 -1.9 π΄ Lewis Hamilton Ferrari P5.6 P8.3 -2.6
7. Podium Probabilities (10,000 Simulated Races)ΒΆ
Instead of just predicting one outcome, we simulate the race 10,000 times with realistic randomness β mechanical failures, safety cars (33% chance at Suzuka), first-lap incidents, and general chaos. Then we count how often each driver ends up on the podium. This gives us probabilities rather than a single prediction, which better reflects how unpredictable F1 actually is.
===================================================================================== π² PODIUM PROBABILITIES (10,000 Simulated Races) ===================================================================================== Grid-aware variance: P1-3 Γ0.7, P4-7 Γ0.9, P8-15 Γ1.2, P16+ Γ1.0 Safety car: 33% chance (Suzuka historical) Driver Team Grid Win Podium Top 5 Top 10 -------------------------------------------------------------------------- Kimi Antonelli Mercedes P 1 43.9% 85.1% 96.8% 100.0% βββββββββββββββββββββ George Russell Mercedes P 2 24.9% 73.2% 93.3% 100.0% ββββββββββββ Charles Leclerc Ferrari P 4 14.5% 48.6% 75.1% 98.3% βββββββ Lando Norris McLaren P 5 6.3% 28.7% 58.3% 95.6% βββ Lewis Hamilton Ferrari P 6 3.2% 18.1% 43.9% 91.6% β Gabriel Bortoleto Audi P 9 1.9% 9.0% 21.2% 65.4% Oscar Piastri McLaren P 3 1.5% 14.9% 46.4% 96.0% Isack Hadjar Red Bull Racing P 8 1.2% 5.9% 14.6% 56.7% Max Verstappen Red Bull Racing P11 0.9% 4.8% 13.2% 50.7% Arvid Lindblad Racing Bulls P10 0.7% 4.2% 12.0% 49.8% Liam Lawson Racing Bulls P14 0.6% 3.2% 9.6% 44.5% Nico Hulkenberg Audi P13 0.3% 2.1% 6.4% 35.2% Pierre Gasly Alpine P 7 0.1% 1.1% 5.2% 46.0% Esteban Ocon Haas F1 Team P12 0.1% 0.3% 1.2% 15.0% Carlos Sainz Williams P16 0.0% 0.2% 1.1% 18.5%
8. Teammate BattlesΒΆ
The best measure of a driver's skill is how they perform against their teammate β same car, same strategy options, same pit crew. These head-to-head probabilities come from the 10,000 simulations and show who's likely to beat who within each team.
============================================================
π€ TEAMMATE HEAD-TO-HEAD
============================================================
Alpine
Pierre Gasly ββββββββββββββββββββββββββββββββββββββββ Franco Colapinto
81.4% 18.6%
Aston Martin
Fernando Alonso ββββββββββββββββββββββββββββββββββββββββ Lance Stroll
61.1% 38.9%
Audi
Gabriel Bortoleto ββββββββββββββββββββββββββββββββββββββββ Nico Hulkenberg
70.8% 29.2%
Cadillac
Valtteri Bottas ββββββββββββββββββββββββββββββββββββββββ Sergio Perez
59.1% 40.9%
Ferrari
Charles Leclerc ββββββββββββββββββββββββββββββββββββββββ Lewis Hamilton
71.8% 28.2%
Haas F1 Team
Esteban Ocon ββββββββββββββββββββββββββββββββββββββββ Oliver Bearman
53.1% 46.9%
McLaren
Lando Norris ββββββββββββββββββββββββββββββββββββββββ Oscar Piastri
58.6% 41.4%
Mercedes
Kimi Antonelli ββββββββββββββββββββββββββββββββββββββββ George Russell
62.3% 37.7%
Racing Bulls
Arvid Lindblad ββββββββββββββββββββββββββββββββββββββββ Liam Lawson
54.3% 45.7%
Red Bull Racing
Isack Hadjar ββββββββββββββββββββββββββββββββββββββββ Max Verstappen
53.9% 46.1%
Williams
Carlos Sainz ββββββββββββββββββββββββββββββββββββββββ Alexander Albon
61.4% 38.6%
9. F1 Fantasy PicksΒΆ
Translating race predictions into F1 Fantasy strategy. The key insight: value matters more than raw points. A cheap driver who scores 12 points is better for your team than an expensive driver who scores 25 points, because the budget you save lets you upgrade elsewhere. The β marks the best value picks.
=====================================================================================
π F1 FANTASY PICKS β Japan GP (v1.0)
=====================================================================================
Driver Team Pred Race Qual Bonus TOTAL ~$M Value
----------------------------------------------------------------------------------
Kimi Antonelli Mercedes P 1 19.5 10 0.0 29.5 $ 24 1.24 β
George Russell Mercedes P 2 17.0 9 0.0 26.0 $ 28 0.93
Charles Leclerc Ferrari P 3 13.5 7 0.0 20.5 $ 23 0.88
Oscar Piastri McLaren P 5 8.6 8 0.0 16.6 $ 25 0.67
Lando Norris McLaren P 4 10.5 6 0.0 16.5 $ 27 0.61
Lewis Hamilton Ferrari P 6 8.5 5 0.0 13.5 $ 23 0.59
Gabriel Bortoleto Audi P 7 4.8 2 0.0 6.8 $ 6 1.06
Isack Hadjar Red Bull Racing P 8 3.7 3 0.0 6.7 $ 14 0.48
Liam Lawson Racing Bulls P12 2.5 0 4.0 6.5 $ 7 0.94
Pierre Gasly Alpine P11 2.0 4 0.0 6.0 $ 13 0.47
Fernando Alonso Aston Martin P19 0.1 0 4.4 4.5 $ 9 0.51
Lance Stroll Aston Martin P21 0.0 0 4.2 4.3 $ 7 0.63
Arvid Lindblad Racing Bulls P10 3.1 1 0.0 4.1 $ 7 0.55
Oliver Bearman Haas F1 Team P17 0.3 0 3.5 3.8 $ 9 0.44
Max Verstappen Red Bull Racing P 9 3.2 0 0.5 3.7 $ 28 0.13
Carlos Sainz Williams P14 0.6 0 2.8 3.5 $ 12 0.28
Nico Hulkenberg Audi P13 1.8 0 0.9 2.7 $ 6 0.49
Alexander Albon Williams P16 0.3 0 2.1 2.4 $ 11 0.22
Valtteri Bottas Cadillac P20 0.0 0 2.4 2.4 $ 5 0.51
Esteban Ocon Haas F1 Team P15 0.6 0 0.0 0.6 $ 8 0.07
Franco Colapinto Alpine P18 0.4 0 0.0 0.4 $ 7 0.06
Sergio Perez Cadillac P22 0.0 0 0.0 0.0 $ 6 0.00
π‘ PICKS:
π₯ Best value:
β Kimi Antonelli (Mercedes) β 29.5 pts / $23.8M = 1.24
β Gabriel Bortoleto (Audi) β 6.8 pts / $6.4M = 1.06
β Liam Lawson (Racing Bulls) β 6.5 pts / $6.9M = 0.94
β George Russell (Mercedes) β 26.0 pts / $28.0M = 0.93
β Charles Leclerc (Ferrari) β 20.5 pts / $23.4M = 0.88
π 2x Boost: Kimi Antonelli β 29.5 Γ 2 = 59.0
ποΈ CONSTRUCTORS:
Constructor Season R03 $M S.Val R.Val
-------------------------------------------------------
Mercedes 211 55.5 $29.9 7.06 1.86 β
Ferrari 188 33.9 $23.9 7.87 1.42 β
Haas F1 Team 99 4.4 $ 8.6 11.51 0.51 β
Red Bull Racing 87 10.4 $28.8 3.02 0.36
Racing Bulls 85 10.5 $ 7.5 11.33 1.41 β
Alpine 67 6.4 $13.7 4.89 0.47
Williams 42 5.9 $13.2 3.18 0.44
McLaren 12 33.1 $28.5 0.42 1.16
Cadillac 9 2.4 $ 5.2 1.73 0.46
Audi -4 9.5 $ 5.4 -0.74 1.77
Aston Martin -58 8.8 $ 9.1 -6.37 0.96
π₯ Best value constructors (season pts / price):
β Haas F1 Team β 99 pts / $8.6M = 11.51
β Racing Bulls β 85 pts / $7.5M = 11.33
β Ferrari β 188 pts / $23.9M = 7.87
10. My Fantasy TeamsΒΆ
Analysis of my two actual F1 Fantasy teams with specific transfer recommendations based on the model's predictions. Each suggestion shows the points gained, cost impact, and remaining budget.
=========================================================================== π RUSSELLIN' FOR POSITION Transfers: 0 | Cap: $0.3M =========================================================================== Driver $ Bst Pred Pts 2x Val ------------------------------------------------------------ George Russell $28.0 P 2 26.0 26.0 0.93 Lewis Hamilton $22.9 P 6 13.5 13.5 0.59 Kimi Antonelli $23.8 2xβ‘ P 1 29.5 59.0 1.24 Oliver Bearman $ 8.6 P 17 3.8 3.8 0.44 Valtteri Bottas $ 4.7 P 20 2.4 2.4 0.51 Constructor $ Szn R03 Val ------------------------------------------------------------ Racing Bulls $ 7.5 85 10.5 11.33 Cadillac $ 5.2 9 2.4 1.73 π PROJECTED: 117.6 pts (Drivers: 104.6 + Constructors: 13.0) π TRANSFERS: π CONSTRUCTOR UPGRADE PATHS: Cadillac β Haas F1 Team + 90 szn pts need $3.1M freed Cadillac β Williams + 33 szn pts need $7.7M freed Cadillac β Alpine + 58 szn pts need $8.2M freed Racing Bulls β Haas F1 Team + 14 szn pts need $0.8M freed Racing Bulls β Ferrari +103 szn pts need $16.1M freed Racing Bulls β Mercedes +126 szn pts need $22.1M freed β Boost correct on Kimi Antonelli =========================================================================== π LECLERC ME IF YOU CAN Transfers: 0 | Cap: $0.0M =========================================================================== Driver $ Bst Pred Pts 2x Val ------------------------------------------------------------ George Russell $28.0 P 2 26.0 26.0 0.93 Charles Leclerc $23.4 P 3 20.5 20.5 0.88 Kimi Antonelli $23.8 2xβ‘ P 1 29.5 59.0 1.24 Franco Colapinto $ 7.0 P 18 0.4 0.4 0.06 Valtteri Bottas $ 4.7 P 20 2.4 2.4 0.51 Constructor $ Szn R03 Val ------------------------------------------------------------ Racing Bulls $ 7.5 85 10.5 11.33 Cadillac $ 5.2 9 2.4 1.73 π PROJECTED: 121.3 pts (Drivers: 108.3 + Constructors: 13.0) π TRANSFERS: π CONSTRUCTOR UPGRADE PATHS: Cadillac β Haas F1 Team + 90 szn pts need $3.4M freed Cadillac β Williams + 33 szn pts need $8.0M freed Cadillac β Alpine + 58 szn pts need $8.5M freed Racing Bulls β Haas F1 Team + 14 szn pts need $1.1M freed Racing Bulls β Ferrari +103 szn pts need $16.4M freed Racing Bulls β Mercedes +126 szn pts need $22.4M freed β Boost correct on Kimi Antonelli
Confidence: HIGH (post-qualifying)ΒΆ
| Version | Features | Key Addition | Confidence |
|---|---|---|---|
| v0.1 | 3 | ELO baseline | LOW |
| v0.2 | 9 | Regulation-aware weighting | LOW-MEDIUM |
| v0.3 | 9 | XGBoost ML | MEDIUM |
| v0.4 | 15 | Two-model approach + weather | MEDIUM |
| v0.5 | 15 | Speed traps + lap consistency | MEDIUM |
| v0.6 | 18 | First lap + tire degradation + momentum | MEDIUM |
| v0.7 | 21 | Suzuka sectors + safety car sim | MEDIUM-HIGH |
| v0.8 | 21 | 2026 weighted 10x (car > driver fix) | MEDIUM-HIGH |
| v0.9 | 22 | Honest validation + team change flag | MEDIUM-HIGH |
| v1.0 | 24 | Tire strategy + practice data | MEDIUM-HIGH |
| v1.0+Q | 24 | Actual qualifying grid + live sectors + 5-way car pace + position-dependent sims | HIGH |
What changed from pre-qualifying:
- Grid positions: estimated from season averages β actual P1-P22 from qualifying
- Sector deltas: 2023-2024 historical Suzuka β live 2026 qualifying sectors
- Car pace: 3-way blend (season/FP1/FP2) β 5-way blend (+FP3 +qualifying, 35% quali weight)
- Speed traps: FP1/FP2 only β includes qualifying max attack speeds
- Simulation: uniform variance β grid-position-dependent (front row tighter, midfield wider)
- Fantasy: estimated quali positions β actual qualifying results for scoring
- Weather: FP2 conditions β qualifying conditions (16.5Β°C, 52% humidity, dry)
Remaining uncertainty:
- Race day weather could change (forecast is dry but Suzuka is unpredictable)
- Safety car timing and VSC periods (modeled as 33% probability)
- Tire strategy choices (1-stop vs 2-stop) not yet race-specific
- First lap incidents β modeled statistically but inherently random
- Post-race: accuracy analysis to calibrate for future races