Analysis
LMU Hypercar car strength ranking
Overall Hypercar car strength ranking across all major Le Mans Ultimate circuits, based on weighted lap time gaps from GoSetups, BeAlien, and Hymo.
Updated 3 Aug 2026
Data on this page is cached and may be up to 48h old. For live figures, use the Discord bot.
Based on aggregate setup-shop benchmark data, the Lamborghini SC63 is the strongest Hypercar car in Le Mans Ultimate, followed by the Genesis GMR-001 and the Cadillac V-Series.R.
Hypercar — all 16 tracks
Lower score = stronger car. Score = 60% avg gap + 40% worst gap across selected tracks.
| # | Car | Score | Avg Gap | Worst | Coverage |
|---|---|---|---|---|---|
| 1 | Lamborghini SC63 | 0.280 | +0.15% | +0.47% | 6/16 |
| 2 | Genesis GMR-001 | 0.380 | +0.18% | +0.67% | 11/16 |
| 3 | Cadillac V-Series.R | 0.419 | +0.22% | +0.72% | 5/16 |
| 4 | Alpine A424 | 0.456 | +0.29% | +0.70% | 5/16 |
| 5 | Peugeot 9X8 EVO | 0.462 | +0.29% | +0.73% | 5/16 |
| 6 | BMW M Hybrid V8 | 0.519 | +0.33% | +0.80% | 5/16 |
| 7 | Ferrari 499P | 0.542 | +0.38% | +0.78% | 6/16 |
| 8 | Toyota GR010 Hybrid | 0.572 | +0.38% | +0.86% | 3/16 |
| 9 | Aston Martin Valkyrie AMR-LMH | 0.613 | +0.47% | +0.83% | 6/16 |
| 10 | Peugeot 9X8 | 0.674 | +0.53% | +0.89% | 7/16 |
| 11 | Glickenhaus 007 LMH | 0.683 | +0.50% | +0.96% | 2/16 |
| 12 | Isotta Fraschini Tipo 6 LMH-C | 0.699 | +0.49% | +1.02% | 2/16 |
| 13 | Porsche 963 | 0.774 | +0.38% | +1.36% | 4/16 |
Only lap times published on each source's official setup shop are tracked here. Cars with no data on any selected track are excluded from the ranking.
How the ranking works
Score
A composite metric where lower is better and 0 means the car was fastest (or tied fastest) on every selected track.
score = 0.6 × avg_gap + 0.4 × worst_gap
Avg gap is weighted by data quality (see Evidence tiers). Worst gap uses the raw value from the weakest track regardless of weight.
Gap per track
For each track the gap is the car's % time deficit behind the fastest car with a current lap on that track. If no current laps exist the fastest stale lap is used as the reference instead.
A stale lap that beats every current lap still gets a gap of 0% - the car is demonstrably fast even on older data. The stale weight (0.5) is still applied to reduce its influence on the average.
Evidence tiers
- Current (weight 1.0) - lap is up to date with the active BoP. No patch warning.
- Stale (weight 0.5) - lap exists but a newer BoP change has been released for this car. The setup shop has not yet published an updated time.
- Imputed (weight 0.0) - no lap at all on this track. The field median gap from current cars is substituted so the car is not silently ignored.
Coverage badge
Shows how many of the selected tracks have current data for that car out of the total.
- Green X/X - all tracks have current data.
- Amber X/X - at least one track has a stale lap but no missing data.
- Red X/X - at least one track has no lap data at all (imputed).
Hover the badge to see the breakdown of current, stale, and imputed tracks.
Worked example
GT3, two tracks selected: Spa-Francorchamps and Monza.
| Car | Spa gap | Monza gap | Avg gap | Worst gap | Score | Rank |
|---|---|---|---|---|---|---|
| BMW M4 GT3 | +0.28% | +0.00% | 0.14% | 0.28% | 0.196 | 1 |
| Ferrari 296 GT3 | +0.00% | +0.35% | 0.175% | 0.35% | 0.245 | 2 |
BMW M4 score: 0.6 × 0.14 + 0.4 × 0.28 = 0.084 + 0.112 = 0.196
Ferrari 296 score: 0.6 × 0.175 + 0.4 × 0.35 = 0.105 + 0.140 = 0.245
The BMW wins despite being slower at Spa because its worst-track gap (0.28%) is smaller than the Ferrari's (0.35%). The score penalises cars that have a weak track in the selection - a car that is consistently decent beats one that excels somewhere but falls apart elsewhere.