MotoGP Data dominance · tyre · race pace
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Riders

Alex Rins

Spain

Career

Pace and style

Pace

MetricValueUsual rangeRankn
Race pace+0.87%0.40–1.1928/54187
One-lap pace (qualifying)+0.97%0.71–1.3224/54131
Long run (practice)+0.82%0.48–1.2415/59270
Fast lap (practice)+0.86%0.48–1.3622/60434

Percentage above the fastest rider of each session (median over all their sessions): 0% would mean always being the fastest. The usual range goes from their good quartile to their bad one. Rank: among all riders with enough data.

Style

MetricValueUsual rangeRankn
Consistency (pace variation)0.30%0.22–0.4128/54153
Places gained grid → finish+3.00-1.00–5.0018/82159
Hides pace for qualifying−0.02-0.67–0.6226/49137
Hides pace for the race−0.00-0.63–0.4027/3867
Qualifying specialist (+) or diesel (−)+0.09—13/43131
Races better than qualifies+0.88-1.61–3.6213/74126
Top speed361.2 km/h—25/6415220

Descriptive: how the rider has done so far, not a prediction. "Hides pace" is not very stable from one year to the next: always look at the usual range.

Race and qualifying

Racecraft by phase

+0.17
Start
−1.06
First laps
−1.11
End of race
−2.17
Total

Positions gained (+) or lost (−) in each phase versus what the rider’s position would suggest, over 33 races. Descriptive.

Races better than qualifies?

Positions finished better (+) or worse (−) than the starting position suggests, per season.

SeasonBeats the gridn
2026−0.5511
2025−1.3520
2024−2.4014
2023+2.974
2022+1.9915
2021+0.4512
2020+3.0311
2019+3.5516
2018+2.4813
2017+0.7410

Q2 risk

2%
Q2 with best lap cancelled
5%
Disastrous Q2

Over 44 Q2 sessions since 2021. Disaster = best lap more than 1% slower than the others' median.

Tyres

Tyre management

Metrics/lapUsual rangeRankn
Degradation in practice · Hard+0.3110.311–0.3216/63
Degradation in practice · Medium+0.2170.155–0.3357/349
Race degradation (fuel-corrected)+0.0290.001–0.06114/54153
Pace loss in the race+0.010-0.021–0.04216/54153

Seconds lost per lap over a run. Lower is better: better tyre management.

Tyres race by race

GPFront / rearRel. paceDeg. s/lapGrid→Pos.
2026 ARAMedium / Medium+1.00%−0.00519→13
2026 AUTMedium / Medium+1.25%+0.05220→19
2026 BRAHard / Soft ★+1.12%−0.00917→14
2026 CATMedium / Soft+0.59%+0.07619→14
2026 CZEMedium / Medium+1.35%−0.01317→—
2026 FRAHard / Soft+1.12%+0.02111→12
2026 GBRHard / Medium—%—17→—
2026 GERHard / Medium+1.91%+0.04217→14
2026 HUNMedium / Soft+1.11%−0.02220→13
2026 ITAMedium / Medium+0.72%+0.11912→—

★ = chose the minority compound. Degradation includes fuel and traffic: only compare within the same race.

Circuits, team and injuries

Strongest and weakest circuits

Over one lap · Strong at: SPA (+0.48) · Weak at: FRA (−0.48), CZE (−1.31)

In races · Strong at: GBR (+0.51), VAL (+0.44) · Weak at: AUT (−0.63)

Affinity: how much better (+) or worse (−) the rider performs at this circuit versus their own average, in percentage points of gap. Only cases with enough signal are shown.

Against the teammate

SeasonTeamTeammateRaceGridPoints
2026Monster Energy Yamaha MotoGP TeamFabio Quartararo3–111–1423–65
2025Monster Energy Yamaha MotoGP TeamFabio Quartararo6–161–2168–201
2024Monster Energy Yamaha MotoGP TeamFabio Quartararo5–124–1431–113
2023LCR Honda CASTROLIker Lecuona0–11–054–0
2022Team SUZUKI ECSTARJoan Mir9–49–6173–87
2021Team SUZUKI ECSTARJoan Mir4–1211–699–208
2020Team SUZUKI ECSTARJoan Mir5–84–10139–171
2019Team SUZUKI ECSTARJoan Mir13–413–4205–92
2018Team SUZUKI ECSTARAndrea Iannone9–96–13169–133
2017Team SUZUKI ECSTARAndrea Iannone6–75–759–70

Who finishes ahead in the races both started; a retirement loses to a classified finish. With fewer than 8 races together it is only indicative.