MotoGP Data dominance · tyre · race pace
ca es

Marco Bezzecchi

Italy

Career

Pace and style

Pace

MetricValueUsual rangeRankn
Race pace+0.40%0.15–0.654/54141
One-lap pace (qualifying)+0.65%0.24–0.979/5490
Long run (practice)+0.39%0.11–0.864/59199
Fast lap (practice)+0.65%0.27–0.977/60254

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)0.27%0.21–0.3515/54113
Places gained grid → finish0.00-3.00–3.0063/8295
Hides pace for qualifying+0.20-0.43–0.887/4987
Hides pace for the race+0.13-0.56–0.6717/3845
Qualifying specialist (+) or diesel (−)−0.10—34/4390
Races better than qualifies+0.41-0.60–2.7520/7479
Top speed368.6 km/h—3/649562

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

−0.22
Start
+0.36
First laps
+0.79
End of race
+1.15
Total

Positions gained (+) or lost (−) in each phase versus what the rider’s position would suggest, over 42 races. Descriptive.

Races better than qualifies?

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

SeasonBeats the gridn
2026+2.4110
2025+1.6318
2024−0.2317
2023+1.1717
2022−2.1517

Q2 risk

8%
Q2 with best lap cancelled
4%
Disastrous Q2

Over 76 Q2 sessions since 2021. Disaster = best lap more than 1% slower than the others' median.

Tyres

Tyre management

Metrics/lapUsual rangeRankn
Degradation in practice · Medium+0.5530.079–1.02830/344
Degradation in practice · Soft+0.2240.162–0.3025/138
Race degradation (fuel-corrected)+0.0420.017–0.07833/54113
Pace loss in the race+0.023-0.005–0.05733/54113

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+0.15%−0.0061→3
2026 AUTMedium / Medium+0.05%+0.0594→3
2026 BRAHard / Medium+0.04%+0.0062→1
2026 CATMedium / Soft+0.40%+0.07512→4
2026 FRAHard / Soft+0.12%+0.0212→2
2026 GBRHard / Medium+0.17%−0.0255→3
2026 ITAMedium / Medium0.00%+0.0781→1
2026 NEDMedium / Medium—%—3→—
2026 SPAMedium / Medium+0.19%+0.0354→2
2026 THASoft / Medium0.00%+0.0881→1

★ = 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: RSM (+0.45), ITA (+0.22) · Weak at: GBR (−0.25), ARA (−0.32), GER (−0.36)

In races · Strong at: FRA (+0.33) · Weak at: AUT (−0.33), JPN (−0.34), MAL (−0.45)

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
2026Aprilia RacingJorge Martin7–59–6264–306
2025Aprilia RacingLorenzo Savadori10–113–1353–8
2024Pertamina Enduro VR46 Racing TeamFabio Di Giannantonio8–98–9153–165
2023Mooney VR46 Racing TeamLuca Marini11–79–10329–201
2022Mooney VR46 Racing TeamLuca Marini8–1211–9111–120

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.

Injuries and absences

SeasonGPTypeNote
2026GERAbsentNo result between two weekends that were raced
2026GBRComeback1st GP after being absent (GER)
2026ARAComeback2nd GP after being absent (GER)