MotoGP Data dominance · tyre · race pace
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Round 10 of 18 Aftermath

Styrian Grand Prix 2021

Red Bull Ring - Spielberg Austria

4.348 m · 28 laps · since 1996
06.08 – 08.08.2021
Aftermath

What happened

The official result against what we predicted, race craft by phase and the start.

Race result

Pos.RiderBikeTeamTime / gapPoints
1Jorge MartinDucatiPramac Racing38:07.87925
2Joan MirSuzukiTeam SUZUKI ECSTAR+1.54820
3Fabio QuartararoYamahaMonster Energy Yamaha MotoGP+9.63216
4Brad BinderKTMRed Bull KTM Factory Racing+12.77113
5Takaaki NakagamiHondaLCR Honda IDEMITSU+12.92311
6Johann ZarcoDucatiPramac Racing+13.03110
7Alex RinsSuzukiTeam SUZUKI ECSTAR+14.8399
8Marc MarquezHondaRepsol Honda Team+17.9538
9Alex MarquezHondaLCR Honda CASTROL+19.0597
10Daniel PedrosaKTMRed Bull KTM Factory Racing+19.3896
11Francesco BagnaiaDucatiDucati Lenovo Team+21.6675
12Enea BastianiniDucatiAvintia Esponsorama+25.2674
13Valentino RossiYamahaPetronas Yamaha SRT+26.2823
14Luca MariniDucatiSKY VR46 Avintia+27.4922
15Iker LecuonaKTMTech 3 KTM Factory Racing+31.0761
16Pol EspargaroHondaRepsol Honda Team+31.1500
17Cal CrutchlowYamahaPetronas Yamaha SRT+40.4080
18Danilo PetrucciKTMTech 3 KTM Factory Racing+48.1140
DNFAleix EspargaroApriliaAprilia Racing Team GresiniRetired0
DNFJack MillerDucatiDucati Lenovo TeamRetired0
DNFLorenzo SavadoriApriliaAprilia Racing Team GresiniDid not start0
DNFMaverick ViñalesYamahaMonster Energy Yamaha MotoGPRetired0
DNFMiguel OliveiraKTMRed Bull KTM Factory RacingRetired0

Sprint result

Pending · no data yet

Forecast vs reality

C14
ForecastFavouriteWinnerOrder (model / grid)Position error (model / calibrated grid)
Race (after the grid)Jorge Martin · 30% ✓Jorge Martin · 30% · from P10.79 / 0.792.3 / 2.3

Error: average positions off, compared with the calibrated grid (the grid turned into expected positions with a simple regression, no model). If the model does not beat it, its edge over the raw grid is only calibration.

How it’s calculated

Each forecast (race before the sprint, race after the sprint, and sprint) is compared with the official result once the race has been run, only if there are at least 8 classified finishers. It measures: whether the predicted order resembles the real one (rank correlation, from 0 = no relationship to 1 = identical), the average error in positions for those who finish, the same for the grid as a reference, the “probability error” for the win and the podium (the average of the squared difference between the probability given and what happened: 0 is perfect, lower is better), what share of riders finished within their 80% interval, who the favourite was and whether they won, and what probability the actual winner had. Everything is walk-forward: each forecast was made only with data from before that race.

Keep in mind. A single race says little: the model should be judged over a whole season. To compare the position error fairly there is also a “corrected grid” (the grid adjusted using previous races, because the pole-sitter cannot gain places and the last rider cannot lose any); against this reference the improvement before the sprint is small, and after the sprint it is real.

Lap-by-lap positions: race

Position crossing the line on each lap. The top six are in colour; the rest can be switched on in the legend. When a rider retires, their line ends.

Lap-by-lap positions: sprint

Pending · no data yet

Race pace

RiderPaceGapDeg. s/lapRearn
Jorge Martin1:24.464—+0.457Medium22
Joan Mir1:24.480+0.016+0.562Medium24
Jack Miller1:24.654+0.190+0.105Medium14
Fabio Quartararo1:24.863+0.399+0.275Medium24
Takaaki Nakagami1:24.872+0.408+0.359Medium21
Brad Binder1:24.950+0.486+0.327Medium22
Johann Zarco1:24.951+0.487+0.344Soft25
Alex Rins1:24.980+0.516+0.217Medium21
Miguel Oliveira1:25.036+0.572+0.193Medium11
Marc Marquez1:25.109+0.645+0.210Medium22
Maverick Viñales1:25.185+0.721+0.292Medium16
Alex Marquez1:25.186+0.722+0.356Medium22
Daniel Pedrosa1:25.188+0.724+0.089Medium25
Francesco Bagnaia1:25.218+0.754+0.221Soft22
Enea Bastianini1:25.243+0.779+0.319Medium19
Luca Marini1:25.348+0.884+0.308Medium24
Valentino Rossi1:25.388+0.924+0.508Medium22
Iker Lecuona1:25.459+0.995+0.094Medium20
Danilo Petrucci1:25.468+1.004+0.574Medium24
Pol Espargaro1:25.520+1.056+0.406Medium20
Cal Crutchlow1:25.793+1.329+0.729Medium21

Actual race pace: median of the clean laps, excluding the first lap, cancelled laps and pit laps. Degradation mixes tyre wear, fuel and traffic.

How it’s calculated

Three paces per rider and GP (since 2018). Practice: estimated race pace from laps done on medium front and rear tyres that are already used (fresh rubber inflates the pace), not counting FP1 (unrepresentative time of day and track conditions); only laps no more than 0.20 s per kilometre above the same rider’s best lap in these conditions are kept (0.25 in Thailand and Malaysia), and the median is taken. Race and sprint: median of the actual clean laps, with a minimum of 4. The pace per km, the scatter, the sectors, the tyre age range of the laps used and, as context, the rider’s typical degradation on the medium in practice are also given.

Keep in mind. Practice pace is an estimate: we do not know how much fuel or which engine map each rider is running, which is why it is not used to forecast the race. Compare riders within the same GP; across circuits, use the pace per km with caution.

Who was the most consistent

Race

#RiderIndex (1 = field)Spread %Deg. s/lapLaps
1Jack Miller0.690.20%−0.01912
2Takaaki Nakagami0.740.21%+0.02920
3Jorge Martin0.800.23%+0.00920
4Francesco Bagnaia0.870.25%+0.00120
5Daniel Pedrosa0.890.25%−0.01323
6Brad Binder0.900.26%−0.00620
7Fabio Quartararo0.930.26%+0.03222
8Alex Rins0.930.26%+0.02520
9Joan Mir0.940.27%+0.01622
10Johann Zarco0.970.27%+0.04023
11Cal Crutchlow1.000.28%+0.02919
11Miguel Oliveira1.000.28%−0.01010
13Marc Marquez1.030.29%+0.01020
14Danilo Petrucci1.050.30%+0.02522
15Valentino Rossi1.110.32%+0.01521
16Luca Marini1.120.32%−0.01722
17Alex Marquez1.840.52%+0.04120
18Iker Lecuona3.721.06%+0.06718
19Pol Espargaro3.861.10%+0.02818
20Enea Bastianini3.891.11%+0.00417
21Maverick Viñales6.941.97%+0.12915

Index: below 1 = more consistent than the field in this race. Spread: how far laps stray from the rider’s trend, as % of lap time. Only riders who ran in one stint. Excluding the first 2 and last 2 laps of each race, pit entries and anomalous laps.

All race consistency →

How it’s calculated

For each rider and race or sprint (since 2018) in which they did not pit, their clean laps are taken excluding the first 2 and the last 2 (where the fight at the start and the easing off at the end happen), with a minimum of 7. Since lap times change over the race (the tyre wears, the tank empties), first the straight line that best follows that trend is drawn and then how far the laps deviate from it is measured: the scatter around the line, as a % of the typical lap time. The lower, the more consistent. To compare circuits and years this % is divided by the median of all riders in that race: an index below 1 means more consistent than the field, above 1 less. For the season the median of the index across all their races is taken, and the ranking only includes riders with at least 5 races. Bike-swap races (flag-to-flag) do not count; races restarted after a red flag do, with the part that counts.

Keep in mind. It only measures consistency, not speed: a rider can be very consistent and slow. Riders who went into the pits are left out. The whole-career figure is the median index across all their races since 2018 (full races and sprints separately), using the same measure; the site only shows riders with 20 races or more, because with few races the figure depends heavily on luck.

The race in numbers

Race

94
Overtakes
1
Lead changes
2 leaders
24/27
Laps led by the winner
Jorge Martin
1.548 s
Closest finish

Comeback of the day: Brad Binder, from P16 to P4.

Longest battle: Joan Mir vs Jorge Martin (21 laps).

Overtakes are counted at the finish line: moves undone within the same lap are not seen. It is a measure of movement, not an official statistic.

How it’s calculated

Everything comes from the order of crossing the line on each lap (official lap-by-lap position sheet, since 2010). An overtake is a pair of riders who swap order between two consecutive laps (moving up because someone retires does not count). A battle is two riders running less than 1 second apart for at least 5 consecutive laps. Lead changes, different leaders, laps led by the winner, the closest finish (gap of 2nd at the line), the biggest comeback (from the official grid to the finishing position) and whether there was a red flag are also counted. Per rider: position on the first lap and at the finish, laps led, overtakes made and suffered, best and worst position.

Keep in mind. Only what happens at the finish line is seen: an overtake and a counter-overtake within the same lap do not show up. It is a measure of the race’s “movement”, not an official overtaking statistic.

Incidents

SessionTimeRiderWhatDetail
Race14:01:13Jump startJump start
Race14:03:55Lorenzo SavadoriCrashCrashed out - Rider OK
Race14:03:55Daniel PedrosaCrashCrashed out - Rider OK
Race14:42:52Lorenzo SavadoriDid not startDid not start
Race14:43:08Maverick ViñalesPit-lane startStarting from pit lane
Race14:44:08Jump startJump start
Race14:59:47Maverick ViñalesLong lapLong lap penalty due to exceeding track limit
Race15:02:59Enea BastianiniLong lapLong lap penalty due to exceeding track limit
Race15:03:12Miguel OliveiraRetiredEntered pits and retired
Race15:07:58Jack MillerCrashCrashed out - Rider OK
Race15:09:00Jack MillerRetiredEntered pits and retired
Race15:09:15Pol EspargaroLong lapLong lap penalty due to exceeding track limit
Race15:15:59Iker LecuonaLong lapLong lap penalty due to exceeding track limit
Race15:22:02Maverick ViñalesRetiredEntered pits and retired
Race15:23:18Long lapLong lap penalty

Race: 13 track-limit warnings.

Official race direction log (Session.pdf). Times are local circuit time.

The start

C23

Holeshot: Jack Miller (started P4).

RiderGridL1Δ
Iker Lecuona1913+6
Brad Binder1611+5
Alex Rins138+5
Maverick Viñales922−13
Aleix Espargaro717−10
Francesco Bagnaia26−4
How it’s calculated

For each race and sprint, each rider’s position on the official grid (the race grid or the sprint grid, which can differ because of penalties) is compared with the position in which they cross the line at the end of the first lap, according to the official lap-by-lap position sheet. “Gain” is the places gained (positive) or lost (negative) at the start and on the first lap; “holeshot” marks who crosses the line first at the end of the first lap.

Keep in mind. It measures the whole first lap, not just the start to the first corner. In the 6 races split by a red flag, the actual restart grid was the order from the first part, and here it is compared with Saturday’s grid: the gain in those races is approximate.

Who finished better and worse than the grid suggested

RiderGrid→Pos.Beats the grid
Brad Binder16→4+8.5
Takaaki Nakagami10→5+3.6
Alex Rins13→7+3.5
Danilo Petrucci22→18−1.7
Pol Espargaro15→16−4.2
Francesco Bagnaia2→11−7.5

Positions gained (+) or lost (−) versus what the starting position suggests, net of what is normally gained or lost at the start. Finishers only.

How it’s calculated

Using all riders who have finished races since 2010, the typical finishing position for each starting position is calculated (a straight line: whoever starts 10th finishes, on average, around 10th, but the pole-sitter cannot gain places and the last rider cannot lose any, and the line already takes this into account). The residual for a race is the difference between this typical position and the actual position: positive means they finished better than their grid slot suggested, negative worse. The evolution takes the average of all of each rider’s residuals per season.

Keep in mind. It only counts finished races: a retirement gives no residual (it leaves a gap in the curve, not a bad number). A single race is noise; what matters is the trend over many races.

The tyre gamble

RearShareRel. paceDeg. s/lapWinsPodiumsAvg. pos.
Medium91%+0.85%+0.014139.6
Soft9%+0.73%+0.018008.5

Rear compound in the race. Pace is relative to the best of the session; degradation includes fuel and traffic, so only compare within the same race.

How it’s calculated

In each race and sprint since 2018, a rider’s compound is the one that appears on most of their laps (front and rear). Per rider: the median of the clean laps, the % gap to the best pace of the session, the degradation (how many seconds per lap they slow down on average, calculated if they have at least 6 clean laps), the grid and the result; “minority” means their rear compound is not the one chosen by most of the field. Per compound: what % of the field chose it, the median pace and degradation, wins, podiums, average finishing position of those who finish and % of retirements (out of those who started on that compound). It helps answer “did the minority gamble pay off?”.

Keep in mind. Degradation mixes the tyre, the fuel being burned and traffic, so it only makes sense to compare riders within the same race, not across circuits. A compound chosen by 1 or 2 riders gives figures that depend heavily on who ran it.

Race weather

C25
17.9 °C
Air
max 18.5 °C
82%
Humidity
1.5 mm
Rain
8 km/h
Wind
gusts 30 km/h

Open-Meteo data at the circuit location during the race; not the track temperature.

Race weekend

As it happens

Live timing, the grid as it forms and who wins the run to turn one.

The weekend, session by session

FP1 · 06.08
Pos.RiderBest lapGapLapsTop km/hTyres (front / rear)Long-run pacePace gapn runRun rear
1Takaaki Nakagami01:23.805—22312.1— / ———
2Joan Mir01:23.881+0.07622310.3Medium / Medium——
3Aleix Espargaro01:24.183+0.37822308.5Soft / Medium——
4Alex Rins01:24.221+0.41623307.6— / ———
5Pol Espargaro01:24.254+0.44922315.7Medium / Medium——
6Marc Marquez01:24.475+0.67024313.9Medium / Medium1:25.204—10Medium
7Maverick Viñales01:24.492+0.68725310.3— / ———
8Fabio Quartararo01:24.580+0.77526307.6Soft / Medium——
9Johann Zarco01:24.580+0.77522314.8Soft / Medium——
10Jack Miller01:24.827+1.02221315.7Medium / Medium——
11Daniel Pedrosa01:24.850+1.04521307.6— / ———
12Francesco Bagnaia01:24.915+1.11026313.0Soft / Medium1:25.292+0.10%8Medium
13Alex Marquez01:24.959+1.15423313.0Soft / Medium——
14Luca Marini01:25.207+1.40222309.4— / ———
15Miguel Oliveira01:25.238+1.43314311.2Medium / Medium——
16Valentino Rossi01:25.264+1.45922307.6Soft / Medium——
17Jorge Martin01:25.316+1.51122315.7Soft / Soft——
18Brad Binder01:25.317+1.51222313.0— / ———
19Danilo Petrucci01:25.409+1.60420304.2Medium / Medium——
20Iker Lecuona01:25.499+1.69420308.5Medium / Medium——
21Enea Bastianini01:25.585+1.78021313.0— / ———
22Lorenzo Savadori01:25.793+1.98821305.9Medium / Medium——
23Cal Crutchlow01:26.090+2.28520306.8Soft / Medium——
FP2 · 06.08 partly wet
Pos.RiderBest lapGapLapsTop km/hTyres (front / rear)Long-run pacePace gapn runRun rear
1Lorenzo Savadori01:31.304—19299.1Wet-Medium / Wet-Medium1:36.348+2.41%6Wet-Soft
2Johann Zarco01:31.458+0.15421304.2Wet-Soft / Wet-Soft1:35.138+1.12%10Wet-Soft
3Joan Mir01:31.566+0.26218303.3Wet-Medium / Wet-Medium1:36.206+2.26%5Wet-Soft
4Francesco Bagnaia01:32.182+0.87821309.4Wet-Soft / Wet-Soft1:35.601+1.61%11Wet-Soft
5Aleix Espargaro01:32.231+0.92712299.1Wet-Soft / Wet-Soft1:37.714+3.86%6Wet-Soft
6Alex Rins01:32.311+1.00718303.3Wet-Soft / Wet-Soft1:36.202+2.25%9Wet-Soft
7Alex Marquez01:32.445+1.14116305.0Wet-Soft / Wet-Soft1:35.132+1.11%5Wet-Soft
8Iker Lecuona01:32.543+1.23920300.0Wet-Medium / Wet-Medium1:34.084—12Wet-Soft
9Maverick Viñales01:32.685+1.38113299.1Wet-Soft / Wet-Soft——
10Marc Marquez01:32.841+1.53714302.5Wet-Soft / Wet-Soft1:34.748+0.71%8Wet-Soft
11Enea Bastianini01:33.024+1.72021303.3Wet-Soft / Wet-Soft1:36.625+2.70%13Wet-Soft
12Luca Marini01:33.152+1.84818300.8Wet-Soft / Wet-Soft1:34.848+0.81%11Wet-Soft
13Pol Espargaro01:33.415+2.11116307.6Wet-Soft / Wet-Soft1:36.151+2.20%9Wet-Soft
14Jack Miller01:33.453+2.14914305.0Wet-Soft / Wet-Soft1:34.734+0.69%8Wet-Soft
15Fabio Quartararo01:33.498+2.19418297.5Wet-Soft / Wet-Soft1:35.107+1.09%13Wet-Soft
16Brad Binder01:33.589+2.28519304.2Wet-Medium / Wet-Soft1:35.420+1.42%13Wet-Soft
17Takaaki Nakagami01:33.658+2.35415301.6Wet-Soft / Wet-Soft1:35.910+1.94%6Wet-Soft
18Danilo Petrucci01:33.684+2.38015295.8Wet-Soft / Wet-Soft1:35.298+1.29%12Wet-Soft
19Jorge Martin01:33.906+2.60220307.6Wet-Soft / Wet-Soft1:35.727+1.75%8Wet-Soft
20Cal Crutchlow01:33.954+2.65019298.3Wet-Soft / Wet-Soft1:36.656+2.73%13Wet-Soft
21Daniel Pedrosa01:33.954+2.65017295.8Wet-Soft / Wet-Medium1:36.692+2.77%7Wet-Soft
22Valentino Rossi01:34.582+3.27820298.3Wet-Soft / Wet-Soft1:35.640+1.65%8Wet-Soft
RetiredMiguel Oliveira—00.0— / ———
FP3 · 07.08 partly wet
Pos.RiderBest lapGapLapsTop km/hTyres (front / rear)Long-run pacePace gapn runRun rear
1Francesco Bagnaia01:23.114—23317.6— / ———
2Fabio Quartararo01:23.142+0.02824310.3Medium / Soft1:24.011+0.08%5Medium
3Maverick Viñales01:23.262+0.14821311.2Medium / missing1:23.942—5Medium
4Jorge Martin01:23.294+0.18020316.7— / ———
5Joan Mir01:23.387+0.27323308.5Medium / Soft——
6Johann Zarco01:23.487+0.37322315.7Medium / Soft——
7Marc Marquez01:23.513+0.39921314.8— / ———
8Aleix Espargaro01:23.594+0.48019311.2Hard / Soft——
9Jack Miller01:23.731+0.61723314.8Soft / Soft——
10Takaaki Nakagami01:23.740+0.62622313.0Medium / Medium——
11Pol Espargaro01:23.757+0.64321318.5— / ———
12Daniel Pedrosa01:23.758+0.64423313.0Medium / Soft1:24.989+1.25%13Soft
13Alex Rins01:23.766+0.65224309.4Medium / Medium——
14Alex Marquez01:23.789+0.67524315.7— / ———
15Brad Binder01:23.799+0.68522313.0Hard / Soft——
16Miguel Oliveira01:23.935+0.82122310.3Medium / Soft1:25.479+1.83%5Medium
17Iker Lecuona01:24.159+1.04521308.5— / ———
18Danilo Petrucci01:24.342+1.22821307.6Medium / Soft——
19Valentino Rossi01:24.381+1.26721305.9Medium / Soft1:24.984+1.24%7Medium
20Enea Bastianini01:24.384+1.27022313.9— / ———
21Luca Marini01:24.403+1.28918311.2— / ———
22Lorenzo Savadori01:24.437+1.32323310.3Hard / Soft1:25.248+1.56%4Medium
23Cal Crutchlow01:24.644+1.53021305.0Medium / Medium1:25.603+1.98%5Medium
FP4 · 07.08
Pos.RiderBest lapGapLapsTop km/hTyres (front / rear)Long-run pacePace gapn runRun rear
1Fabio Quartararo01:23.816—16307.6Medium / Medium1:23.926—5Medium
2Francesco Bagnaia01:24.022+0.20617319.5Hard / Medium1:24.400+0.57%6Medium
3Maverick Viñales01:24.024+0.20820311.2Medium / Medium1:24.550+0.74%11Medium
4Joan Mir01:24.180+0.36413305.9Medium / Medium1:24.279+0.42%5Medium
5Marc Marquez01:24.273+0.45718311.2Hard / Medium1:24.648+0.86%5Soft
6Daniel Pedrosa01:24.409+0.59316315.7Hard / Medium1:24.889+1.15%10Medium
7Takaaki Nakagami01:24.510+0.69419310.3Medium / Soft1:26.145+2.64%5Soft
8Jack Miller01:24.521+0.70515313.0Hard / Soft1:24.732+0.96%5Soft
9Enea Bastianini01:24.589+0.77316313.0Hard / Medium——
10Miguel Oliveira01:24.634+0.81815307.6Hard / Medium1:24.977+1.25%10Medium
11Jorge Martin01:24.744+0.92816319.5Medium / Medium——
12Johann Zarco01:24.819+1.00316313.9Medium / Soft——
13Alex Marquez01:24.831+1.01517312.1Hard / Soft1:24.947+1.22%5Soft
14Pol Espargaro01:24.842+1.02616313.9Hard / Medium——
15Brad Binder01:24.856+1.04015311.2Hard / Medium——
16Cal Crutchlow01:24.868+1.05218303.3Hard / Medium1:25.188+1.50%6Medium
17Danilo Petrucci01:24.926+1.11016311.2Hard / Medium1:25.254+1.58%6Medium
18Luca Marini01:25.027+1.21115311.2Medium / Medium——
19Valentino Rossi01:25.051+1.23517306.8Medium / Medium1:25.420+1.78%10Medium
20Aleix Espargaro01:25.096+1.28017311.2Hard / Medium1:25.400+1.76%10Medium
21Alex Rins01:25.141+1.32516309.4Medium / Medium1:25.558+1.95%6Medium
22Lorenzo Savadori01:25.172+1.35615308.5Hard / Medium——
23Iker Lecuona01:25.561+1.74512305.0Hard / Medium——
Q1 · 07.08
Pos.RiderBest lapGapLapsTop km/hTyres (front / rear)
1Alex Marquez01:23.547—9313.0Medium / Soft
2Miguel Oliveira01:23.552+0.0059309.4Hard / Soft
3Alex Rins01:23.585+0.0388308.5Medium / Soft
4Daniel Pedrosa01:23.730+0.1839312.1Hard / Soft
5Pol Espargaro01:23.971+0.4248315.7Hard / Medium
6Brad Binder01:24.050+0.5038311.2Hard / Soft
7Valentino Rossi01:24.097+0.5509304.2Medium / Soft
8Luca Marini01:24.115+0.5688309.4Medium / Soft
9Iker Lecuona01:24.141+0.5948305.9Hard / Soft
10Enea Bastianini01:24.245+0.6989312.1Medium / Soft
11Lorenzo Savadori01:24.405+0.8587306.8Hard / Soft
12Danilo Petrucci01:24.465+0.9188307.6Hard / Soft
13Cal Crutchlow01:24.513+0.9668305.0Medium / Soft
Q2 · 07.08
Pos.RiderBest lapGapLapsTop km/hTyres (front / rear)
1Jorge Martin01:22.994—9316.7— / —
2Francesco Bagnaia01:23.038+0.0449315.7— / —
3Fabio Quartararo01:23.075+0.0818309.4Medium / Soft
4Jack Miller01:23.300+0.3069315.7Medium / Soft
5Joan Mir01:23.322+0.32810309.4Medium / Soft
6Johann Zarco01:23.376+0.3829313.0Medium / Soft
7Aleix Espargaro01:23.448+0.4549311.2— / —
8Marc Marquez01:23.489+0.4958313.9— / —
9Maverick Viñales01:23.508+0.5148309.4Soft / Soft
10Takaaki Nakagami01:23.536+0.5429312.1Medium / Soft
11Alex Marquez01:23.841+0.8479313.9Medium / Soft
12Miguel Oliveira01:23.944+0.9504308.5Hard / Soft
Warm Up · 08.08 partly wet
Pos.RiderBest lapGapLapsTop km/hTyres (front / rear)Long-run pacePace gapn runRun rear
1Marc Marquez01:31.403—13302.5Wet-Medium / Wet-Medium1:32.824+0.05%9Wet-Medium
2Jack Miller01:31.451+0.04813307.6Wet-Medium / Wet-Medium1:33.021+0.26%7Wet-Medium
3Maverick Viñales01:31.662+0.25913299.1Wet-Soft / Wet-Medium1:33.101+0.35%10Wet-Medium
4Iker Lecuona01:31.695+0.29213300.8Wet-Medium / Wet-Medium1:32.776—11Wet-Medium
5Francesco Bagnaia01:31.892+0.48913309.4Wet-Medium / Wet-Medium1:33.489+0.77%11Wet-Medium
6Johann Zarco01:32.514+1.11112305.9Wet-Medium / Wet-Medium1:33.498+0.78%8Wet-Medium
7Jorge Martin01:32.518+1.11512305.9Wet-Medium / Wet-Medium1:32.902+0.14%5Wet-Medium
8Alex Marquez01:32.628+1.22512302.5Wet-Medium / Wet-Medium1:33.761+1.06%9Wet-Medium
9Aleix Espargaro01:32.647+1.24413300.8Wet-Soft / Wet-Soft1:35.534+2.97%11Wet-Soft
10Miguel Oliveira01:32.677+1.27412302.5Wet-Medium / Wet-Medium1:33.418+0.69%5Wet-Medium
11Danilo Petrucci01:32.844+1.44112298.3Wet-Medium / Wet-Medium1:34.603+1.97%9Wet-Medium
12Pol Espargaro01:32.870+1.46712308.5Wet-Soft / Wet-Soft1:33.887+1.20%6Wet-Soft
13Valentino Rossi01:32.982+1.57912296.7Wet-Medium / Wet-Medium1:35.780+3.24%10Wet-Medium
14Daniel Pedrosa01:33.047+1.64413299.1Wet-Medium / Wet-Medium1:34.098+1.43%10Wet-Medium
15Brad Binder01:33.091+1.68811300.0Wet-Medium / Wet-Medium——
16Fabio Quartararo01:33.113+1.71012295.0Wet-Soft / Wet-Medium1:34.004+1.32%10Wet-Medium
17Lorenzo Savadori01:33.331+1.92812293.4Wet-Medium / Wet-Medium1:34.729+2.11%7Wet-Medium
18Enea Bastianini01:33.486+2.08312305.0Wet-Medium / Wet-Soft1:35.148+2.56%8Wet-Soft
19Joan Mir01:33.487+2.0849297.5Wet-Medium / Wet-Medium——
20Alex Rins01:33.541+2.13812302.5Wet-Medium / Wet-Medium1:35.022+2.42%7Wet-Medium
21Takaaki Nakagami01:33.782+2.37912303.3Wet-Medium / Wet-Medium1:34.516+1.88%8Wet-Medium
22Luca Marini01:33.830+2.42712300.8Wet-Medium / Wet-Soft1:34.498+1.86%9Wet-Soft
23Cal Crutchlow01:33.872+2.46912295.8Wet-Soft / Wet-Medium1:35.938+3.41%8Wet-Medium
Race · 08.08
Pos.RiderTime / gapPointsLapsTyres (front / rear)Long-run pacePace gapn runRun rear
1Jorge Martin38:07.8792527Medium / Medium1:24.464—22Medium
2Joan Mir+1.5482027Medium / Medium1:24.480+0.02%24Medium
3Fabio Quartararo+9.6321627Medium / Medium1:24.863+0.47%24Medium
4Brad Binder+12.7711327Hard / Medium1:24.950+0.58%22Medium
5Takaaki Nakagami+12.9231127Medium / Medium1:24.872+0.48%21Medium
6Johann Zarco+13.0311027Medium / Soft1:24.951+0.58%25Soft
7Alex Rins+14.839927Medium / Medium1:24.980+0.61%21Medium
8Marc Marquez+17.953827Hard / Medium1:25.109+0.76%22Medium
9Alex Marquez+19.059727Medium / Medium1:25.186+0.86%22Medium
10Daniel Pedrosa+19.389627Hard / Medium1:25.188+0.86%25Medium
11Francesco Bagnaia+21.667527Hard / Soft1:25.218+0.89%22Soft
12Enea Bastianini+25.267427Medium / Medium1:25.243+0.92%19Medium
13Valentino Rossi+26.282327Medium / Medium1:25.388+1.09%22Medium
14Luca Marini+27.492227Medium / Medium1:25.348+1.05%24Medium
15Iker Lecuona+31.076127Hard / Medium1:25.459+1.18%20Medium
16Pol Espargaro+31.150027Medium / Medium1:25.520+1.25%20Medium
17Cal Crutchlow+40.408027Medium / Medium1:25.793+1.57%21Medium
18Danilo Petrucci+48.114027Hard / Medium1:25.468+1.19%24Medium
RetiredAleix Espargaro04Hard / Medium——
RetiredJack Miller018Hard / Medium1:24.654+0.23%14Medium
Did not startLorenzo Savadori00— / ———
RetiredMaverick Viñales027Medium / Medium1:25.185+0.85%16Medium
RetiredMiguel Oliveira014Hard / Medium1:25.036+0.68%11Medium

Official classification of each session (Dorna). Best lap and the tyres used on it: official FIM PDFs. Long-run pace: median of the clean laps in long runs (5 flying laps or more); blank if the rider did none. Every rider runs their own programme and fuel load, so long-run pace only compares within the same session.

How it’s calculated

For each session with lap data (since 2018) and each rider, two readings. Time attack: their best valid lap (neither cancelled nor a pit lap), with the tyre they were on, and the gap to the best in the session in seconds and in %. Race sim: the median of the clean laps from their long runs (at least 5 consecutive fast laps; in the race and sprint, the whole race), with a minimum of 4 laps, and the gap to the best long-run pace of the session. Top speed and the % of laps done on slicks (below 100 means the track was wet) are also added.

Keep in mind. If a rider has not done any long run, their race sim is left blank. Compare only within the same session: each team tests different things (fuel, tyres, maps) and a long run on old rubber is not comparable with one on fresh rubber.

Long-run pace in practice

RiderPaceGapDeg. s/lapRearn
Fabio Quartararo1:23.926—+0.275Medium5
Joan Mir1:24.228*+0.302+0.562Medium4
Johann Zarco1:24.793*+0.867+0.344Medium4
Jorge Martin1:24.830+0.904+0.457Medium5
Alex Rins1:25.141+1.215+0.217Medium7
Valentino Rossi1:25.302+1.376+0.508Medium9
Luca Marini1:25.600+1.674+0.308Medium6
Cal Crutchlow1:25.685*+1.759+0.729Medium3

Estimated practice pace: median of the clean laps on the medium compound used in practice. It is an estimate: every team runs its own programme and fuel load. n = laps used (at least 3). * = only 3 or 4 laps: pace less reliable.

How it’s calculated

Three paces per rider and GP (since 2018). Practice: estimated race pace from laps done on medium front and rear tyres that are already used (fresh rubber inflates the pace), not counting FP1 (unrepresentative time of day and track conditions); only laps no more than 0.20 s per kilometre above the same rider’s best lap in these conditions are kept (0.25 in Thailand and Malaysia), and the median is taken. Race and sprint: median of the actual clean laps, with a minimum of 4. The pace per km, the scatter, the sectors, the tyre age range of the laps used and, as context, the rider’s typical degradation on the medium in practice are also given.

Keep in mind. Practice pace is an estimate: we do not know how much fuel or which engine map each rider is running, which is why it is not used to forecast the race. Compare riders within the same GP; across circuits, use the pace per km with caution.

Who will make it to Q2

C21a
Pred.RiderP(through)Actual in Q1
1Daniel Pedrosa57%4
2Brad Binder42%6
3Miguel Oliveira33%2 ✓
4Alex Rins20%3
5Pol Espargaro17%5
6Danilo Petrucci9%12
7Valentino Rossi9%7
8Lorenzo Savadori4%11
9Enea Bastianini2%10
10Alex Marquez3%1 ✓
11Cal Crutchlow4%13
12Luca Marini2%8
13Iker Lecuona0%9

Forecast after Practice for the riders going to Q1. Two go through. Q1 is fairly predictable, but 55% for the favourite still means a miss almost half the time.

How it’s calculated

For the riders who go to Q1 (those who did not finish in the top 10 of Friday’s Practice), the Q1 riders are ranked by one-lap pace in practice: each rider’s average position among the Q1 riders in Practice (PR) and FP2, counting only valid laps (neither cancelled nor pit laps). If there is no FP2 yet (Friday evening) or it is a GP before 2023, their best lap across all of practice is used. The probability of going through is the historical frequency: of all riders who held that same predicted position in previous Q1 sessions, what percentage finished in the top 2. At least 10 previous cases are needed to give a number.

Keep in mind. Q1 is fairly predictable (the predicted first place goes through roughly 55 times out of 100), but practice is not qualifying: each team runs its own programme. On Friday evening the forecast is weaker than on Saturday morning, once FP2 is in.

Pole and front row

C21
Pred.RiderP(pole)P(front row)P(top 6)Actual in Q2
1Joan Mir36%68%92%5
2Fabio Quartararo28%53%85%3
3Johann Zarco16%48%79%6
4Aleix Espargaro3%32%67%7
5Maverick Viñales3%27%54%9
6Jack Miller6%21%54%4
7Takaaki Nakagami1%12%43%10
8Francesco Bagnaia2%11%36%2
9Miguel Oliveira1%7%28%12
10Marc Marquez2%7%21%8
11Jorge Martin1%11%26%1
12Alex Marquez0%3%17%11

Forecast after Q1, from Practice and FP2. These are probabilities, not a grid: the favourite takes pole about half the time.

How it’s calculated

The same predictor as in Q1, applied to the 12 riders in Q2 (the top 10 from Practice and the 2 who come through from Q1): each rider’s average position among the Q2 riders in Practice and FP2, using valid laps; before 2023, the best lap across all of practice. The probabilities of pole, front row (top 3 in Q2) and top 6 come from history: of all riders predicted in that same position in previous Q2 sessions, how many took pole, the front row or a top 6 (with a minimum of 10 cases). It is published on Saturday after Q1 and, once Q2 ends, it stays next to the actual result.

Keep in mind. Since 2023, the favourite takes pole 49% of the time and the forecast captures 55% of the front row: qualifying is much more open than the race. The probability does not look at who the rider is, only at the position practice puts them in.

Grid penalties

Pending · no data yet

Sprint forecast

C13s

Win and podium chances in Saturday’s sprint, based on the grid.

Pending · no data yet

Race forecast

C13

Forecast based on the starting grid.

RiderGridWinPodiumTop 5Top 10P(DNF)Final
Jorge Martin130%57%70%79%20%1
Francesco Bagnaia218%43%56%66%32%11
Fabio Quartararo316%47%64%82%15%3
Jack Miller410%34%53%71%26%—
Joan Mir57%29%51%75%18%2
Johann Zarco66%26%46%77%16%6
Aleix Espargaro74%18%35%65%26%—
Marc Marquez83%15%32%72%15%8
Maverick Viñales92%10%25%71%11%—
Takaaki Nakagami101%8%19%63%15%5
Alex Marquez111%4%13%51%25%9
Miguel Oliveira121%3%11%51%14%—
Alex Rins130%3%8%40%21%7
Daniel Pedrosa140%2%7%38%13%10
Pol Espargaro150%1%4%27%20%16
Brad Binder160%1%2%22%21%4
Valentino Rossi170%1%2%17%13%13
Luca Marini180%0%1%13%8%14
Iker Lecuona190%0%1%7%34%15
Enea Bastianini200%0%1%6%21%12
Lorenzo Savadori210%0%1%4%29%—
Danilo Petrucci220%0%0%3%20%18
Cal Crutchlow230%0%0%2%28%17
How it’s calculated

The starting point is the official grid, because it is the best predictor of the finishing order. From there the race is simulated 4,000 times, adding three sources of randomness drawn only from previous races (since 2015): how many places are gained or lost on the first lap, how much the order shuffles from the first lap to the flag, and the probability that each rider retires (their historical retirement rate, smoothed towards the field average as if we added 6 “average” races, and capped at 60%). The probabilities (win, podium, top 5, top 10, retirement) are the percentage of simulations in which it happens and already include the risk of retiring. The expected position and the 80% interval (the range of positions they finish in 8 times out of 10) are calculated only over the simulations in which the rider finishes. The post-sprint version (Saturday afternoon) replaces the starting point with a mix of half grid, half actual pace in the sprint (median of the laps excluding the first, cancelled laps and pit laps, with a minimum of 5 laps); the website always shows the most recent version.

Keep in mind. Before the sprint the model predicts the order just as well as the grid (over 213 races, 0.76 in both cases): its value is that the probabilities are honest (when it says 35%, it happens roughly 35% of the time); the post-sprint version is the only one that genuinely beats the grid. It is deliberately cautious: it never gives more than a 70% podium chance, and the 80% interval is right slightly more often than it claims (83%). It is not recalculated during the race.

What the sprint changed

C13b

Who rises and who drops in the race forecast after the sprint.

Pending · no data yet

Sprint pace

Pending · no data yet
Preview

Before the race

What to expect this weekend: race and qualifying outlook, the weight of the grid and the weather.

Who rules each sector

C6
S1 · MartinS2 · QuartararoS3 · MirS4 · Quartararo

Finish line S1 S2 S3 S4 · 4,347 m per lap

Approximate sectors: estimated from the time spent in each sector (typical error 5 to 10% of a lap) until we have the official split points.

© OpenStreetMap contributors

Fastest per sector: 2021

Median gap to the fastest rider in each sector within each session, across all seasons at this circuit; active riders only. The name on the layout is the sector leader. Sector split points on the map are approximate.

How it’s calculated

Sector map

The lap is divided into the 4 official timing sectors. In each dry session (laps on slicks, since 2018), for each rider with at least 3 clean laps their best time in each sector is taken and compared with the best in the session for that sector: 0% is the fastest, 0.5% means half a percent slower. Then the median across all sessions is taken (at least 3 in total since 2018, at least 2 in a given season). To draw the sectors on the track layout, where each sector starts and ends is approximated from how the time is split: if sector 1 takes 25% of the lap, it covers the first 25% of the layout (based on clean race laps from the most recent season).

Keep in mind. A sector is a different physical stretch at each circuit: it tells you where a rider is fast, not whether they are good on the brakes or through corners. The drawn boundaries are approximate (the typical error is 5-10% of the lap) because they assume the same average speed in all sectors, until the official splits are loaded by hand.

Circuit layout

The track drawing comes from OpenStreetMap: of all the segments tagged as a race track, the closed circuit whose length is closest to the official one is taken, the direction of racing is deduced from the one-way tags (or from the number of right and left corners) and the finish line is placed on the pit lane. The elevation of each point comes from a smoothed digital terrain model (Copernicus, 90 m cells, via Open-Meteo), and enables the 3D relief. There are currently 25 circuits. © OpenStreetMap contributors (ODbL licence).

Keep in mind. The elevation is that of the terrain at a 90 m resolution, not measured on the asphalt: it is useful for seeing climbs and descents, not for giving exact gradients. The position of the sectors on the layout is approximate (see “Sector map”).

A track for grid position, or an open one?

C15
Pending · no data yet

The last race here in numbers

2020 edition

23
Overtakes
2
Lead changes
3 leaders
1/12
Laps led by the winner
Miguel Oliveira
0.316 s
Closest finish

Comeback of the day: Johann Zarco, from P22 to P14.

Longest battle: Aleix Espargaro vs Fabio Quartararo (12 laps).

There was a red flag.

Overtakes are counted at the finish line: moves undone within the same lap are not seen. It is a measure of movement, not an official statistic.

How it’s calculated

Everything comes from the order of crossing the line on each lap (official lap-by-lap position sheet, since 2010). An overtake is a pair of riders who swap order between two consecutive laps (moving up because someone retires does not count). A battle is two riders running less than 1 second apart for at least 5 consecutive laps. Lead changes, different leaders, laps led by the winner, the closest finish (gap of 2nd at the line), the biggest comeback (from the official grid to the finishing position) and whether there was a red flag are also counted. Per rider: position on the first lap and at the finish, laps led, overtakes made and suffered, best and worst position.

Keep in mind. Only what happens at the finish line is seen: an overtake and a counter-overtake within the same lap do not show up. It is a measure of the race’s “movement”, not an official overtaking statistic.

Race pace at the last edition

C1

2020 edition

RiderPaceGapDeg. s/lapRearn
Pol Espargaro1:24.188—+0.406Medium8
Andrea Dovizioso1:24.225+0.037+0.226Soft9
Miguel Oliveira1:24.268+0.080+0.193Medium10
Jack Miller1:24.276+0.088+0.105Soft9
Brad Binder1:24.288+0.100+0.327Medium8
Alex Rins1:24.322+0.134+0.217Medium8
Takaaki Nakagami1:24.382+0.194+0.359Soft10
Joan Mir1:24.410+0.222+0.562Medium10
Valentino Rossi1:24.561+0.373+0.508Soft9
Johann Zarco1:24.583+0.395+0.344Soft10

Net race pace: median of clean laps, excluding lap 1, cancelled laps and pit laps. Degradation mixes tyre, fuel and traffic.

How it’s calculated

Three paces per rider and GP (since 2018). Practice: estimated race pace from laps done on medium front and rear tyres that are already used (fresh rubber inflates the pace), not counting FP1 (unrepresentative time of day and track conditions); only laps no more than 0.20 s per kilometre above the same rider’s best lap in these conditions are kept (0.25 in Thailand and Malaysia), and the median is taken. Race and sprint: median of the actual clean laps, with a minimum of 4. The pace per km, the scatter, the sectors, the tyre age range of the laps used and, as context, the rider’s typical degradation on the medium in practice are also given.

Keep in mind. Practice pace is an estimate: we do not know how much fuel or which engine map each rider is running, which is why it is not used to forecast the race. Compare riders within the same GP; across circuits, use the pace per km with caution.

Winners here

  • 2021Jorge MartinDucati
  • 2020Miguel OliveiraKTM

Attrition here

Average here 11% · global 19%
YearDNFs%
20214/2218%
20201/225%
How it’s calculated

For each full-length race, how many riders who took the start were not classified (crash, mechanical failure, disqualification or not completing enough laps) and what % of the field they represent. Those who do not start count neither as starters nor as retirements. It is the same definition of retirement used by the forecast.

Keep in mind. It does not distinguish the reason for the retirement: a solo crash, a multi-rider pile-up at the first corner and a mechanical failure all count the same.

Tyres at the last edition

2020 edition

RearShareRel. paceDeg. s/lapWinsPodiumsAvg. pos.
Soft62%+0.55%−0.0110112.7
Medium38%+0.21%+0.016128.3

Rear compound in the race. Pace is relative to the best of the session; degradation includes fuel and traffic, so only compare within the same race.

How it’s calculated

In each race and sprint since 2018, a rider’s compound is the one that appears on most of their laps (front and rear). Per rider: the median of the clean laps, the % gap to the best pace of the session, the degradation (how many seconds per lap they slow down on average, calculated if they have at least 6 clean laps), the grid and the result; “minority” means their rear compound is not the one chosen by most of the field. Per compound: what % of the field chose it, the median pace and degradation, wins, podiums, average finishing position of those who finish and % of retirements (out of those who started on that compound). It helps answer “did the minority gamble pay off?”.

Keep in mind. Degradation mixes the tyre, the fuel being burned and traffic, so it only makes sense to compare riders within the same race, not across circuits. A compound chosen by 1 or 2 riders gives figures that depend heavily on who ran it.