After 5 races since he replaced Ponsson (one raced missed due to injury), now is time to wonder… how well has Jordi Torres rode the Avintia Ducati GP16?

If we look how far each rider have finished from the race winner for the 5 weekends that Torres has been in the MotoGP grid…

… we see that Torres has been very close to the man he has been replacing. Torres finished only 0.5s behind Simeon on his debut race in MotoGP. He was two seconds adrift in Thailand and only 0.2s in Japan, both races less than 40 seconds form the race winner. He got a worse result in Philip Island, where he crossed the chequered flag more than a minute behind the race winner, and over 20 seconds behind Simeon. Torres did not race in Malaysia after he got injured during practice.

But that is not a fair comparison, as Torres has been riding a two year old Ducati GP16, and Simeon a theoretically faster Ducati GP17.

If we compare the time differences to race winner on the races that Xavier Simeon rode the Ducati GP16 (before Rabat’s crash) and Torres results on the exact same bike we can see that Torres has clearly outperformed the man he was brought in to replace.

On a Ducati GP16 Torres has managed to finish a race under 40 seconds behind the race winner on two out of his four appearances in MotoGP, while Simeon closest finish to the winner in his eleven attempts has been 46.7 seconds in Qatar. The average time distance to race winner for Torres has been 50.9 seconds, comparable to Karel Abraham’s performance on the other DucatiGP 16 in the grid, and ten seconds faster than the average performance of Simeon on the GP16.

Note that races where a rider was lapped or did not finish a race are excluded from the analysis.

And while Torres results on the GP16 have been better than the previous results from Simeon on the same bike, Simeon’s results have been far from what Rabat and other riders have achieved on the Ducati GP17 during the season.

The closest that Simeon has finished to the race winner on the GP17 has been 37.2 seconds (37th best result of a Ducati GP17 this season, in terms of distance to winner), more than double the distance to race winner that Rabat has achieved (15.2s), and a far cry from the 19 times that Bautista and Miller have finished less than 20 seconds from the race winner.

In fact Simeon has finished further from the leader on all occasions that he rode Rabat’s GP17 (37.2 to 59.0 seconds), than Rabat’s worst result in Germany (29.0s).

Another interesting inside is that – as expected – Simeon has been considerably faster on the GP17 than on the GP16. His mean distance to the winner dropped from 60.8s to 44.8s, while the closest he has been to the race winner on a GP16 was 46.7s, compared to his best results on a GP17 of 37.2s.

With Rabat recently stating that he will not be able to race in Valencia, Torres and Simeon will have their last chance to score a solid result on the Ducati GP16 and GP17 respectively. Will Torres finally beat Simeon, despite racing on a one year older machinery? Will Simeon finally manage to finish as close to the leaders as Rabat has been doing during the season?

In this case, the weapon of choice to make the plots were python with pandas and seaborn. And while usually these two allow you to do nice plots in a couple of lines, I ended creating a >100 lines plot function in order to show and tune the distribution of time differences and the corresponding annotations.

]]>Some will bring home a big smile, like Marc Marquez who won the world championship in Japan in front of the big bosses, or Alex Rins with 2 podiums and a 5th position. Some will come home a tad more disappointed… Petrucci for example, who only managed a top 9 as his best result.

And the rest?

The following graph shows the difference in average points per race during the 3 flyovers and the average points per race during the previous 14 races.

We can see that Rins has improved the most, with 8.4 points more per race than befora. Bautista (5.9), Viñales (5.2), Morbidelli (3.3) and Smith (3.2) complete the top 5 riders who have improved the most during the packed 3 weeks.

At the bottom of the table we find Lorenzo (-9.3) – who did not start any of the 3 races – accompanied by some of the top riders in the championship: Dovizioso (-5.2), Rossi (-4.6), Petrucci (-3.0), and Marquez (-2.7).

Another way to show that change in scored points is to use an arrow plot, with arrows starting at the average points scored during the first 14 races of the season, and ending at the average points scored during the three flyovers. This time riders are sorted by average points during the flyovers.

Marquez scored the most points per race during the flyovers (16.7) despite a decrease in points, as he averaged 19.4 points per race on the previous races. Viñales and Rins both scored 15.7 points per race over the 3 flyovers, Viñales improving by nearly 50% and Rins more than doubling the average points he scored per race. Bautista is the fourth best performing rider during the flyovers after doubling the points per race (5.1 to 11.0). Morbidelli, (2.4 to 5.7), Syahrin (2.0 to 4.0), and Smith (1.4 to 3.7) also doubled their scoring points during the last three races.

]]>Christophe Ponsson, who currently races in the Spanish Superstock 1000 series, landed the seat despite having zero experience in a MotoGP bike or anything similar. Ponsson was so unfamiliar with a MotoGP prototype bike, that he felt that learning to ride his Ducati GP16 was “as if I start again riding on a bike”.

Ponsson slipped into his leaders and ended FP1 with a best lap of 1’40.038, 7.4 seconds (and out of the 107% rule) slower than the fastest lap of the session, and 4.0 seconds afar from the rider in front of him.

In FP2, he improved his lap time by 2 seconds and ended 6.0 seconds behind the session’s best lap, this time inside the 107% rule. He kept improving and on Saturday he qualified with a lap of 1’37.180, 4.8 seconds slower than Lorenzo’s pole position lap. On Sunday, Ponsson finished the race dead last with a fastest lap of 1’37.375, 4.7 seconds slower than the race fastest lap.

So Ponsson speed increased over the weekend, he started the weekend 7.4 seconds of the pace (a bit more if you compare his very first laps), and ended 4.7 seconds behind the fastest pace.

Best lap times are a good measurement to measure the performance of a rider over a whole session, however it does not capture the evolution during the session, lap by lap. Did Ponsson become faster and faster at each lap of each session? How much did he improve per lap during the race, considering that he rode by himself all 26 laps?

If we want to look at the pace improvement during a session we need to take into account the lap times for all laps of the session.

In the previous plot we can see the lap times of Ponsson and Dovizioso (for reference). We can see that both riders had a slow first lap, starting from the grid, and then they settled on a fairly constant pace, Dovizioso close to 93 seconds (1’33”), and Ponsson around 98 seconds (1’38”). In addition, Dovizioso lost around 2 seconds in his last lap, celebrating his victory, and Ponsson slowed down considerable on the laps that he was being lapped.

But if we look closely, we can see that Ponsson in fact improved a bit during the race, starting with low 1’38” and dropping to high 1’37” towards the end of the race.

But how can we measure that subtle improvement between laps?

One approach is to fit the data into a relatively simple model that captures the pace at each lap, and how it changes lap per lap. The simplest of models is a linear regression, where we assume a constant pace improvement per lap. But we need to make sure that the lap times from slow laps (start of the race, blue flags, or celebration laps) are not used to compute the pace. For that we need a robust regression.

Thus, the motogpdata elders, decide to use a RANSAC regressor (sklearn) to robustly fit a straight line over the lap times. The *robust* bit is important, because it is the bit that means that the algorithm will decide for us which laps should be used to compute the pace and which not. RANSAC algorithms do that by splitting the data points randomly into inliers (points to use to fit the model) and outliers (points discarded as being to far away from the model), then it fits the model, computes the residual, and tries another random split of the points. After a few iterations the best model is selected.

So we took the data from the MotoGP statistics website and put together a small spreadsheet with Ponsson’s lap times and the lap times of Dovizioso for comparison, as Dovizioso was the winner of the race and fast all weekend.

We then used the magic oh Python and pandas to load that data in a one liner, parse and clean it a bit, and used the lap times to perform the linear regression using RANSAC.

The greyed out points are lap times considered outliers by the RANSAC algorithm, and thus have not been used to compute the pace improvement.

The line for each rider represent the estimated pace during the session. The nearly horizontal lines indicate that the race pace did not change much during the race. Ponsson improved 0.018s per lap, compared with a 0.005s improvement per lap for Dovizioso. Ponsson started with a pace of 1’38.2 and ended 0.4s faster with a pace of 1’37.8, as we had inferred on the previous plot. Dovizioso started with a pace of 1’33.3, and ended 0.1s faster, at 1’33.2. Ponsson ended the session 4.6 slower than Dovizioso.

We then repeated the analysis with the 6 other timed sessions of the weekend: FP1, FP2, FP3, FP4, Qualification, and Warm Up.

Ponsson did improve during each session, averaging a 0.2 seconds improvement per lap during the bulk of practice (FP1, FP2, and FP4). However between his pace at the end of FP4 (1’37.9) and at the end of the race in Sunday (1’37.8) he only improved by one tenth of a second over 45 laps.

With complete disregard for the fact that each session is different – that sometimes a rider is chasing a quick lap and others trying the wrong kind of tyres – we can crudely concatenate all laps from all sessions in chronological order and analysed how Ponsson pace improved along the entire weekend.

During the 109 laps analysed of Ponsson’s weekend, he averaged an improvement of 0.042 seconds per lap. In comparison, Dovizioso had an improvement roughly a third as big, at 0.015 seconds per lap.

However our linear model assumption that pace progressed uniformly during the weekend doesn’t seem to correspond with Ponsson lap times progression. In fact Ponsson improved a lot from FP1 to FP4, but not much during qualification, warm up, and race.

In order to capture that change in pace improvement we tried to fit a polynomial function to the data points, using the same RANSAC estimator and the magic of sklearn pipelines.

In this case, we can see that the model better captures the progression of Ponsson’s pace, with a pronounced improvement per lap between FP1 and FP4 and a much more reduced improvement towards the end.

So was Ponsson’s improvement good enough? Probably not.

While he ended the weekend 5.5 seconds faster than he started (see last plot), he was still 4.4 seconds per lap slower than the race winner. In addition, as the weekend progressed, his lap times improvements became smaller and smaller. He started the race with a pace of 1′.38.2 and ended with a pace 1′.37.8. During the 27 laps that he rode alone during the race, he only improved a tenth (0.02s per lap) compared of what he had improved during free practice sessions (0.20s per lap). This suggests that even if Ponsson was given more time, he would only improve marginally, and remain far behind any other rider.

That was in fact the general opinion around the paddock. Several riders argued that it was not safe to ride with a rider 4 seconds slower a lap, and the selection committee of Dorna, FIM, and IRTA refused Ponsson as a substitute rider, forcing Avintia to find a new rider. The Ducati GP16 was raced by Jordi Torres in Aragon.

[Code]

When deciding what function to fit into the data we need to be careful, fitting too complex models into poor data (small number of samples, too many outliers, etc) can lead to overfitting, see for example what happens when we use a third order polynomial on each session data separately:

In this case a cubic fit has too many parameters to estimate (4 parameters) with the given data (as low as 7 laps during qualification), and thus it is too flexible and unstable for the data we have, specially for sessions with low number of laps.

For instance, on the last plot we can see that during qualifying (7 laps) the model says that Ponsson’s pace started at 1’34.6 and ended at 1’39.4, which makes little sense. In this case, the pace calculated using linear regression seemed to better capture the real pace.

Also, while we could use the fitted functions to extrapolate when Ponsson’s pace would be similar to Dovizioso’s, one single race weekend is not enough data and we can be led to wrong conclusions, as very well illustrated in xkcd:

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In racing, a big chunk of glory (or agony) is consequence of the machine you ride. If not, ask Rossi how his two years in Ducati compare to the results he obtained while riding the Honda inherited from Doohan… Because of this, beating a teammate (or anyone riding a similar motorbike) becomes a rider’s imperative. Because if you beat someone on a similar machine, then it is the rider who did it. The flesh, not the hardware.

To visualise that, we grabbed the MotoGP 2017 results and measured how many points per race did each rider obtain compared with the average points per race of all riders on the same team. Using points per race – and not total points over the season – allows us to compare riders regardless of the number of races started. For instance, we can compare Michele Pirro, with 3 races, to Jonas Folger (13 races), or Dovizioso (18 race). We called this metric Points Over Average (POA) and was computed as:

\(POA = \frac{p}{n} – \sum\limits_{r \in R} \frac{p_r}{n_r} \)

where \(p\) is the number of points during the season and \(n\) the number of races started. \(p_r\) and \(n_r\) are the points and number of races started of rider \(r\), and \(r\) is one of the \(R\) riders with similar machinery, in this case all riders from the same team.

In other words, POA is the difference between points per race of a rider and the average points per race of all riders in the same team, himself included.

We used Tableau to plot the POA (vs. teammates) against the average points per race for all 2017 MotoGP riders:

Marc Marquez, has the highest number of points per race (16.56), so he is well on the right. He is also above the grey line, indicating that he obtained more points per race than the average Honda HRC rider (him and Pedrosa). Next to him, Dovizioso is higher up, indicating that he outperformed his teammates by a bigger margin that Marquez outperformed his teammate. Marquez had 2.44 points more than the average HRC rider, while Dovi dominated the Ducati garage with 3.65 points more than average. Dovi was the rider with higher POA (+3.65 POA), followed by Marquez (+2.44 POA), Zarco (+2.30 POA), Aleix Espargaro (+1.77 POA), Petrucci (+1.67 POA), and Miller (+1.57 POA).

Interestingly, Michele Pirro had more points per race (8.33) on the 3 wild cards than teammate Lorenzo (7.61), who spent all year struggling to be in terms with his Ducati.

Some teams had riders on different machinery: Pramac Racing had Petrucci on a Ducati GP17 and Scot Redding on a Ducati GP16. Thus we repeated the POA calculations, but comparing each rider against all riders on the same machine instead of comparing him against all riders on the same team. This resulted in the following plot:

Again, Marquez, Dovi, Zarco, and Aleix Espargaro outclassed their rivals in similar machinery. Petrucci has a much lower POA now, as he is being compared against Ducati factory riders, as opposed to being compared to Scott Redding. Crutchlow now appears with a high POA (1.98) as he outscored Miller, Rabat, and Aoyama on the same machine.

While this kind of analysis allows us to partially neglect the differences in machinery, a higher POA doesn’t necessary mean a better rider. For instance, the fact that Aleix Esaprgaro has a POA of 1.73 doesn’t mean that he is a better rider than Maverick Viñales, who has a POA of 0.50, as it is not the same to compare your performance to Sam Lowes than to Valentino Rossi…

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**Reigns of riders with at least 25 victories:**

We also offset all *reigns* to start at the same time (a reign starts the year that a rider wins a race) so we could compare each rider at the same points of their winning reign.

**Reigns of riders with at least 25 victories, offset to start at the same time:**

There, we could see that Rossi has been constantly above any other rider for most of his career, meaning that he had more wins that anyone else at the same point of each rider’s reign.

However these graphs (an derived conclusions) have a fundamental problem. They don’t take into account that nowadays there are considerable more races per year than they were in the past.

When MotoGP started, in 1949, the race calendar had 6 races for the whole year. That number has been steadily increasing all the way to the 19 races of this season, and maybe even 20 for next year, if Mexico finally makes into the calendar.

**Evolution of number of races per year:**

This makes comparing the number of victories of riders of different eras skewed in favour of the more recent riders, as it is easier to win 1 race in a calendar with 18 races than in a season with 6.

A way to avoid that bias is to normalise the number of victories per year, so instead of all wins counting as 1, a win in a championship with less than 19 races (as in the 2018 season) will count as more than 1. So for instance: a victory last year (with 18 races) counts as 1.06 normalised victories, and a victory in a season with 10 races (like 1975) counts as 1.9 normalised victories.

Normalised number of victories, nnv, can be computed as:

nnv(rider, year) = num_victories(rider, year) * (19/num_races(year))

**Reigns of riders with at least 35 victories:**

In this case we highlighted riders with at least 35 wins -instead of 25, as before- so only 11 riders gain the label of *champion, *as decided by the* motogpdata ring of* *elders*, in an attempt to prevent too much clutter on the plot.

This new criteria means that Dani Pedrosa (8th racer in number of victories, with 31) is greyed out as he becomes the 13th racer per number of normalised victories, with 33. Kevin Schwantz also looses the label of *champion, *with 32 normalised victories.

On the other hand, we now have John Surtees (62 normalised victories), Geoff Duke (56), and Kenny Roberts (38) as newly crowned *champions*.

Another thing that jumps to the eye on the previous graphs is that the most successful rider, with 118 normalised victories, is legend Giacomo Agostini. Agostini gets the title despite we only count his 68 wins in 500c, and ignore the fact that he also won 54 races (106 if we would normalise them!) in 350cc. However if we expand the analysis to all racing categories we would start talking about Angel Nieto and his 12+1 championships, and that is a different rabbit hole…

So back to the top class. Below the man who won every single 350cc and 500cc race in 1968, 1969, and 1970, we find Valentino Rossi, with 101 normalised victories. Behind, Hailwood overtakes Doohan as the third most successful rider with 78 normalised victories. Interestingly, John Surtees (62) and Geoff Duke (56) are now considered more successful riders than the recent crop of Lorenzo (52), Marquez (46), Stoner (41), and Pedrosa (33).

**Reigns of riders with at least 35 normalised victories, offset to start at the same time:**

If we offset all reigns, so they all start together, we can see that the previously dominant Valentino Rossi is now surpassed by Surtees. Surtees, with 62 “modern” wins, ended his 5 year reign in two wheel racing (in 1960) to focus on four wheel racing, where he feared pretty well, adding the 1964 Formula 1 title to his four 500cc and three 350cc motorbike GP titles.

Mike Hailwood was also more successful than Rossi, after a 7 year reign, when he retired prematurely, forced by Honda pulling out of Grand Prix motorcycle racing.

Interestingly, Marquez and Stoner are now very equal to Eddie Lawson, sandwiched in between Geoff Duke and Kenny Roberts.

**The top 25 riders, according to their number of normalised victories are:**

Rank (normalised) | Rider | Normalised victories | Victories |
---|---|---|---|

1 | Giacomo Agostini | 118 | 68 |

2 | Valentino Rossi | 101 | 89 |

3 | Mike Hailwood | 78 | 37 |

4 | Mick Doohan | 72 | 54 |

5 | John Surtees | 62 | 22 |

6 | Geoff Duke | 56 | 22 |

7 | Jorge Lorenzo | 52 | 47 |

8 | Marc Marquez | 46 | 40 |

9 | Eddie Lawson | 45 | 31 |

10 | Casey Stoner | 41 | 38 |

11 | Kenny Roberts | 38 | 22 |

12 | Barry Sheene | 34 | 19 |

13 | Dani Pedrosa | 33 | 31 |

14 | Kevin Schwantz | 32 | 25 |

15 | Freddie Spencer | 32 | 20 |

16 | Wayne Rainey | 31 | 24 |

17 | Wayne Gardner | 24 | 18 |

18 | Randy Mamola | 22 | 13 |

19 | Phil Read | 20 | 11 |

20 | Alex Criville | 19 | 15 |

21 | Umberto Masetti | 16 | 6 |

22 | Max Biaggi | 16 | 13 |

23 | Gary Hocking | 16 | 8 |

24 | Leslie Graham | 14 | 5 |

25 | Libero Liberati | 13 | 4 |

By obtaining the normalised number of victories for each rider, computing each rider reign, and offsetting them, we can compare riders from very different racing periods.

However, the circle can’t only be squared to a point. We can’t forget that we are comparing riders that faced completely different challenges. That we ignored the role of lesions, the quality and reliability of the machinery they had, the team, the level of the competition, etc. And as such, we should take any conclusion with a bucket of salt, as we are nonetheless comparing the incomparable.

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With 47 top class wins (4th most successful winner in all time) it is no surprise that we concluded that Lorenzo is a genuine champion. However looking at the numbers we saw that his reign was far from reaching the heights of the most successful rider in the top class of Grand Prix racing: Valentino Rossi.

We compared Lorenzo’s reign (47 victories in 11 years) with Rossi’s first 11 years and we saw how Rossi clearly outperformed Lorenzo – or any other human being (including aliens), for that matter – with 79 victories in 11 years since his first victory.

But each moment in time has its own circumstances…

Rossi arrived to the premier class in 2000, the year after Doohan injury-triggered retirement, which left a vacuum that was contested by riders like Criville (15 victories during his career), Biaggi (13 victories), Capirossi (9 victories), Barros (7 victories), or Okada (4 victories). And while these riders were extremely skilled (every single rider in MotoGP is extremely skilled in my view, including the ones who pay to be there), their numbers say that they were far less successful than the inch-perfect riders that Lorenzo found when he arrived to the premier class.

When Lorenzo landed in MotoGP, he had to compete against 4 of the most succesful riders in history: Rossi (89 wins during his still ongoing reign), Marquez (40 wins), Stoner (38), and Pedrosa (31). So surely, while Rossi-Biaggi fights were visceral and intense, the level of the riders that filled the grid alongside Rossi was probably a bit lower (at least it was considerably less successful) than the riders that Lorenzo faced since 2008.

So what if we forget about the early years of Rossi, and we look at the victories of all riders since 2008 only?

**Accumulated victories since 2008 (1st year of Lorenzo’s in MotoGP):**

And boom! here you see why Lorenzo sees himself as a true champion. Since he entered MotoGP, he has won more races than anyone else, including Rossi (whom he beat regularly on equal machines), Stoner, Pedrosa, and Marquez.

Yes Marquez has accumulated 40 victories in 6 years, only 7 less than Lorenzo in 11 years, but if we look at the graph above, we can see that the only rider to keep pace with Marquez during 2013, 2015, and 2016 was Lorenzo. Keeping the new poster boy at bay until Lorenzo moved to Ducati in 2017.

So in short, Rossi might have had a much longer and successful MotoGP career than any other rider, but nobody has matched Lorenzo – not even Rossi – since Lorenzo arrived to MotoGP. No wonder why Lorenzo sees himself as the true champion that he is.

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Lorenzo, who would shock the motoGP paddock 7 days later by announcing a contract with Honda for 2019 and 2020, did not take these words lightly and a few days later, when asked about Dominicali words during Mugello first day of practice, replied: “*I won’t comment on Domenicali’s remarks. I’ll only say that I’m not a great rider, I’m a champion.*”

With 3 MotoGP championships (and 2 more in 250cc) there is no doubt that Lorenzo is a champion. And to just make it clear, he backed his words with an astounding win at Mugello three days later, followed by two more wins at Catalunya and Austria.

But how much of a champion is Lorenzo? How does Lorenzo compare to other champions?

To answer that question, I used the freely available data at motogp.com (for some reason it doesn’t work on Firefox) to collect all MotoGP and 500cc winners (until the Brno round). I labelled a *champion* anyone with at least 25 wins and I plotted the accumulated number of victories per year, highlighting Jorge and any other *champion*.

**Reigns of riders with at least 25 victories:**

This plot shows the *reigns *(from the year with the first victory to the year with the last one) of each rider. A rapid ascend implies a large number of victories during that time period. On the other hand, a “plateau” indicates lack of victories (see Valentino struggling with his Ducati in 2011-2012).

We can see that Jorge Lorenzo (with 47 wins) towers on top of Casey Stoner (38 wins), Marc Marquez (40 wins), and Dani Pedrosa (31 wins). Only Doohan (54 wins), Agostini (68 wins), and Rossi (89 wins) have more victories than Lorenzo.

As a side note, it is interesting to see Dani Pedrosa -who has never won a championship- to rank 8th in total number of victories, level with Eddie Lawson and with more victories in his pocket than Schwants (25), Wayne Rainey (24), Freddie Spencer (20), or Alex Criville (15).

To better compare the reigns of the different champions I shifted all the *reign* lines so they start together.

**Reigns of riders with at least 25 victories, offset to start at the same time:**

From this last plot (with champions who fought against Lorenzo also coloured) we can see that both Marquez, Stoner, Agostini, and Rossi remained above Lorenzo throughout their careers. This means that at the same year since they started their reign , they had more victories than Lorenzo. For instance now Marquez has 40 wins (on the 6th year since winning the first race), and Stoner had 38 when he retired after the 6th year of his reign, compared with 31 for Lorenzo at the 6th year of his reign.

Lorenzo rate of victories per year throughout his career compares best with the 7 year reign of Mike Hailwood, which ended abruptly when he took a sabbatical year paid by Honda and moved to car racing. The first 6 years of Lorenzo’s reign are also similar to the first 6 years of Eddie Lawson reign. However Lorenzo has won another 16 races from the 7th year onwards, while Lawson spent the 7th and 8th year of his reign without a single win, and he could only add one more in the 9th year.

Lorenzo also kept a winning rate similar to Doohan’s during the first 7 years of their careers, but Lorenzo flattened a bit from the 8th year compared to Doohan relentless increase in victories during the 8th and 9th year of his reign, which ended abruptly when he had to retire due to injury (video in Spanish, and well… it includes a heavy crash). Doohan piled 54 wins during his 9 year reign, compared with 44 wins for Lorenzo during his first 9 years.

But all reigns, including Lorenzo’s, pale in comparison with Rossi’s career. After 11 years of racing, Lorenzo counts with 47 wins. At the same point of his career Rossi had already won 79 races. Even Agostini’s 68 victories during his 12 year long reign can not compare with Rossis’s numbers. This shows how brutally successful has Rossi’s career been, specially during the first 11 years up to the “*Ducati plateau*” of years 12th and 13th.

So yes, Lorenzo is a champion, no doubt about it. And to add to his credit, he managed to win 47 races while competing against 4 of the most successful riders ever, including an incredibly successful Valentino Rossi.

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