Posted by: drracing | September 29, 2017

ELMS – Spa Race analysis

Hi everybody!

I start to like this race analysis thing! That’s why i am here again with a new one, this one crunching the publicly available numbers relative to the ELMS race in Spa, held on the weekend of the 23rd and 24th of September.

Before to dive into the analysis though, i would like to share some data and a video about a simulation session done in preparation for the same race. The session took place on my simulator and the latest iteration of the LMP2 vehicle model has been used.
Here is a link to the video.
Incidentally, the best lap of the session was a 2’02.427, which compares pretty well to the pole position time of 2’02.457 done by Ben Hanley. In the video we managed to catch a lap slightly below 2’02.7.
This tells nothing in particular about the accuracy of the model, but as I had a chance to compare the simulations results with logged data, i can say i am pretty happy with how it matches to the real car!

And now, let’s look at Spa and the available data, to try and understand what happened exactly.

This beautiful track, which needs no introduction, offers always not only very exciting racing action but also a very interesting scenario from a technical perspective, mixing long straights and fast sections with quick and slow corners and leaving room for very different setup choices potentially producing a very similar lap performance.

The race was won with merit by Graff Racing car n.40, driven by James Allen, Richard Bradley and Gustavo Jacaman.
It was a complex race, with many neutralization phases either done with FCY or letting the safety car into the track. This was necessary, for example, when the Algarve car crashed at Pouhon and the car flipped over, after impacting with the barriers.
Because of the many neutralization periods, strategy played a very important role and teams went through the race using very different approaches, making it very difficult to read. For example, Dragonspeed cars (n.21 and n.22) pitted early at lap 8 when the first FCY was declared, while SMP, even if not using the FCY for an early pit stop, was able to run 19 laps with a full tank before stopping to refuel, while all the other main contenders stopped at lap 18.
To make all more spicy, the two leading cars both had to serve a drive through penalty at the end of the race and ended up with a gap to each other of less than 0.6 seconds.

Let’s look at the pit stops first and at the overall time spent in the pit lane.

Graff #40:                    5:58.598
G-Drive #22:               6:36.065
SMP #27:                     5:15.185
Autosport #32:           5:31.889
Dragonspeed #31:     6:51.258

The winning car n.40 spent 5:58.598 in the pit, including the late drive through, which took about 23.6 seconds and went into the pit lane six times.
Car n.22, who finished second, spent more time in the pit (6:36.065) and went in seven times, but, as we said, the first pit stop was done very early and under FCY, a condition where all the other cars are forced to drive slow anyway, while the latest was a drive through penalty that took 23.4 seconds. Without the drive through, the strategy could have proved very good indeed.
Car n.27 is the one who spent less time in the pit lane among the main contenders, with 5 pit stop and an overall 5:15.185.
Car n.32 also had a shorter pit time than the two leading teams, with five pit stops and an overall time of 5:31.889.
Finally, car n.21 also stopped seven times for a total of 6:51.258.
I am not totally sure about this, but my taking is that each team changed the tyres only twice during the race.
Again, it was a very complex race, from a strategy perspective. The five stop strategy that SMP and Autosport put in place was probably also in Graff plans, but the latest penalty forced them to stop once more. Interestingly, without that stop, they would have been in the pit for 5:34.987, not too much longer than what SMP did.

What about each car performance?

If we look at the best laps of each car, car n.22 is on top and the winning crew is actually “only” fourth:

Best lap times:
Graff #40:                    2:05.939
G-Drive #22:               2:05.236
SMP #27:                     2:06.25
Autosport #32:           2:05.719
Dragonspeed #31:     2:05.623

As we see, car n.22 was very clearly the quickest one on the single lap, with the good surprise of car n.32 being now much closer to the best contenders’ pace than in Paul Ricard.
Anyway, as we have seen already in the two previous race analysis, looking at the best lap time doesn’t tell too much in endurance racing.
If we take a look at the average of the best 20 laps, we start getting a better picture:

Best 20 lap times average:
Graff #40:                    2:07.158
G-Drive #22:               2:07.285
SMP #27:                     2:07.888
Autosport #32:           2:07.365
Dragonspeed #31:     2:07.912

The first thing we notice is car n.40 taking the lead, with car n.22 and n.32 being very close. It is not a case that also car n.32 was for a long time in contention for the lead and it is interesting to see how much closer to the Orecas they were here compared to Paul Ricard.
Another interesting thing here is that car n.21, which was clearly the fastest on track in Paul Ricard, was not as successful in Spa, at least in terms of pace. This is partially due also to how the race evolved, with FCY and SC periods probably affecting the stints of the two quick drivers in the crew, Lapierre and Hanley. One of the latest stints of Nico Lapierre was indeed very quick and car n.21 was probably the fastest car on track during that same stint. Still, the impression is that they struggled much more than in Paul Ricard, also in terms of pace.
All of these trends seems to be confirmed if we look at the best 50 lap times average, with car n.40, car n.22 and car n.32 ever closer to each other:

Best 50 lap times average:
Graff #40:                    2:08.32
G-Drive #22:               2:08.33
SMP #27:                     2:09.019
Autosport #32:           2:08.498
Dragonspeed #31:     2:09.327

It is impressive to see how car n.22 and car n.40 had nearly the same average time. As we will see later on, this is even more interesting considering that i suspect the two cars were running different setup philosophies.

Since the race was so much affected by FCY and SC situations, we will not have a chance to look at a best 100 lap times average (the leader only run 97 laps) and we will directly jump to the “all clean laps” times average (or something at least close to it, as several cars found themselves involved in a FCY or SC for a different time).

All clean laps lap time average:
Graff #40:                   2:09.059
G-Drive #22:               2:08.949
SMP #27:                     2:09.758
Autosport #32:           2:09.147
Dragonspeed #31:     2:09.94

Again, car n.40 and car n.22 are very close to each other, but with car n.22 now being slightly faster.
It is also very interesting to notice how car n.27 was pretty much always out of pace, compared to the other competitors, including car n.32, which was in every of the averages we looked at the third quickest.

If we look to the plots showing the best 20 and 50 lap times for each car, we pretty much identify the same trends. Car n.40 and car n.22 are pretty close together, with Graff’s car being clearly the fastest in the 20 best lap graph and the G-Drive one getting better if we look at the 50 best laps one.

 

Best 20 laps

 

Best 50 laps

 

It is also interesting to notice how car n.32 was pretty close to two Orecas pace for more or less the whole race and also was significantly quicker than the n.27 SMP Dallara. The latter, although being probably closer to the best cars compared to what achieved during qualifying, was still pretty much off in terms of lap times.
The plot also shows that car n.21 was not really as brilliant in Spa as it was in Paul Ricard.

Since the ELMS offers some variety in terms of Chassis used by each team, it is interesting to take a look at the sector times and analyse where each car was faster or slower, trying to find indications about each car strong or weak points and about how each team approached its setup.

The track was divided, as usual, in three sectors, as shown in the image below.

 

track map

 

The first sector is pretty much about top speed and having less drag. The second one is pretty long and represents a good test of both car’s low and high speed grip and handling. Downforce is very important here, together with a well balanced behavior in both low and high speed corners.
Last sector is again about speed and, partially, about braking stability (there is a very hard braking before the last chicane, where the cars downshift from 6th to 1st gear and from about 290 km/h to about 70).

If we look at the best sector 1 times, we can immediately recognize a very important trend:

Best sector 1 times average:
Graff #40:                   35.769
G-Drive #22:              35.981
SMP #27:                    36.038
Autosport #32:          36.086
Dragonspeed #31:    36.115

Just by looking at these numbers we immediately catch something extremely important: while all the other cars are very close to each other (with car n.27, car n.32 and car n.21 nearly all in less then a tenth of a second), car n.40 has a clear edge, being some two tenths faster than car n.22 and about three tenths faster than all the others.
This trend doesn’t change if we look at the average of the best 20 sector 1 times, but actually the advantage of car n.40 becomes even more evident.

Best 20 sector 1 times average:
Graff #40:                   35.984
G-Drive #22:              36.265
SMP #27:                    36.346
Autosport #32:          36.229
Dragonspeed #31:    36.335

Interestingly, the advantage of car n.40 on car n.22 increases, while the gap between car n. 40 and car 32 reduces slightly, with car n.32 being quicker than car n.22.
It is also interesting to notice how, in this first sector, the SMP Dallara doesn’t seem to be too far off from the competition, if we exclude car n.40.
If we look at the average of the best 50 sector 1 times, the trends remains very similar:

Best 50 sector 1 times average:
Graff #40:                   36.142
G-Drive #22:              36.430
SMP #27:                    36.554
Autosport #32:          36.374
Dragonspeed #31:    36.611

The gap between car n.32 and car n.40 reduces again a tiny bit but in general all the cars seem to increase their average times similarly compared to the 20 best sector 1 times average, with the exception of car n.27 and car n.31 that seem to have a slightly stronger performance deterioration.
This is particularly interesting for car n.27, as it is the only car in our analysis having only two silver drivers in the crew, both performing very similarly and, as far as we could see in Paul Ricard, pretty well too. We would expect a smaller effect due to the drivers when looking at performance deterioration in the 50 best sector 1 average than for other crews, but still the average time goes up slightly more than for other cars. This could signalize the car suffering more the effects of tyre deterioration in this sector, where, we have to remember, we also find the famous Eau Rouge corner, which could maybe become a bigger challenge if the tyres are not new anymore and if the car has less downforce than the competitors. These are of course mainly speculations, i am simply trying to interpret what we see, but of course i could be completely wrong.
In terms of performance deterioration, the worst case is still car n.21 (as in Paul Ricard), with the third (non-professional) driver probably still having a very important impact on the average performance of the crew.

If we finally look at the “all clean laps” sector 1 times average, we identify more or less the same trends:

All clean laps sector 1 average:
Graff #40:                   36.449
G-Drive #22:              36.761
SMP #27:                    36.940
Autosport #32:          36.739
Dragonspeed #31:    37.023

The main message, summarizing what we can deduce analyzing first sector performances, is that car n.40 seems to have a pretty clear edge on the competition. Graff’s car is consistently about three tenths quicker than the other cars, in a track section where performance are defined mainly by straight line speed.
This is well confirmed by the best 20 and 50 first sector times plots:

 

Best 20 sec 1

 

Best 50 sec 1

This seems to strongly suggest that car n.40 was running less downforce/drag than the other Orecas (and less drag than the other cars) and/or that they had more engine power. Since we deal with a spec engine class and the difference in time is pretty big, i think the reason should be mainly connected to a different aerodynamic setup, compared for example to car n.22 (although there is nothing like “all engines are the same” and i would not be surprise if, because of engine fatigue of other teams or simply because of the window that each manufacturer allows in terms of “power tolerances”, a part of a similar gap could rely on the engine itself).
Another interesting point that the plots confirm is also how competitive car n.32 was in this first sector, also compared to car n.22, which is consistently slightly slower.

Our conclusions seem to find further support if we look at the top speeds (the speed trap was located at the end of the Kemmel Straight, that means at the end of sector 1). Here, car n.40 has again a clear advantage on the competition, as we can see looking at the best speed overall and to the average of the best 20 and 50 top speeds each car achieved:

Best top speed:
Graff #40:                   301
G-Drive #22:              294.5
SMP #27:                    297.7
Autosport #32:          297.7
Dragonspeed #31:    292.9

Average best 20 top speeds:
Graff #40:                   297.95
G-Drive #22:              292.1
SMP #27:                    294.5
Autosport #32:          294.7
Dragonspeed #31:    290

Average best 50 top speeds:
Graff #40:                   296.5
G-Drive #22:              288.2
SMP #27:                    292.9
Autosport #32:          292.4
Dragonspeed #31:    287.7

As we could imagine, car n.40 is the fastest, with car n.27 and car n.32 following and being relatively close to each other and car n.22 being a bit slower.
Looking at the plots relative to the best 20 and 50 top speeds, we identify more or less the same situation but it looks like car n.27 had a slight advantage on car n.32 on the long distance:

 

Best 20 top speed

 

Best 50 top speed

 

Beside Graff having the best speed (and also the best sector 1 time, which looks very consistent) we see something interesting: although car n.27 seems to have a higher top speed than car n.32 on the long run, it constantly produces slower sector 1 times, which seems to suggest the SMP Dallara having slightly less drag than Autosport’s Ligier but also maybe some issues in driving fast through the Eau Rouge section, maybe because of lower downforce or different setup choices. The same conclusions seems realistic if we compare SMP Dallara to G-Drive Oreca, that has slower top speeds, but is nonetheless consistently faster in sector 1.

Contrary to sector 1, in sector 2 downforce and handling play a central role, while having low drag is surely not the top priority to obtain competitive times.
Following what we learnt analyzing sector 1, it is not a surprise to find out that the fastest car in sector 2 is actually G-Drive Oreca (n.22).
If we only look to the best sector two time of each car, the advantage of car n.22 on the competition is an astonishing half a second, with car n.32 and car n.21 following and car n.40 being the slowest.

Sector 2 best times:
Graff #40:                   57.588
G-Drive #22:              56.745
SMP #27:                    57.475
Autosport #32:          57.248
Dragonspeed #31:    57.249

The situation changes a bit if we look at the best 20 sector 2 times average, with car n.22 still being fastest than all the others, but with a much smaller gap, above all compared to car n.40 and car n.32, with the latter being very competitive in this second sector.

Sector 2 best 20 times average:
Graff #40:                   58.335
G-Drive #22:              58.157
SMP #27:                    58.566
Autosport #32:          58.241
Dragonspeed #31:    58.594

We see a similar picture if we also look at the average of the best 50 sector 2 times, only the gap between car n.22 and the closest among the others (car n.32 and car n.40) increasing a bit. SMP Dallara remains pretty much out of pace in this sector:

Sector 2 best 50 times average:
Graff #40:                   58.972
G-Drive #22:              58.717
SMP #27:                    59.197
Autosport #32:          58.966
Dragonspeed #31:    59.385

Nothing changes significantly in the “all clean laps” average, with car n.22 still on top of car n.32 and car n.40:

Sector 2 “all clean laps” times average:
Graff #40:                   59.651
G-Drive #22:              59.422
SMP #27:                    59.927
Autosport #32:          59.640
Dragonspeed #31:    60.267

The performance of each car compared to the others in sector 2 is somehow easier to perceive if we look at the best 20 and 50 sector 2 times plots:

 

Best 20 sec 2

 

Best 50 sec 2

 

Above all when looking at the best 50 sector 2 times plot, we clearly identify how big was the edge that G-Drive crew had on the competitors. We also clearly see that car n.32 and car n.40 performance were pretty close to each other. Again, if we assume that the two cars have the same engine power and we consider also what we saw in sector 1, this could indicate that the Oreca 07 has a higher aerodynamic efficiency than the Ligier Js P217 (in this case, in particular, meaning the Oreca had similar downforce but less drag), which seems to be reasonable considering that the Oreca 07 defined pretty much LMP2 performance target until today.

Sector 3 is, again, a quick section of the track where top speed plays a very important role. The only quick corner belonging to this sector is Blanchimont, which is an easy flat out with these cars. Beside this, as we said, there is a heavy braking into the bus stop chicane, which is composed of two very slow corners.
In this sector, car n.40 is again in front in terms of performance, above all compared to the direct competitor during the race, car n.22. The latter, gets closer to Graff’s pace only if we consider the last part of the best 50 sector times list: is it maybe connected to a bigger tyre wear affecting car n.40? Or maybe to a worse traffic management? Difficult to say.
Looking to the best sector 3 times, car n.40 is con top but interestingly the closest car following is car n.32:

Sector 3 best times:
Graff #40:                   32.175
G-Drive #22:              32.27
SMP #27:                    32.409
Autosport #32:          32.183
Dragonspeed #31:    32.259

Car n.40 gains a stronger gap on the competition in the average of the best 20 sector 3 times:

Sector 3 best 20 times average:
Graff #40:                   32.487
G-Drive #22:              32.608
SMP #27:                    32.618
Autosport #32:          32.615
Dragonspeed #31:    32.584

Car n.22, car n.27 and car n.32 are extremely close to each other, with car n.21 being slightly quicker than the other two.
The situation changes a bit if we look at the average of the best 50 sector 3 times, with car n.40 being pretty much on the same level as car n.22 and car n.27:

Sector 3 best 50 times average:
Graff #40:                   32.747
G-Drive #22:              32.795
SMP #27:                    32.797
Autosport #32:          32.894
Dragonspeed #31:    32.896

It is interesting to notice how close to each other are car n.22 and car n.27, confirming in this sector the Dallara is pretty competitive.
All cars are also very much packed together if we look at the “all clean laps” average, with car n.40 still holding a small advantage and car n.22, car n.27 and car n.32 being very close to each other.

Sector 3 “all clean laps” times average:
Graff #40:                   33.06
G-Drive #22:              33.12
SMP #27:                    33.178
Autosport #32:          33.153
Dragonspeed #31:    33.261

As always, the best 20 and 50 laps plots give a more “visual” feeling about the relative performance of each car.

 

Best 20 sec 3

 

Best 50 sec 3

 

Up to the 30 mark, Graff’s Oreca is clearly the fastest car, while between the 30 and 50 mark the performances of car n.40, car n.22 and car are very close to each other.
Car n.32 is very quick on the very left side of the plot, but tends to loose performance and, in general, seems a bit slower than the competition, despite having average times that are not too far from the ones of the other cars.
Again, it is also interesting to notice how in this sector the n.27 SMP Dallara pretty much matches car n.22 pace, in a track section which is probably the one resembling more closely the second sector of Paul Ricard track, where car n.27 was very competitive (mainly inline speed and a hard braking).
Interestingly, it looks like Autosport’s Ligier performs better in the first sector than in the third one, although in both of them top speed plays a central role. We cannot forget, anyway, how an important part of first sector performance depends on how good the car flies through the Eau Rouge complex.

To close we can take a quick look at the lap time each car produced during the race at each lap. Again, the plot comparing all cars is pretty messy (even more in this race, because of the many SC and FCY that came in), but still tells interesting things:

 

all laps all cars

 

Some points we can extract just by looking at all the lines are:

  • Car n.21 lost a lot of time in the first two stints, where the non-professional driver was at the wheel
  • Car n.21 was extremely quick between laps 60 and 70, but was in general not as quick as it was in Paul Ricard compared to the competition
  • Car n.40 had a pretty bad performance between laps 60 and 70, being in this interval of time slower than car n.22 and car n.32
  • maybe also because of the many safety cars, we don’t seem to identify a dramatic performance deterioration as, for example, in COTA WEC race

 

More information can be deduced by looking at the comparison between car n.40 and each other car.
The following plot compares car n.40 with its main contender for the final victory, car n.22.

 

all laps 40 vs 22

 

Car n.22 was apparently slightly faster during the first stints and again between laps 63 and 76, but slower in the stint immediately after and in the final stint, when it probably got caught in traffic. Car n.40 was faster also between lap 45 and 52.

What about SMP Dallara?

 

all laps 40 vs 27

 

As we have already seen, car n.27 was constantly a bit slower than car n.40 and never really on the same pace as the Orecas. The green line in the plot above lies nearly always above the blue one, in particular during the last four stints.

A comparison between Graff’s car n.40 and Autosport’s car n.32 is, on the other hand, a bit harder to read:

 

all laps 40 vs 32

 

Car n.32 was indeed very fast in the first part of the race and again faster than car n.40 between laps 65 and 75, as we saw. Anyway, it didn’t match car n.40 pace in the last stints nor it did between lap 45 and 52.

Finally, as we already had a chance to say, car n.21 was not so fast in Spa and this is again confirmed if we look at the following plot:

 

all laps 40 vs 21

 

Until lap 60, car n.40 seems constantly faster. Car n.21 runs some very competitive laps 61 and 74, but also afterward it never really match car n.40 pace anymore, also showing maybe the only case of visible performance degradation, with its lap times constantly increasing in the last two stints.

Closing, this analysis confirms that car n.40 not only worked out its strategy very well, but also obtained its victory relying on its pace, which proved to be extremely good, also thanks to some setup choices that were apparently different than the other Orecas (see for example Dragonspeed – G-Drive).
Spa is surely one of the best track for the Oreca to express its potential, but it was also interesting to see how the Autosport’s Ligier was not too far off from Orecas pace (above all car n.22), while the Dallara seemed to struggle more.

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