At the end of every IMSA WeatherTech SportsCar Championship Season, I spend some time crunching the numbers. It's available to the public, all of the data. It just takes time and dedication to go through the information and decipher the untold stories of the year. And, to be honest, I love doing that. For example, this year 275 individual drivers participated in an IWSC race. That's up from 248 last year. That's not explicitly listed online anywhere, but I keep a count of all the drivers' results from the season, so it's easily figured out within a spreadsheet.
Over the next week, come with me to see what we didn't learn as the races were happening as I break down the 2022 season class by class. We'll go in order of speed, so let's start with the DPi category.
24 drivers stood on the podium, but none more than champions Oliver Jarvis and Tom Blomqvist. Although they only won 2 races, they went home with 7 trophies and racked up 3 poles. Others had more wins (the WTR Acura had four and the 01 Cadillac had three), and Sebastien Bourdais earned the Pole Award with four on his own.
Qualifying points:
|
Qualifying
Points |
||
|
DPi |
||
|
Earned |
W/O Q
Pts |
|
|
60 |
312 |
3120 |
|
10 |
316 |
3030 |
|
0.1 |
300 |
2920 |
|
0.2 |
291 |
2900 |
|
5 |
269 |
2710 |
|
31 |
263 |
2820 |
This is interesting. When looking at the breakdown, the
second-place car in the championship actually outscored the victors by 4 points. Take away qualifying points and the 60
still takes the championship ahead of the 10, then the 01 ahead of the 02 (separated
by that one spot on track as reflected in the last laps of Petit Le Mans), but
the Mustang Sampling Cadillac finishes behind Pipo Derani in the championship,
instead of the other way around. Not a big deal in the long run, sure, but
it is interesting to see how big of a gap the points accrued was in the top
class. In qualifying, both cars ran the same number of races yet the 10 car outscored the 31
by 53 points!
Qualifying to Race:
Something else I started doing this year was tracking how
many positions were gained and lost through the race by each team. This speaks mostly to poor qualifying performances being overcome by good racing, but it
also shows the bad luck of some teams over the course of several
races. Good qualifying doesn’t equate to good race results, but bad qualifying can
make it harder to get a good finish.
For DPi, the car that made up the most ground was also the
one who scored the fewest points for qualifying, no surprises. The 31 Whelen
Engineering Cadillac made up 11 spots over the course of the season. Compare
that to the 2x pole-sitting car of Konica Minolta, who ultimately lost 8 spots
throughout the year. Not huge numbers, but the final points tally for the championship reflects that Konica Minolta lost the championship in realistically one bad race as opposed to the consistency exhibited by MSR across all races giving them the momentum needed to win it. Look at the results from Konica Minolta compared to MSR and that tells you all you need to know. The worst finish for the 10 was 6th, where they finished 3 times. Compare that to MSR, with a worst finish of fifth once.
On Track by Driver Performances:
These numbers tell a lot. All of this data was accrued over
the year by using the Alkamel provided Fast Lap during the race. I kept record
of each race and broke it down further by class. It’s not an average of a series of
laps over a stint but rather the Fastest Lap per driver per race, not per
event. This does mean that the starting drivers in the sprint races are at a
disadvantage, since they don’t get new tires necessarily or a second stint.
That said, you can only judge like for like, and so I am more interested in
comparing drivers to their on track peers. That detail is more relevant to the GTD
class, but it’s important to state off the bat so everyone can understand how
it works.
So who was the strongest driver over the year in DPi?
Earl Bamber.
His average position amongst the DPi drivers for Fast Lap
was 4. Compare this to Oliver Jarvis, champion in 2022 and class MVP just a couple years ago, who’s average was 11.1.
The weakest of the class was Jimmie Johnson, with an average of 21.7. Bamber,
it’s worth noting, was the finishing driver for all of the sprint races, so
Lynn didn’t get new tires as frequently during the season. But the same argument
can be made for Westbrook and van der Zande, both of whom were the finishing
drivers most of the year.
Earl was not the strongest when it came to average time
off pace. That award goes to last year’s champ Pipo Derani. Pipo was on average
0.485 seconds off the fastest lap. The slowest of the full season drivers by
this average was a surprise, Richard Westbrook, at 0.999 off. That means the
whole full season field averaged less than a second off pace! That’s super
impressive!
Another new thing I did this year was compare the average time off co-driver (or fastest co-driver). This was super useful, because your most useful comparison is the same machinery, although I do appreciate drivers out on track at the same time. However, the driver who was least off the pace set by his codriver was Pipo Derani again. He was 0.058 seconds off his co driver. Now, bear with me for a second on this. Oliver Pla was the most off his codriver at 1.168 seconds, but he ran half a season after replacing Tristan Nunez, who’s average was 0.687! It’s not like either of them are slow pokes, but they were both the furthest off of the full season co-drivers, namely Pipo! Pretty wild!
|
By Avg. Pos FL |
D24 |
S12 |
LB |
LS |
MO |
BI |
WG6 |
M |
RAm |
PLM |
FL |
Avg. Pos |
||
|
0.2 |
Bamber |
2 |
4 |
3 |
8 |
2 |
7 |
4 |
3 |
6 |
1 |
1 |
4 |
|
|
60 |
Blomqvist |
5 |
10 |
8 |
1 |
1 |
4 |
2 |
1 |
11 |
7 |
3 |
5 |
|
|
31 |
Derani |
8 |
13 |
2 |
6 |
3 |
1 |
6 |
6 |
8 |
3 |
1 |
5.6 |
|
|
10 |
R.
Taylor |
4 |
3 |
12 |
7 |
4 |
5 |
5 |
5 |
|
11 |
|
6.22 |
|
|
0.1 |
Bourdais |
6 |
14 |
1 |
10 |
7 |
9 |
3 |
10 |
4 |
2 |
1 |
6.6 |
|
|
0.1 |
RvdZ |
9 |
16 |
4 |
|
5 |
11 |
12 |
2 |
5 |
4 |
|
7.56 |
|
|
48 |
Kobayashi |
12 |
2 |
|
|
|
|
8 |
|
|
9 |
|
7.75 |
|
|
10 |
Albuquerque |
14 |
21 |
9 |
2 |
8 |
2 |
1 |
11 |
2 |
10 |
1 |
8 |
|
|
5 |
Vautier |
13 |
6 |
11 |
4 |
11 |
6 |
10 |
12 |
3 |
6 |
|
8.2 |
|
|
0.2 |
Lynn |
15 |
11 |
7 |
3 |
9 |
8 |
7 |
8 |
1 |
19 |
1 |
8.8 |
|
|
5 |
Westbrook |
17 |
9 |
5 |
5 |
6 |
3 |
16 |
9 |
9 |
14 |
|
9.3 |
|
|
31 |
Pla |
|
|
|
|
|
12 |
13 |
7 |
10 |
8 |
|
10 |
|
|
60 |
Jarvis |
20 |
19 |
6 |
9 |
10 |
10 |
11 |
4 |
7 |
15 |
|
11.1 |
|
|
48 |
Lopez |
18 |
5 |
|
|
|
|
|
|
|
|
|
11.5 |
|
|
31 |
Nunez |
19 |
7 |
10 |
11 |
12 |
|
|
|
|
|
|
11.8 |
|
|
48 |
Rockenfeller |
25 |
12 |
|
|
|
|
14 |
|
|
17 |
|
17 |
|
|
48 |
Johnson |
27 |
|
|
|
|
|
17 |
|
|
21 |
|
21.7 |
|
*Bold Denotes Slowest Driver of Class
|
By Avg. Time off Pace |
By Avg Time off Co-drivers |
||||||
|
31 |
Derani |
0.485 |
48 |
Kobayashi |
0 |
||
|
0.2 |
Bamber |
0.487 |
31 |
Derani |
0.058 |
||
|
48 |
Lopez |
0.493 |
0.2 |
Bamber |
0.215 |
||
|
0.1 |
Bourdais |
0.595 |
5 |
Vautier |
0.216 |
||
|
48 |
Kobayashi |
0.637 |
10 |
R.
Taylor |
0.253 |
||
|
10 |
Albuquerque |
0.684 |
60 |
Blomqvist |
0.264 |
||
|
10 |
R.
Taylor |
0.688 |
48 |
Lopez |
0.276 |
||
|
60 |
Blomqvist |
0.718 |
10 |
Albuquerque |
0.277 |
||
|
0.2 |
Lynn |
0.755 |
0.1 |
Bourdais |
0.323 |
||
|
0.1 |
RvdZ |
0.777 |
5 |
Westbrook |
0.363 |
||
|
5 |
Vautier |
0.853 |
48 |
Rockenfeller |
0.446 |
||
|
60 |
Jarvis |
0.948 |
0.2 |
Lynn |
0.483 |
||
|
31 |
Nunez |
0.976 |
60 |
Jarvis |
0.493 |
||
|
5 |
Westbrook |
0.999 |
0.1 |
RvdZ |
0.513 |
||
|
48 |
Rockenfeller |
1.083 |
31 |
Nunez |
0.687 |
||
|
31 |
Pla |
1.734 |
31 |
Pla |
1.168 |
||
|
48 |
Johnson |
2.466 |
48 |
Johnson |
1.623 |
||
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