Glossary

Search with CTRL+F or CMD+F.

1st Seg Stats
First segment stats - The same stats as you know but only before the first caution or pit stop of the race
2T
Two tires
4T
Four tires
AFP
Average finish position
ARP
Average running position
ASP
Average starting position
Avg Team Geo
Average team geometric mean lap score - The average of the driver's team's geometric mean lap score in the races the driver has participated in. This tends to be well below the actual average
Fin%
Percentage of races finishes
Fin.
Races finished
GF Laps
Green flag laps
GR
Gain rating - The weighted number of positions gained. The weighting is done based on the perceived difficulty of passing from a driver's current position. For example, it's for more difficult to pass from 2nd than it is from last, because the quality of car and driver is much higher at the front and there's just fewer spots to gain to begin with. The driver is assigned a score for each lap on which he or she gains a position. That score is the product of two values: the difference between the driver's starting and finishing position on that lap, and the weight of their starting position. The weight is inverse to the ordinal value of the position; something like 1/N, where N is the position. For example, 12th has a weight of 1/12 [Read more]
GR-LR
Net rating - The difference between the driver's GR and LR [Read more]
GR/LR
The ratio of GR and LR
Gain Laps
Laps where position improved
LR
Loss rating - See GR, but LR is only for laps where the driver has lost position. The weight is the inverse of their position from the back of the field, i.e. losing positions at the rear of the field results in a higher score than losing positions at the front, and thus a higher score is bad [Read more]
Last Seg Stats
Last segment stats - The same stats as you know but only after the last caution or pit stop of the race
Loss Laps
Laps where position was lost
Net Gained
Pos. Gained - Pos. Lost
P50 / P95
50th percentile (median) / 95th percentile
PFAE
Positions finished above expected - Based on the starting position of a driver, the number positions finished higher than average for that starting position. For example, if a driver starts 12th and finishes 6th, but the average finish for a 12th place start is 13th, the driver scores +7 PFAE for that race
PFARP
Positions finished above running position - Like PFAE and PGAE, but comparing the driver's finish position against the average finish of a driver at their current running position at the specific point in the race. For example, if a driver is running 12th on lap 100, and the average finish for a driver running 12th on lap 100 is 13th, and the driver finishes 6th, they score +7 PFARP.
PGAE
Positions gained above expected - For any given running position, we can find the average position on the next lap. PGAE is the sum of the difference between the corresponding average to the driver's current running position and where they ended up in actuality on the next lap. For example, if a driver is running in 12th, and a driver in 12th on average is running 11.95th on the next lap, and the driver actually gains a position, he is scored a 0.95 for that lap. But if he held his 12th instead, he'd have been scored a -0.05. PGAE/100 is the driver's average score per 100 green flag laps
PO Points
Playoff points
POMS
Percent of max speed - Race adjusted average speed. Assuming the fastest lap of the race is the fastest anyone could have gone on that day in that race, each lap speed as evaluated as a percentage of that lap speed and averaged to gain the driver's race adjusted average speed. This stat exists because without it, it's impossible to compare laps between a low speed track like Martinsville against a high speed track like Talladega. Note that this still isn't perfect: some tracks have greater fall off than others, and sometimes the weather changes or there's a rain delay, and that can cause distortion in POMS.
POMS Var.
POMS variance - The variance in a driver's POMS
PRT
Performance relative to team - The sum of the difference between the driver's lap scores and their team's geometric mean lap score. Positive means a driver is doing better than their team's geometric mean lap score (most drivers are positive), negative means they aren't. This is most useful for comparing within teams and against similar teams
PS
Pit stops
Pos. Gained
Total number of positions gained on gain laps
Pos. Lost
Total number of positions lost on loss laps
RR
Retained rating - Using the same weighting principles as GR and LR, the score on laps where the driver's position has not changed. Almost a weighted average running position
Retain Laps
Laps where position was unchanged
Retained Ratio
(GR + RR) / LR
SS
Speed score - 1000 x the ratio of the driver's 95th percentile lap to the race 95th percentile lap. A good read of a driver's top speed. [Read more]
T10%
Top 10 percentage
T5%
Top 5 percentage
TIB
Average time (in seconds) in box
TIM
Average time (in seconds) in motion
TOPR
Average time (in seconds) on pit road
Team Geo
Team geometric mean lap score - The driver's team's geometric mean lap score in this race
W%
Winning percentage
cPOMS
Continuously graded POMS - Like rPOMS but instead of using the fastest lap of the race, it uses the fast lap of that lap. For example, when scoring a driver's lap 30 lap speed, it uses the fastest of all drivers' lap 30 lap speeds
eARP
Estimated average running position - Assumes drivers are in 1st for laps they've led and that they split the rest of their laps evenly between their start and finish position. This isn't bound to be highly accurate but it uses the maximum amount of information available for all seasons of all motorsports. It's superior to any of its constituent parts or and naive combination thereof. Formula: ((1 * laps led) + 0.5(start position + finish position)(laps run - laps led)) / (laps run). On Lap Raptor, it's always applied on a race level (meaning we never take shortcuts and use ASP and AFP) as inputs
eGR-LR
Estimated net rating - An experimental approximation of GR-LR using the driver's race starting position and their race finishing position. On the Other series page, also uses the number of laps led to help in the scoring. Uses the same weighting principles as GR and LR
f-stats
The stat but in finishes
nRT
Net retained rating - RR + GR - LR
oPOMS
Offset POMS - All the POMS tend to be close together. As of writing the difference between the top POMS driver and the 17th best is 0.08. That's 0.87%. Offsetting the two by 0.85 amplified the difference, at least in the ratios. The difference between the oPOMS is the same, but now the top driver is 9% better than 17th
rPOMS
Race averaged POMS - The average of a driver's average POMS in each of their races. One potential issue with ℓPOMS is that it gives a higher weighting to races with more laps. The Bristol night race, which has 500 laps, has 6x times the weighting in a driver's ℓPOMS than a race at the Indy Road Course, which has 80-90 laps. To cover for this, rPOMS takes a driver's average in each race, then averages those averages. The drawback here is we are giving races with a small number of laps - imagine if a 40-45 lap truck race at COTA got rained out and they only ran 25 - and equal weighting to one with hundreds. Assigning greater weight to a small sample could cause distortion. It's best to keep both types of POMS in mind.
tPOMS
Total POMS - The sum of all of a driver's lap scores
tPOMS/R
tPOMS per race
wARP
Weighted average running position - A driver's average green flag running position, which each lap weighted in proportion to how well that lap predicts a driver's finish position over Lap Raptor's entire data set. The result is that a driver's running position in later laps are weighted higher than earlier laps. This better accounts for strategic decision making and smart driving (for example, earlier in a race you might be willing to sacrifice track position for speed or to avoid on-track incidents).
wPFARP
Weighted positions finished above running position - Like PFARP, but the the laps are weighted based on how well that point in the average race predicts a driver's finish position over Lap Raptor's entire data set. See wARP for more information.
ΔPOMS
Change in POMS - How much faster a driver went in the final segment than in the first. Last segment minus first segment.
ℓPOMS
Lap averaged POMS - POMS as you know it. The score you see is Sum(lap score of all relevant laps) / GF Laps