New for 2019, I will be keeping track and updating Expected Points (xPts) for every race and for the season as a whole. xPts is the number of points we would expect to see a driver earn in a race given how he ran as judged by their average track position (ATP) and ATP25. The last 25% of the race is given extra weight as it is when the race is finally coming down to the wire and performance is more crucial. If two drivers both had an ATP of 5 but one had an ATP25 of 3 and then other an ATP25 of 18, while they both had good days from their general ATP, we would still expect the former to score more points than the latter.
In virtually every race, there are drivers who are running well all day and then get crashed out through no fault of their own. And there are drivers who can’t avoid a crash ahead of them and the rest of the race is spent at the back of the pack due to lost time. No race perfectly reflects the true speed or talent of the drivers and cars, and xPts is a way to start to understand the race a little better.
For example, in the first race this year Ryan Hunter-Reay was looking like he was going to be a competitor for a race win or at the very least a podium. He started the race in fifth, led practice sessions, and was running in the top six when his engine cut out on him on lap 19. He earned seven points for the race after finishing in 23rd. We don’t know exactly how the rest of his race would have played out, but based on how he had been running up to that point, we have a good idea of how it was likely to. That’s what xPts does for us. Based on how he was running in the race (ATP of 5.74) and how he was running (or in his case, not running) in the last 25% of the race as shown by an ATP25 of 23, we would have expected him to earn 21.7 points. That’s a difference of +14.7 compared to what he actually got. xPts tells us Hunter-Reay was actually a strong driver at St. Pete and his result was pretty unlucky.
Josef Newgarden on the other hand over performed his xPts by 7 in the same race. This over performance can be attributed to a great call by his strategist Tim Cindric to pit for an extra stint on the red alternate tires on lap 56: he was one of only three drivers to do that. This decision ultimately ended up leading Newgarden to victory in the first race of the season, and the great call is reflected in the comparison between the xPts model and his actual points.
xPts at the race level gives a gut reaction to how to feel about a driver’s race. Under performed? Maybe we should look and see if there was a strategy decision, bad break, or something else that set him back. Over performed? How did they get that edge: was it a good strategy call, being at the right place at the right time, or maybe they simply performed best when it mattered at the end of the race.
Over longer periods of time, xPts becomes even more useful. A driver that consistently over or under performs compared to how we’d expect them to is very interesting to look at. If we are halfway through the season and a driver has scored 100 less points than we’d expect them to through that point, I would expect them to start climbing in the standings when their bad luck turns. They’ve probably been caught out by bad timed cautions, wrecks, or something else. A driver that is doing consistently better is the opposite: they might be having great luck so far with ending up in the right spot at the end of the race despite how they were running throughout it. This is usually not an easily repeatable thing, and they would be expected to regress to the mean as time goes on and luck evens out.
An over or under performing driver might not always be due to luck however. If a team can consistently beat their points expectation and doesn’t seem to be regressing, that is a good sign that they have found and advantage and are doing something other teams aren’t. This is hard to do in IndyCar since every team is closely watching every other team, and small advantages are usually found out quickly. Most over and under performances can be attributed to the luck of racing, but xPts can also alert us to teams whose strategy or driving style requires a closer look.
xPts is useful at both the individual and multiple race levels, and I’m excited to be bringing it to The Single Seater this year. I will be posting all of the xPts data on this page throughout the season, so be sure to check back there often for race and season xPts. It is very much a new tool in IndyCar analytics, which also means it’s going to be a work in progress. If there are any updates to the model throughout the season, I will let everyone know in a post and update the methodology on the xPts page. I hope people find value in xPts and it helps to add a deeper level of understanding IndyCar performances and races, making all of us more informed fans of the sport.