Kickers Are People Too – Part 1: Modeling Kicker Quality

Let’s face it. You play in at least one league that still uses kickers.1 And you know what? That’s totally fine! While kicking is still the hardest part of the game to model, it doesn’t mean we shouldn’t at least get better at it. So that’s what I’m here to do in this three part series. In this article — Part 1 — I’ll introduce my kicking quality model, which takes into account all sorts of factors including kick distance, weather, altitude, field surface, era,2 and more. From there, I’ll derive a power ranking for each kicker based off of how well he performed relative to the situation, so we can get a retrospective look at how well each kicker performed in 2015 relative to his peers.3 In Part 2, I’ll derive a model to  predict the number of attempts per game each kicker gets. Finally, in Part 3 we will put the first two parts together to create kicker rankings for 2016. Let’s jump into Part 1, the kicker quality model.

Why We’re Doing This

Let’s start with a hypothetical. Let’s say I kick 10 field goals and make nine of them, and you kick 10 field goals and make eight of them. Who was better? If we went by raw percentages, I made 90 percent of my attempts while you made 80 percent of your attempts. But what if all of your kicks came from 60 yards out, in snowy conditions, on grass, while mine came from 20 yards out, in perfectly calm weather, on AstroTurf? Suddenly your 80 percent from 60 yards out in a blizzard looks a whole lot better than my 90 percent on chip shots during a beautiful day. That’s the basis of my kicker model that I’ve developed using the Armchair Analysis data set, which goes all the way back to 2000. I have to say, the idea for this model wasn’t originally mine. Torin Clark, Aaron Johnson, and Alexander Stimpson presented their kicker model at the MIT Sloan Sports Analytics Conference back in 2013. I’ve simply taken their work, and updated it with a few additional features that I believe extend their work to make the model as accurate as possible. I’ve also changed their kicker evaluation from what they call “added points” or “added points per attempt” to a power ranking. I’ll explain why down below. If you want the details of their work, I highly suggest you check out their paper on the topic.

Model Factors
  1. That also includes you DFS players who play at FanDuel.  (back)
  2. Kickers have indeed improved over time.  (back)
  3. In fact, I’ll have a full list at the bottom from 2000 to present.  (back)

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