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2020 Analysis: Buffalo Bills punter Corey Bojorquez

Let’s discuss punting

After the 2019 season, most fans of the Buffalo Bills were less than thrilled with the overall performance of punter Corey Bojorquez. With both film study and traditional statistics falling short of definitive analysis I decided to create my own metric. Was it valid? Who knows! Did I use it anyway? You bet I did! Am I doing it again this year? Ha, ha, ha! Of course I am.

Review of method

Check last year’s article for more details on why I don’t like punting stats. The short version is that they lack context. For my homebrew method, I create a definition of a “bad” punt and calculate the percentage of punts that fall under this definition. I do not rate punts on the opponent’s side of the field. See the original article for an explanation, but also add in the idea that punting in enemy territory is generally bad no matter what the punter does.

Punts on your own side of the field are divided into two zones, between the 1-24 yard line, and between the 24-49:

  • For kicks from your own 1- through your own 24-yard line a bad punt is anything 45 yards or less. The league average was 45.9 and the rationale is that when you have plenty of room to kick there’s no reason not to boom it (except outkicking your coverage). Anything below average when the situation calls for “well above average” can be considered “bad.”
  • Between the 25- and 49-yard line, punts 40 yards and under were considered “bad.” This is semi-arbitrary. A 40-yard punt in this zone results in the opponent receiving it between the 11 and 35, which isn’t bad (though also not necessarily “good” either). Note that this changed from last year—see nerdy explanation below.

Charts and fun stuff

First off, if you’re into the traditional stats, Corey Bojorquez killed it in 2020. He led the league in yards per punt with 50.8 and was tied for the longest punt of the year with Kevin Huber. Both kicked a 72 yarder.

But remember we hate traditional punting stats so here’s the chart:

After all this build up, the narrative is very simple. Using this metric, Corey Bojorquez was pretty average in 2020 when it came to the frequency of bad punts. He also improved drastically from 2019. And looking at the play log (thank you to for the data) there’s only one truly terrible punt. A 12-yarder vs. the Arizona Cardinals. I was going to do a GIF but decided it was in no one’s best interest to relive that.

More nerd stuff

If you compare this year’s chart to last year’s you’ll notice a few differences. A couple of the raw numbers changed for Corey Bojorquez, which also adjusted percentages. Last year I included playoff punts, this year I didn’t. I worried that there might be coaching tendency changes in the playoffs that could skew results. With the small sample sizes for some of the punters, even one or two punts could be significant.

I expanded the sample size by a few punters to give approximately half of the league’s results. The larger group should be sufficient to be representative of the league as a whole. That allowed me greater confidence in creating an average to compare to, so I did.

The average of the sample led to another major change. Keen readers might have noticed I changed the definition of a bad punt in the 24-49 yard-line zone. Here’s a long explanation on why. Last year I chose 35 based mostly on end result (ball landing between the opponent’s 40- and 16-yard line).

You’ll notice that in the 1-24 yard-line zone the sample’s average was about 31 percent bad punts. While fairly rudimentary, if we divide punts into three types; “bad,” “meh,” or “good” you’d want a relatively even distribution between the three types. My first guess that punters should want at least an average punt distance when backed up in their own territory proved to be pretty successful at isolating roughly a third of the punts.

When I started doing the 25-49 zone, it quickly became clear that I wasn’t going to be anywhere near a third. I added five yards to make it 40 and got to about 20 percent of punts ending up in the “bad category,” which I think gives us a much better definition—though still not perfect. If I were to dedicate more time to this (and maybe I will), I’d likely tweak things. For instance, I’m betting that if I changed the zones to something like 1-34 and 35-49 or similar it’d make a big difference.

But for a quick study I think this will do for now.

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