DawgTalkers.net Forums DawgTalk Looking Back: Browns 16 Bengals 17 Postgame Thoughts

I wondered the same thing yesterday and couldn't really get anywhere.

What I did accomplish was the following; first, a general overview of success by kickers that have changed teams over the past three years.


The first query was this:

give me a list of free agent kickers with at least three nfl season's experience that were signed by new teams over the last five seasons.

I wanted to eliminate the (arbitrary, on my part) rule that "it takes three years to even know". Then I asked for their career percentages...


Joey Slye: 82.3% career FG percentage

Matt Prater: About 84.1% career FG percentage (Prater has a long career with consistently above 80% accuracy)

Nick Folk: Approximately 86.1% career FG percentage

Eddy Pineiro: Around 79.5% career FG percentage

Austin Seibert: Approx 73.3% career FG percentage

Michael Badgley: Roughly 84.7% career FG percentage

Zane Gonzalez: About 83.5% career FG percentage

Dustin Hopkins: Approx 85.7% career FG percentage

Greg Joseph: Around 80.2% career FG percentage

Greg Zuerlein: Roughly 84.6% career FG percentage

Cade York: A newer kicker, estimated around 80% but less data available



Then:

is there a math formula for "clutchness"?


Yes, there is a mathematical approach to quantifying "clutchness" in NFL kicking performance, often based on statistical models that evaluate kicker success in high-pressure situations compared to expectations.

One approach used in sports analytics is:

Define "clutch time" kicks as field goal attempts occurring within the final two minutes of the game where the score difference is six points or fewer.

Calculate the expected probability of making each kick based on factors like kick distance using logistic regression.

Compare the actual made kicks during clutch time to the expected number of successful kicks.

The difference between actual made kicks and expected made kicks (Successes Over Expectation, SOE) during clutch situations is taken as a measure of clutchness.

This method can be refined further by controlling for kick distance, weather, and other context details.

Researchers have found mixed evidence on whether kickers truly perform better or worse in clutch moments, but this mathematical model is one way to quantify clutch performance objectively.

Overall, clutchness formulas rely on probabilistic modeling of kick difficulty and comparing observed success under pressure to statistical expectations. This can also be expanded to measure clutch performances more broadly across a player's career or in specified high-leverage game situations.


Then I asked the obvious. (Note: I didn't plan to include Gostkowski and Vinatieri, but someone here mentioned New England's kickers, and I couldn't remember Gostkowski, so I asked in the same AI thread. From that point forward, they were lumped in to any questions about "kickers" I'm actually glad because it adds a little context.)


Please run all these kickers we just discussed through this clutch model...





Notice anything interesting??

Win probability isn't affected all that much?

Or is it that 3/4 kickers that didn't make the final list were Browns kickers? That would be kinda hilarious.

I was more shocked by Prater's 96% clutch percentage... and that he was sitting on a couch while we were wiping our's a$$ and teaching him to tie his shoes.

41 years old and coming off a major knee injury... that is why he was sitting on the couch. I'm not saying he should have been, just stating the "why".

Now there’s a visual I won’t soon forget.

I agree on both counts. You don't cut a rookie after his first game. I understand it was a bad performance and understand the emotion, but to cut him after one game would be a punk move.

I also agree with celebrations. Celebrate when you have something to celebrate. Being behind gives you no cause to celebrate.