On Any Given Axes: TNF, Bengals vs Browns

Andy Dalton is actually very good this season! Johnny Football is actually going to play football! A divisional matchup that the NFL thought would be less one-sided at the start of the season when they decided the TNF games!

Amongst all these heart wrenching story-lines weren’t you desperate for someone to post some simple (and some less simple) graphs to clear the air? Well look no further.

Today I’m starting up the first of hopefully many On Any Given Axes features, where I take a game that I’m watching and share graphs that I’ve made about it. I’ll share the graphs on twitter and copy the tweets here, and will try to respond to any interesting comments on either, so do keep in touch!

What I’ve got: A divisional matchup with two maverick quarterbacks

What I’m going to do with it: Watch it and graph it.

01:01 GMT: Score Stories

First up, what’s happened when these two teams have last met each other? I made a fancy thing called a ‘score story’ (better names accepted) to try and capture the ups and downs of this divisional matchup. I plot a graph of the point differential at each point in a game for each game and do this for every game on the same graph. The result of this is a confusing mess of lines showing the turmoil of the game.

01:39 GMT: Thursday

This one is pretty dominated by the fact that there isn’t much data on how these two teams do on a thursday, but I thought I’d stick it in just because it looked nice. These are score scatter graphs where the teams scores (from the past 14 years) are on the axes, so if your point is in the bottom right hand side (split up by the ‘win line’), the x axis team wins, and if the point is in the top left hand side the y axis team wins. I have highlighted the thursday games with red dots.

First thing to note is that the Bengals just seem to have higher scoring games and just seem to win more. Secondly you can see an interesting pattern emerging due to the fact that the predominant method of scoring in the NFL is touchdowns with a PAT or a field goal, which leads to a characteristic block-like distribution of scores. To further illustrate this, below is a heatmap showing the distribution of scores for any game played in the past 14 years.


It’s cool that there’s such a dark line down the middle, showing how rare it is to get a tie in the NFL.

02:20 GMT : Touchdown!

We’ve had a touchdown so I thought I’d have a look at what percentage of plays within 10 yard ranges ended in a touchdown and ended in an interception for each of these two teams for the past three years.

More bad news for the Browns. Lower efficiency in the redzone and a higher amount of interceptions in midfield. But to be fair to Manziel, he didn’t start for most of the games in this dataset, whereas the Bengals’ distribution is all Dalton

02:32 GMT – Draft Picks

My brain just isn’t working anymore so this will be my last, a distribution of the 1st round draft picks (which is mostly correlated with how bad your team did the season previous) for both the Bengals and the Browns.

This is just quite cruel to the Browns now, but you can see they are much more heavily based in the lower numbers which means that the Bengals have a slightly better record.

This (or more likely next) is your season, Browns!


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