NFL BIG DATA BOWL PART 1
Tags: NFL, Kaggle, Data Visualization

On Kaggle, this year’s NFL Big Data Bowl has provided tracking data for all the pass plays in the 2018 seasons in an effort to analyze defensive pass coverage. The data includes player tracking, play, game, player level information, target receivers, as well as defensive pass coverage schemes. In part 1 of this deep dive, let’s take a look at the player level and game/play data as we do some exploratory analysis.

Coverage scheme data was only made available for week 1, but let’s start by looking at how often defences use different coverage schemes.

We can clearly see that Cover 3 Zone and Cover 1 Man are by far the most frequently used coverages.

When do defences like to use these coverages? That seems to depend on the down and the number of yards left to get a 1st down. On 1st and 2nd down, defences generally use Cover 3 Zone more, while on 3rd and 4th down teams use Cover 1 Man more. Teams also heavily favour man coverages in short yardage situations.

Since Cover 3 Zone and Cover 1 Man seem to be the most frequently used defensive formations, let’s take a quick look at what offensive positions teams try to target more on offence against these defensive schemes.

In general, pass plays seem to target WR by a large margin against both of these coverages. Passes to the RB happen more often against the Cover 3 Zone defence and slightly less to the WR, which is typically how Cover 3 Zone schemes are designed to operate (weaker against short passing routes).

How many yards does each defensive coverage give up against the pass? Let’s see how many yards a play results in, categorized by the defensive coverage scheme.

In general, we can see that Cover 3 Zone, Cover 4 Zone, and Cover 1 Man give up similar yardage.

Since we know that teams like to use different coverages depending on the down and yards to go, let’s introduce the number of yards to go in our analysis. We know that the average number of yards to go in our dataset is 8.9 so let’s split out data into less than 9 yards and more than 9 yards to look at how often teams use different coverages.

As expected, teams slightly favour Cover 1 Man when there are less yards to go, and pick Cover 3 and 4 Zone a bit more when there are more than 9 yards to go. Next, we can look at how well the defences perform in terms of average yards gained on the play.

For plays that occur when there are less than 9 yards to go, defences tend to choose Cover 3 or 4 Zone, and Cover 1 Man, which appears to be the best choices as they are the plays that give up the lowest average yardage per play. The same plays tend to be chosen for plays where there are more than 9 yards to go, but Cover 3 Zone is no longer the coverage that holds teams to the fewest average yards per play. That distinction belongs to Cover 2 Zone. Being the best performing coverage by average play result and only being used just over 10% of the time is a disconnect that NFL teams should explore in the future as a way to improve defensive performance.

Let’s zoom in to see how coverages perform against different offensive formations. First, let’s take a look at how the defences line up in the various coverages at the point when the ball is snapped.

Next, we can see how the coverages match up with various offensive formations.

Here we can see that defences try all sorts of coverages when the offence lines up in a Shotgun formation, but the zones seem to fare better (Cover 2 Man looks like it does really poorly against the Shotgun formation). It also looks like Cover 1 Man does very well vs. the Empty formation.

We can also look at how teams generally line up in difference offensive formations so that teams can adjust their defensive coverages and choose the best (or avoid the worst) matchup. For example, if the defence sees the offence line up in a Shotgun formation, maybe they’ll want to avoid using a Cover 2 Man and instead go with one of the zone options.

Lastly, which teams were the best at defending the pass? Let’s use the available metric EPA, which measure the expected points added on the play relative to the offensive team, and see which teams had the lowest average EPA across all their pass plays for the year.

CHI, BUF, BAL, and MIN look like the best defensive teams in the NFL for 2018.

Looking at how defences performed on preventing a pass play completion for a 1st down during 3rd and 4th down plays can also show us which defences do well in big moments.

What about sacks and interceptions? Here we can see that there is a clear correlation between the number of sacks and interceptions a team scores, but that it does not necessarily indicate that a team’s defence is ‘good’. We can see CHI produces a lot of sacks and interceptions, and is indeed one of the top defences in terms of average EPA for pass plays. We can also see that MIA, one of the worst teams in terms of average EPA, also performs well in scoring sacks and interceptions. This would suggest that the pass complete and incomplete rates may be better markers for a team’s defence.

Analysis done in Python / Jupyter Notebooks Data part of NFL Big Data Bowl 2021 (https://www.kaggle.com/c/nfl-big-data-bowl-2021/data)