A tipped pass for an interception or crushing hit for a fumble can decide a close game. No coach emerges from a press conference without touting the importance of winning the turnover battle.
However, not all turnovers are created equal. In the 2013 NFL regular season, teams with more interceptions than their opponent won the game 80% of the time. Teams that forced and recovered more fumbles than their opponents won the game 70% of the time.
Interceptions have a bigger impact because the defender is most likely on his feet after the takeaway. This can lead to a big swing in field position or even a score. Defenders that recover fumbles tend to fall on the ball.
What factors affect interceptions in the NFL? Here, we’ll look at the surprising analytics behind interceptions.
You can do better than guessing that each team will throw picks on 2.9% of pass attempts, the NFL average. And it doesn’t involve an arcane statistic that comes from charting games. The critical numbers are in the box score, although it might not be the numbers you expect.
We’ll also look at how this analysis changes the predicted point spread for a game.
How pass rush affects interceptions
Seattle cornerback Richard Sherman led the NFL in interceptions in 2013. Despite all of his public claims about being the best cornerback in the league, Sherman credits his front seven for much of his success.
Pass rush is an obvious candidate to affect interceptions. The more often a defense applies pressure on the quarterback, the more often he throws an errant pass. Or perhaps the defender strikes the quarterback’s arm, causing a wobbly pass to fall into the hands of the defense.
To study this, we need to measure the strength of the pass rush. To start, let’s look at sacks, a number that requires proper context. A defense might rack up more sacks by facing more pass attempts. To account for this, let’s use sack rate, or sacks divided by the sum of pass attempts and sacks, as a measure of pass rush.
To determine whether pass rush causes interceptions, consider NFL defenses in the regular season from 2003 through 2013. While I expected defenses with a better sack rate to have a higher interception rate, there’s no correlation between these two quantities for these 352 defenses.
For those with a technical inclination, sack rate explains less than 1% of the variance in interception rate. For everyone else, check out the left panel of the visual in the next section.
Richard Sherman might be a great cornerback because of Seattle’s pass rush. However, his pass rush doesn’t explain his high interception total in 2013.
How pass protection affects interceptions
If pass rush has no effect on a defense’s interceptions, what about pass protection on offense? An offensive line that keeps pass rushers away from the quarterback might result in fewer interceptions.
Over the same 11 regular seasons, the sack rate allowed by an offense explains 6% of the variance in the interception rate. While this correlation is stronger than on defense, I still do not recommend using sacks to predict interceptions. The right panel of the visual shows why.
We can dig even deeper into pass protection. Over the last 5 seasons, the NFL has tracked QB hits, or the number of times the quarterback gets hit after releasing the ball. We can now calculate the rate at which an offensive line allows the hits on the quarterback (the sum of QB hits and sacks divided by the sum of pass attempts and sacks).
This QB hit rate gives a better perspective on pass protection. An offensive line might look good because of a low sack rate. For example, Indianapolis gave up sacks on 5.2% of pass attempts in 2013, 5th best in the NFL.
However, this same offensive line allowed a hit rate of 23%, 26th worst in the NFL. Andrew Luck’s ability to get rid of the ball in the face of pressure played a big role in their low sack rate. The lack of protection probably also contributed to Luck’s below average completion percentage of 60% in 2013.
However, even a better statistic like QB hit rate doesn’t correlate with interceptions. Hit rate explains 4% of the variance in interception rate, a weaker correlation than shown in the right panel of the visual.
The data does not support the belief that pass rush affects interceptions. I would guess this comes from the ability of NFL quarterbacks to not let pressure to affect their accuracy. Of the thousands that play in high school and hundreds that make it to college, only 32 can play in the pros. These quarterbacks do not fold under pressure.
However, these 32 quarterback do vary in their accuracy, and that might impact interceptions.
How throwing accuracy affects interceptions
Despite the wobbles of the his balls, Peyton Manning has shown incredible precision with his throws. Over his career, he has completed 65.5% of his passes. Of active players, only Drew Brees and Aaron Rodgers have a better career completion percentage.
However, Peyton has gotten even better after having multiple neck surgeries. In his last two seasons with Denver, his completion percentage has increased to 68.4%.
Do more accurate quarterbacks throw fewer interceptions? Any fan would rather have Manning and Rodgers leading their offense than Derek Anderson or Brady Quinn. But are fewer interceptions a consequence of a better quarterback?
To answer this question, consider the career statistics for NFL quarterbacks in 2013 with at least 500 career pass attempts. The visual of these 52 players shows the negative correlation between completion percentage and interception rate.
Peyton Manning is the third point from the right, and he has thrown picks at a higher rate than this regression analysis predicts. The outlier with the lowest interception rate is Nick Foles, the second year quarterback with Philadelphia. As much potential as he has shown, he will not continue to throw interceptions on 1.2% of his pass attempts. The same applies to San Francisco’s Colin Kaepernick, the point with the second lowest interception rate (1.7%).
This correlation does not imply that better accuracy causes fewer interceptions. But this conclusion does seem logical. The quarterback has control over where he throws the ball. The more control he shows, the less likely the ball hits the hands of a defender. There are better ways to look at this causation, but they will have to wait for another day.
For these quarterbacks, completion percentage explains 32% of the variance in interception rate. In the noisy world of football statistics, that’s as strong a relationship as you will see between two statistics. In addition, the correlation also exists for the regular season statistics of offenses from 2003 through 2013. Here, completion percentage explains 20% of the variance in interception rate.
With this strong relationship between accuracy and interceptions, how can we modify a point spread prediction for a game?
How interceptions affect the point spread
To use these results to adjust a prediction, let’s look back at the Super Bowl between Seattle and Denver at the end of the 2013 season. Before the game, the team rankings at The Power Rank predicted Seattle by 1.3 points, which implied a 46% chance for Denver to win.
Denver had a lower likelihood to throw a pick based on Peyton Manning’s accuracy. On average, NFL quarterbacks throw interceptions on 2.9% of pass attempts. With Peyton’s 65.5% career completion percentage, the regression model predicted he would throw interceptions on 2.56% of pass attempts. For a league average 35 pass attempts, this meant 0.14 fewer interceptions for the game.
While such a small fraction of picks might seem inconsequential, the impact of such a turnover makes it matter. From the relationship between interceptions and points in NFL games, the average interception is worth about 5 points. This changed the predicted point spread by 0.7 points in Denver’s favor. Seattle’s predicted margin of victory dropped from 1.3 to 0.6, which increased Denver’s win probably from 46% to 48%.
The game didn’t go Denver’s way. Seattle’s defenders knew what mouthwash Manning used before the game since they spent the entire game in the backfield.
The outcome of interceptions in the Super Bowl
Manning thew 2 interceptions. The first was an errant pass that landed in the hands of Cam Chancellor, a play in which Manning wasn’t pressured that heavily. The second pick came when a defender hit his arm on a throw. The football wobbled into the hands of Malcolm Smith, who ran for a Seattle touchdown.
For the game, Manning thew 49 passes, so the two picks implied a 4.1% interception rate. Even with this small sample size, that is not an outrageous rate. If not for the bad luck on the pick in which his arm got hit, Manning would have had a 2% rate.
Common sense says that pass rush and throwing accuracy affect interceptions. However, the NFL data only shows a link with one of these factors. If you want to predict interceptions, stay away from pass rush statistics and look at completion percentage.