Why Don’t NFL Teams Pass More Often?
Debunking common NFL myths in an analytical study on the true value of passing the ball
Background
Analytics are not used enough in the NFL. In a league with an abundance of money, intelligence, and skill, one may assume that the game we see teams play today is the most optimized and efficient it can be. However, the reality is that the league and its gurus still stick to many traditional aspects of the sport, not utilizing analytical techniques as much as they could. Our research reveals a significant flaw in the way the game is currently played.
Around the same time the three-point line was added to the NBA, the NFL experienced a similarly drastic change with the popularization of the Spread Offense. Many know it as the change that was designed to spread the opposing team’s defense horizontally across the field, exposing holes for the offense. A lesser-known fact is that the implementation of the playstyle caused the passing game to be more efficient than ever…
… and increasingly so over the years. Figure 1 clarifies that the efficiency (which accounts for yards, first downs, touchdowns, interceptions, and sacks) for passing has for at least the past forty years significantly exceeded rush efficiency.
Initial Findings & Suspicions
Mind-blown by this widening chasm between the efficiencies of the two play types, we set out to explore the significance of this discrepancy and how it has affected modern NFL teams’ decision-making. For the data source, NFL play-by-play data from Ron Yurko’s nflscrapR package in R was aggregated.
The initial findings supported the idea that passing has become more efficient — in 2019, the average yards gained from a pass attempt (PYPA) was 6.73 while the average yards gained from carries (YPC) was 4.40. The Baltimore Ravens, who averaged the most yards per carry (5.6), averaged less YPC than Mitch Trubisky and the Chicago Bears’ dismal 5.7 PYPA (worst in the 2019 season). Nonetheless, as seen in Figures 2 & 3, NFL teams have only passed the football 58.5% of the time (out of run or pass plays only) over the past eleven seasons, a stat that one would logically expect to be greater given the above numbers.
If teams only pass 58.5% of the time even after the best rushing teams fail to average more YPC than the league’s worst passing team’s PYPA, then surely, there must be something missing. Though not necessarily flawed, the initial findings offered a rather one-dimensional analysis of the data. While it was concluded that passing yielded significantly more yards for any team, it had still not been confirmed that passing was more correlated with success. Therefore, the group sought to compare the correlations between teams’ winning percentages (WP) in a given season and rushing and passing, respectively. First, a metric was required to measure the success of each play type for all 352 teams (32 teams * 11 seasons). The most logical choice was using Success Rate over Average. A play is considered to be successful when it gains at least 40% of yards-to-go on first down, 60% of yards-to-go on second down, and 100% of yards-to-go on third or fourth down. The metric was calculated by taking a team’s average success rate of a play type and dividing it by the league average for the given season. The correlations were then run between the success rates and the WPs and graphed, as seen below.
Although neither variable has a strong correlation (> .7) with WP, passing is nearly twice as correlated with winning than rushing. Even without knowing the correlations, one can infer that passing success is more correlated with winning merely by noticing the spread of the data points on the graphs. While the comparison in Figure 4 has outliers well beyond the reaches of a wide oval shape, Figure 5 contains all of its data within a football-shaped ellipse.
Creating a Win Percentage Model
The next step in the process was constructing a model that predicted a team’s winning percentage given certain passing and rushing attributes. This model would identify which aspects of a team were more important in creating a successful team — this meant selecting rushing and passing variables and weighing them to optimize the model’s correlation with WP. The variables used were the following:
Passing Attributes:
- Passing Success Rate (as described before)
- Adjusted Sack Rate on pass plays (inversely proportional to a team’s success in pass protection)
- Pass Touchdowns (directly proportional to pass scoring and success)
Rushing Attributes:
- Rushing Success Rate
- Adjusted Line Yards on rushing plays (directly proportional to a team’s success in rush blocking)
- Rush Touchdowns
A team legend was created so the outliers could be identified.
With a correlation of about 0.67, the refined model in Figure 6 came close to a strong relationship with WP. More significantly, passing statistics had an effect on the model that was 1.5 times greater than rushing stats — in other words, the pass variables were weighed 1.5x more. With this compelling evidence, it was becoming more apparent that the passing game is far more critical for a team’s success than its running game. The increasingly confirmed hypothesis that teams do not pass enough was now raising more questions concerning NFL teams’ decision-making.
Busting Two Common Myths in the Modern NFL
Surely there was something still missing — a key factor not taken into account was the potential drawback of repetition and its effect on the value of a play in a game. A common notion about play-calling is that repetition tends to decrease the value of a play while the potential unpredictability in “changing it up” (running/passing almost the same number of times) keeps the defense on their feet. To measure the value of variability — or loss of value with repetition — comparisons were run between the run/pass proportions of past play-calls in a game and the EPA of the current play, as seen in Figures 7 & 8. EPA, or expected points added, is a popular metric used to quantify the value of a play in terms of the number of points it is predicted to yield for the team with the ball. As ESPN explains, “without going into technical details, the key is that the relationships in the EP formula encapsulate the basic tenets of football, including: being closer to the opposing goal line and farther from your own is better; earlier downs are better (first-and-10 is better than second-and-10, etc.); shorter distance to go is better; being at home is better.” To study this comparison, all NFL plays since the 2009 season were used.
To reiterate, the x-axes represent the percent of previous plays in a given game that was either run or pass, and the y-axes represent the value of the given play. There are many data points at a value of 100% of previous plays being the same play because this only occurs in the first few plays of a game when there is no variation. It is also important to note that “blowout” games of wins by more than four possessions were excluded — since teams tend to pass a lot in desperation, causing those plays to be far less successful. The clear takeaway from Figures 7 & 8 is that repeating the same play type throughout a game does not have any impact on its EPA since the blue line of best fit has a slope of < 0.01. Something else to emphasize from these charts is the reason why these many data points were left to display, which is the fact that there are far more points toward the middle of the graph where about half of the past plays are the same play call. What this shows is the flawed concept in the NFL that there should be an even mix of plays.
Furthermore, the same graph functions were run but for the proportion of past play calls being the opposite play type — increasing previous run percentages compared to pass EPA and vice versa.
The change in EPA was similarly negligible in these cases as well. All trends were consistent throughout the past eleven seasons. The percentages are simply one minus the percentages from the previous two graphs but are shown here to emphasize that the change in EPA is negligible in these cases as well. It can reasonably be concluded from Figures 7–10 that passing does not lose any value even if teams have already called a high percentage of passes in a given game. This debunks the common myth of the importance of establishing the run, which — as mentioned briefly earlier — is the idea that teams must run the ball to keep the defense honest. From the above analysis, there is no apparent reason why teams do not throw the ball more. But exactly how much would teams benefit if they were to call more pass plays? To quantify this value for any team is difficult since there has been no team who has experimented with throwing the ball exceedingly more.
Quantifying the Value of Passing More Often
It was first necessary to compare teams’ mean pass EPAs with their run EPAs. Success rates (used earlier in the study) would not be useful in quantifying the value of passing because they only provide the percentage of times that teams are successful and not the actual value of a play.
Mean League Pass EPA = 0.0517 | Mean League Run EPA = -0.0229
In Figure 11, the discrepancies between teams’ mean pass and run EPAs are clear — on average, 2019 regular season teams’ pass plays yielded 0.0746 more expected points than run plays. Not only is passing the ball far more effective but running it is also losing teams potential points.
Furthermore, to see the actual benefit passing would have for teams, the barplot in Figure 12 was created to display the total expected points a team would earn if they were to pass the ball every time (of course, out of pass/run plays only) in the 2019 season. The y-axis (points added) was calculated by multiplying the number of run plays a team had in 2019 by the discrepancy between their pass and run EPA averages. It is important to note that this graph can be run independently of teams’ previous plays in a game since it was concluded above that both the values of passing and rushing are not at all affected by the proportion of prior plays being the same or opposite play.
On average, teams would have produced 34.33 additional points in their 2019 season had they passed the ball every time. The San Francisco 49ers’ potential 113 more points are astonishing, yet not surprising. The Niners were one of two teams that were running more than they passed, yet with a stellar QB in Jimmy Garoppolo, they averaged nearly twice as many PYPA (8.4) than YPC (4.6) and had the fifth-highest average pass EPA n. Why the 49ers decided to run the ball more is inexplicable. What is surprising, however, is that more successful teams would have benefitted even more from calling more pass plays. Six of the eight teams that made the division round of the playoffs and three of the four teams that made the conference championships were above the mean potential points added in Figure 12.
Conclusion
Teams have the opportunity to score more points by only passing the ball more often. Also, better teams tend to have greater margins between their average pass and run EPAs (take a look at the margins of these successful teams in Figure 11: Ravens, 49ers, Cowboys, Chiefs, Saints, and Seahawks). Despite these facts, teams are unwilling to experiment with their pass/run ratio — after all, teams cannot run statistics experiments when their seasons are at stake. However, what can be confirmed is that fans will continue to see teams pass more and more in the coming years. Josh Hermsmeyer of FiveThirtyEight puts it best: “The NFL is a passing league that somehow doesn’t pass enough. NFL teams know the medicine works yet stubbornly refuse to take a clinically effective dose.”
Credits
Andrew Cramer, Atharv Karanjkar, and Ethan Schwimmer were also members of the initial project and instrumental in generating ideas, coding, and modeling.
Sources Used
https://github.com/ryurko/nflscrapR-data
https://www.footballoutsiders.com/
https://www.sharpfootballstats.com/rushing-success-rate-over-average--sroa-.html
https://www.footballoutsiders.com/stat-analysis/2020/finding-optimal-passrun-ratio
https://fivethirtyeight.com/features/is-running-the-ball-back
https://fivethirtyeight.com/features/for-a-passing-league-the-nfl-still-doesnt-pass-enough/
https://thepowerrank.com/2018/09/24/the-surprising-truth-about-passing-and-rushing-in-the-nfl/
https://www.pro-football-reference.com/years/NFL/index.htm
https://www.espn.com/nfl/story/_/id/8379024/nfl-explaining-expected-points-metric
https://www.sharpfootballstats.com/situational-run-pass-ratios--off-.html
https://www.footballoutsiders.com/stats/nfl/offensive-line/2019
http://www.footballperspective.com/why-do-teams-run-the-ball-part-iii/
https://www.espn.com/nfl/story/_/id/8379024/nfl-explaining-expected-points-metric
