How passing and rushing affect winning in the NFL

bill_belichickBefore the Super Bowl, Bill Belichick told his Giants defense to let Thurman Thomas rush for 100 yards.

As David Halberstam writes in Education of a Coach, it was a tough sell before the 1991 Super Bowl against Buffalo. The New York Giants played a physical defense that prided itself on not allowing 100 yard rushers.

No matter, the short, stout coach looked straight into the eyes of Lawrence Taylor and Pepper Johnson and said, “You guys have to believe me. If Thomas runs for a hundred yards, we win this game.”

Just in case his players didn’t listen, Belichick took it upon himself to ensure Thomas got his yards. He took out a defensive lineman and linebacker and replaced these large bodies with two defensive backs. In football lingo, the Giants played a 2-3-6 defense designed to struggle against the run.

Did Bill Belichick go insane? I certainly thought so when I first read this story years ago.

However, analytics is on Belichick’s side. Let me explain.

Visual shows the importance of passing over rushing

When it comes to winning in the NFL, passing is king. Rushing hardly matters.

To quantify this, our football obsessed culture must look past misleading statistics such as rush yards per game. Teams with the lead run the ball to take time off the clock. Any team can rush for 100 yards if they run it 50 times.

To measure true skill, it is better to look at efficiency metrics like yards per attempt. A team can’t fake their way to 5 yards per carry by running the ball more.

Here, efficiency for passing and rushing is defined as yards gained per attempt on offense minus yards allowed per attempt on defense. Higher values indicate more team strength. Sacks count as pass attempts, and these negative yards lower pass efficiency on offense.

The visual shows the pass and rush efficiency during the regular season for all NFL playoff teams from 2003 through 2012.

nfl_pass_rush

From the left panel, playoff teams excel in passing, both throwing the ball on offense and preventing the pass on defense. Only 15 of 120 playoff teams in this era allowed more yards per pass attempt than they gained.

The visual also highlights teams that played in the Super Bowl. Eight of the ten Super Bowl champions were among the NFL’s elite in pass efficiency. However, excellence in the air does not guarantee playoff success. The New York Giants in 2007 and Baltimore in 2012 won the Super Bowl despite subpar pass efficiency.

Rushing hardly matters in the NFL

While the importance of passing in the NFL will not surprise anyone, the insignificance of rushing might. The visual for rush efficiency shows playoff teams as a random scatter of positive and negative values for their regular season statistics. A strong run game on offense and defense does not help a team make the playoffs.

Moreover, teams with a high rush efficiency do not suddenly become clutch in the playoffs. Almost half of the teams that played in the Super Bowl allowed more yards per carry than they gained. In 2006, Indianapolis won the Super Bowl while having the worst rush efficiency in the NFL. Green Bay in 2010 and the New York Giants in 2011 weren’t much better.

A guessing game of a team’s wins

Running the ball does not affect winning as much as you think. To illustrate this point, consider this guessing game. Suppose you want to guess how many games a team will win during the regular season. Without any other data, it makes sense to guess 8, the average number of wins in a 16 game season.

From 2003 through 2012, this estimate would be wrong by 3.1 wins. In technical jargon, 3.1 is the standard deviation of actual wins from the guess of 8. In normal people language, it says 2 of 3 teams will be within 3.1 wins of the guess. About two thirds of NFL teams won between 5 and 11 games between 2003 and 2012.

With the rush efficiency for each team, how much better does your guess get? The right panel of the visual below shows how rush efficiency relates to wins for every NFL team from 2003 through 2012. Simple linear regression gives the best fit line through the data.

nfl_pass_rush_scatter

The regression line gives a new guess about the number of games a team will win. For example, suppose a team has a rush efficiency of 0.6 yards per carry. Instead of guessing 8 wins for this team, the line gives 8.7 wins for this team.

How much better are these new guesses? Not much. The error only drops from 3.1 wins to 3.03 wins. In technical jargon, rush efficiency explains only 4.4% of the variance in wins. You might as well guess randomly.

The results get better using pass efficiency, as shown in the left panel. The error in estimating wins drops from 3.1 to 1.96. Pass efficiency explains 62% of the variance in wins in the NFL. The strong relationship is clear from the visual.

In college football, rush efficiency correlates more strongly with wins than in the NFL. Teams like Alabama, Stanford and Wisconsin have won with a power running game and a physical front seven on defense. The insignificance of running the ball is unique to the NFL.

Analytics gives a broad view of how passing and rushing affect winning. But to dig deeper, let’s look at specific teams and their strengths in these areas.

Indianapolis Colts

Under the leadership of GM Bill Polian and QB Peyton Manning, the Colts had a remarkable run from 2003 through 2010. They won at least 12 games each year before slacking off with 10 wins in 2010.

They achieved success through the air, ranking in the top 8 in pass efficiency each year. Peyton Manning and his offense played the bigger role, but the pass defense helped out some years. The Colts ranked in the top 10 in pass defense (yards allowed per attempt) from 2007 through 2009.

However, Indianapolis was really bad in the run game. Only once in this era (2007) did they gain more yards per carry than they allowed. As mentioned before, they were dead last in the NFL in rush efficiency in 2006 when they beat Chicago in the Super Bowl.

New England Patriots

New England won 125 games, 2 Super Bowls and played in 2 others during the 10 seasons covered by the visual. They followed the same script as Indianapolis: strong in passing, weak in rushing.

From 2003 through 2012, New England ranked in the top 10 in pass efficiency in each year except 2008 and 2012. In 2008, QB Tom Brady got hurt in the first game of the season. New England ended the season 13th in yards gained per pass attempt and did not make the playoffs, the only time this happened during these 10 years.

However, New England has never cracked the top 10 in rush efficiency. Coach Bill Belichick might not have seen the data presented here, but he gets the futility of rushing in the NFL. This understanding extends as far back as his days as defensive coordinator for the Giants.

Indianapolis and New England have built their teams around passing at the expense of rushing. They, along with New Orleans of recent seasons, have had success in winning games and Super Bowls. Now let’s look at teams that excel at rushing.

Minnesota Vikings

More than any other team, the Vikings dominate the ground game. They feature RB Adrian Peterson on offense and have tackles Pat and Kevin Williams clogging up the middle on defense. For the 6 years between 2007 and 2012, Minnesota has finished 1st in rush efficiency 4 of those years.

However, this strength has led to ups and downs in wins. Minnesota went 3-13 in 2011 despite leading the NFL in rush efficiency. The next season, they led the NFL again behind a monster season from Peterson, who made a remarkable return from knee surgery. The Vikings had 10-6 record that season.

The Viking’s best season over this stretch came in 2009. They finished 12th in rush efficiency that season. The difference? A QB named Brett Farve came out of retirement to play for Minnesota. The Vikings finished 7th in yards gained per pass attempt. They went 12-4 and came within a late turnover against New Orleans of playing in the Super Bowl.

San Francisco

The Niners started winning games when coach Jim Harbaugh became coach in 2011. However, they had their strengths before he arrived. Behind DE Justin Smith and LB Patrick Willis, San Francisco had an elite run defense. From 2007 through 2012, they never finished worse than 8th in yards allowed per carry.

This run defense didn’t help them win much the first 4 seasons, as the Niners won only 26 games. The pass defense never finished better than 15th during this time.

When Harbaugh arrived in 2011, San Francisco drafted LB Aldon Smith, a pass rush monster out of Missouri. They also signed CB Carlos Rogers, who had his first Pro Bowl season in 2011. The Niners have finished 9th and 3rd in pass defense in 2011 and 2012 respectively. This resulted in 24 wins during these two seasons.

How to evaluate NFL statistics

In Super Bowl XXV, Bill Belichick’s plan to let Thurman Thomas rush for 100 yards worked, maybe too well. Against a small defense designed to slow down the pass, Thomas ran for 135 yards on 15 carries, a staggering 9 yards per carry. In the second half, he broke off a 31 yard run for a touchdown.

The game ended when Bills kicker Scott Norwood sent a field goal attempt wide right. The Giants won the Super Bowl 20-19.

The Giants did not win the game solely because of Belichick’s defensive plan. The offense generated two long scoring drives in the second half that took time off the clock. And I would bet my life savings Belichick did not want his defense to allow that 31 yard touchdown run to Thomas.

But, as Halberstam discusses in Education of a Coach, Belichick did want the Bills to pick up small gains on the ground if it meant keeping Jim Kelly from throwing the ball. He understood that rushing means almost nothing to winning in the NFL.

If you’re going to remember anything from this article, it should be this: look at a team’s passing instead of rushing numbers to determine whether they will win games.

Grantland, Betting Dork and 3 football predictions

I got into some NFL football this week.

First, I agreed to appear on Betting Dork, the podcast of Gill Alexander. During the NFL season, he invites a guest to appear with his regular round table that talks NFL games. Gill is a friend and all around great guy; dork might be the last word I would use to describe him. You can listen to the podcast each week here.

Second, an opportunity at Grantland came up. They made an excellent video on Kevin Kelley, the high school football coach in Arkansas that always goes for it on 4th down and always onside kicks. They wanted a blog post to accompany the video, so they asked me this: if not punting is one revolution in football analytics, what’s the next big revolution?

My first thought was that NFL teams should stop running the ball.

While this might seem crazy, numbers back up the argument. Including negative yards from sacks, NFL teams throw for 6.10 yards per pass attempt. On the ground, they only gain 4.17 yards per rush.

Moreover, over the last 10 NFL seasons, there is no correlation between rush efficiency, measured by yards per rush on offense, and winning. I found this lack of correlation shocking. The NFL is truly a quarterback’s league. Winning teams can throw the ball downfield while preventing their opposition from doing the same.

The article left a lot of room for further analysis, as people noted in the comments. Pass efficiency might decline with a higher percentage of passes. (Note that I do not think this is a given, especially with good play calling.) There’s also a higher risk for turnovers on pass plays. Hopefully, Grantland will let me follow up on these thoughts later.

You can read the article here. Be sure to watch the awesome video at the bottom on Kevin Kelley’s Pulaski Bruins.

I do think passing matters most in the NFL, especially if you want to predict the future. Yards per pass attempt correlates with winning even more than yards per play, the key stat I look at in college football.

This analysis is based on my NFL yards per pass attempt adjusted for strength of schedule. I’ll make all these numbers available soon.

Of course, I couldn’t resist talking about a college game at the end.

Kansas City at Denver

Kansas City has been one of the luckiest NFL teams this season. They have played a soft schedule and have benefitted from turnovers. The Chiefs needed 2 defensive touchdowns to beat Buffalo 23-13 in their last game.

So I was shocked when my numbers came down on the side of the Chiefs. The line has held steady at Denver at 8, while yards per pass attempt predicts Denver by 5. What gives?

I think people understand the problems with Kansas City. ESPN ran a piece on how the Chiefs were the most troubled 9-0 team in the history of the NFL. And I think that’s right.

However, people might be missing how bad Denver’s defense is. They are 28th in my pass defense rankings, which is just terrible for a Super Bowl contender. They have been a bit better the last 3 games since Von Miller has returned.

Overall, Denver gets its edge in this game from Peyton Manning and it’s top ranked pass offense against Kansas City’s 6th ranked pass defense. Denver has better than even odds to win.

However, don’t be surprised to see the Chiefs go to 10-0, especially if they can generate a pass rush against Manning and get some more turnover luck.

Minnesota at Seattle

Seattle is a legit Super Bowl contender. Minnesota is a poor team that features Christian Ponder at QB. However, a line that favors Seattle by 12 seems like too much. Yards per pass attempt predicts a 8.6 point win for Seattle. Remember, this prediction includes the throwing performance of both Christian Ponder and Josh Freeman.

Moreover, the run game could play a role in this game. Minnesota has RB Adrian Peterson, one of the most explosive players in the game. Their rush attack, ranked 5th by raw yards per rush, faces a Seattle defense ranked 21st in rush defense. While I don’t recommend building a team around a RB like Peterson, his presence can certainly affect this game in favor of Minnesota.

Georgia at Auburn

This game plays a surprising role in the national championship race. A Georgia win (with an Alabama win over Mississippi State) locks up the SEC West for Alabama. Auburn would have 2 conferences losses, and it wouldn’t matter if they beat Alabama in 2 weeks.

However, if Auburn wins, then their game with Alabama decides the SEC West. Then an Auburn win puts Alabama out of the title picture… like I predicted in Grantland a month ago.

Can Auburn win? My team rankings predict a 6 point win for Auburn. However, these rankings can be heavily impacted by turnovers, and Georgia has 7 more give aways than take aways this season. Had they performed better in this department, Georgia probably beats Missouri in their key SEC East battle.

Yards per plays predicts a Georgia win by 2 based on the strength of their offense. Despite a rash of injuries to key skill players, QB Aaron Murray has led the Bulldogs to 6th in my offensive rankings by yards per play. The line favors Auburn by 3.5, so expect a tight game that could come down to a last second field goal.

Thanks for reading.

Did Wisconsin’s offense improve over the season? A Rose Bowl preview

The Power Rank uses strength of schedule adjustments to evaluate Wisconsin's running game.

A few weeks ago, I was in New York City to meet with Mallory Rubin and Ben Glicksman, the college football editors at SI.com. I had an idea for a Rose Bowl story. Earlier this season, I wrote a preview of the Stanford Oregon game based on statistics for drives when quarterbacks Marcus Mariota and Kevin Hogan had played. (Oregon’s Mariota would often be pulled when the Ducks built a huge lead; Stanford coach Shaw only had the sense to start Hogan late in the season.) I thought a similar analysis might be useful for the Rose Bowl. Hogan has now been Stanford’s quarterback for 5 games, and Wisconsin has shuffled through 3 quarterbacks this season.

When I sent them the numbers early last week, they liked the analysis but thought it overlapped too much with Stewart Mandel’s excellent article on Hogan. They suggested I base the preview on Wisconsin. It was not the feedback I was looking for on Christmas day. But it did prompt me to look at something I had been interested in all season: what happened to Wisconsin’s offensive line? The traditional strength of the Badgers had played so poorly the first two games of the season that their position coach was fired after two games on the job.

The analysis of Wisconsin’s rush offense became the center of my analysis of their offense. To read the full article, click here.

How Safe Is Oregon From An Upset Against Stanford?

With Alabama’s loss to Texas A&M last week, Kansas State and Oregon are the front runners to play in the national championship game. However, there is plenty of time for more upsets. With Stanford traveling to Eugene to play Oregon on Saturday night, how vulnerable are the Ducks?

Our teams rankings predict that Oregon will win by 3 touchdowns at home. This differs only slightly from the Vegas line of 20.5. But lumping an entire team into a single rating does not tell the entire story.

We have taken our team ranking algorithm and applied it to football specific statistics like yards per play. The result is rankings for offense and defense that account for strength of schedule. For Stanford, it separates an elite defense from an average offense. We also rank offense and defense for passing and rushing using yards per attempt.

It’s most convenient to consume these results in match up visuals. Below, we show the results for Stanford at Oregon. Better defenses have a blue dot further to the right. When shown next to an opposing offense, the unit with the dot further to the right is predicted to have an advantage.

These visuals let you instantly evaluate a game. Sports Illustrated used them in previewing Alabama and LSU two weeks ago in their November 5th issue. To learn more, click here.

What do they say about Oregon’s chances of staying undefeated?

When Oregon has the ball

Match up visual of Oregon's offense and Stanford's defense
Oregon’s offense scores so many points that head coach Chip Kelly often pulls his starters well before the end of the game. To account for this, we’ve combed through the play logs to identify drives in which the starters played. Through last week, we documented all the details in this post. For the blowout at California last weekend, we use plays until Oregon got the ball up 52-17 with 9:38 left in the 4th quarter.

These adjustments bump up Oregon’s offense in all categories. However, it may be surprising that Oregon’s pass offense ranks 21st. The last two weeks, quarterback Marcus Mariota has had two brilliant performances against USC and California. When we consider all the drives that Mariota has played this season, Oregon has not had an elite passing game. But a freshman can certainly improve over the season. A stand out game against Stanford’s 4th ranked pass defense will even convince our algorithm.

Can Stanford slow down the Ducks’ offense? They haven’t the last two years. But Stanford’s defense, led by linebackers Chase Thomas and Shane Skov, have made the leap to elite status this season. They must first slow down Oregon’s running game. Then they need to get pressure on Mariota when he drops back to throw. It’s a tall order, but Stanford has a better defense than any team Oregon has faced all year.

When Stanford has the ball

Match up visual of Stanford's offense and Oregon's defense
The visual shows the average play of Stanford’s offense this season. However, these season long numbers do not distinguish between the quarterback play of a nervous Josh Nunes versus a speedy Kevin Hogan. Head coach David Shaw gave the reigns to Hogan two weeks ago against Colorado.

When using drives with Hogan at quarterback, Stanford’s offense ranks 11th in the nation in adjusted yards per play. This is quite a contrast from their 47th rankings using all plays. Hogan has improved both the passing and rushing game:

  • Pass offense: 40th to 8th.
  • Rush offense: 55th to 15th.

Hogan has played against Colorado and Oregon State, the 112th and 30th ranked defenses by our numbers, the last two weeks.

However, two games does not offer a lot of data. While Stanford’s offense has most likely improved with Hogan, it’s far from certain the Cardinal are the 11th best offense in the nation. Look for the offense to score points against an Oregon defense riddled with injuries on the line and the secondary.

Oregon’s chance to remain undefeated

Our team rankings give Oregon an 87% chance to remain undefeated. But their injuries along the defensive line alone should worry Duck fans. The Vegas line started at 24 but dropped to 20.5. It might be a closer game than anyone expects.

Thanks for reading.

How To Instantly Get Smarter About Your Team’s Next Game

I was frustrated with sports websites. Sure, all the big media sites have college football statistics. You can find rankings for all 124 bowl subdivision teams in many categories. If you need even more categories, check out cfbstats.com, which has everything from turnover margin to third down conversion against championship subdivision opponents.

But what I really wanted was how a team’s statistics compared with their next opponent. If Stanford has rushed for 3.7 yards per carry this season, I want to see that number next to 2.6, the yards allowed per carry by their next opponent USC. (I just tried to find these numbers on ESPN, and they don’t even have the defensive number for USC. I found it on cfbstats.com.) Of course, if these numbers were adjusted for strength of schedule, that would be even better.

So we started designing team pages that would show these opposing statistics next to each other. My friend Angi Chau had come up with a beautiful interactive visualization for the March Madness bracket in less than a week. How hard could it be to do the same for match up statistics?

Hard. We banged our heads against the wall for months. Finally, we came up with a solution that focuses on simplicity. It’s still not completely satisfying, since there’s a learning curve for the user.

However, we’ve reduced that learning curve to a minute. The front page of our premium college football product explains how and why better defenses appear further to the right in the visualization. Then, you can instantly get a feel for your team’s next game by looking at the team pages. These pages show our rushing and passing numbers that have been adjusted for strength of schedule. The opposing units are next to each other. Click on other teams in the schedule to see different match up statistics.

I love playing with these team pages. I hope you do as well. The front page has a menu for all of the team pages so far, which includes all big conference teams.

Thanks for reading.