THE POWER RANK

  • About
    • About The Power Rank
    • Start Here
    • Contact
  • Predictions
    • Games
    • March Madness
  • Content
    • Must Read
    • Blog
    • Podcast
    • March Madness Book
  • Rankings
    • College Basketball
    • NFL
    • College Football
    • MLB
    • Cluster Luck
    • CFB yards per play
    • World Soccer/Football
  • Members
    • My Account
    • Login
    • Become a member
    • COVID-19 Policy
  • Log in

Predictions for the NFL Divisional Round Playoffs, 2015

By Frank Brank 1 Comment

2014_DivisionWhat’s the NFL without a little controversy? All news is good news for the NFL. The more folks blowing up social media on the missed pass interference call in the Cowboys-Lions game only made more tune into the game.

Conspiracy theorists rejoice.

Overall, I had a pretty solid Wildcard Round last week. Many of the outcomes ended up being as predictable as I had thought. This week will be a little more difficult as the teams get better, the weather gets worse, and the lines get tighter.

Ravens @ Patriots

The first game of the week renews the heated Flacco-Brady rivalry… just kidding.

The Joe Flacco in the Playoffs narrative continues after the Ravens beat the Steelers in Pittsburgh last week. Though his team’s record is impressive in recent years, let’s not depend on a small sample of games spread out across multiple seasons. Flacco will undoubtedly regress towards his career expectancy.

Flacco hasn’t played well on the road in his career. In 56 home games, Flacco has completed 61.7% of his 1740 passes for 7.56 yards per attempt (78 touchdowns, 35 interceptions). In 56 road games, he drops to 59.5% completion rate on 1907 attempts for 6.45 yards per attempt (70 touchdowns, 55 interceptions).

Those road numbers compare to teams like the 49ers, Titans, and Jaguars from this year. For what it’s worth, I quickly scrolled through home/road splits of other quarterbacks like Tony Romo, Peyton Manning, Tom Brady, Ben Roethlisberger and even Andy Dalton without finding a home/road difference even close to Flacco’s.

In addition, he will face New England’s 11th ranked pass defense and 12th best sack rate. That’s quite the step up from Pittsburgh’s abysmal secondary and pass rush.

The Patriots offense, ranked 6th by The Power Rank, also has a favorable match up. Tom Brady will draw the Ravens league average pass defense (15th).

Baltimore does make up for the secondary by getting after the quarterback. The Power Rank predicts they sack the opposing quarterback on 8.25% of pass attempts against average pass protection. The issue, of course, is Tom Brady doesn’t take many sacks. New England gives up a 3.7% sack rate against an average pass rush, second best in the NFL.

If you’re backing the Ravens because of Joe Flacco’s recent playoff success, you should look at the difference in his home and road performance. He doesn’t play well on the road compared to other quarterbacks.

Markets opened this game at Patriots -8.5. With some money coming in early, this line was adjusted moved down to Patriots -7.

This game is appropriately lined given the Patriots home dominance over the last decade; however, there’s some clear line value any time you can get an underdog north of seven points. Baltimore is still getting the slim majority of the bets, so this line has a small chance to get under seven points. The value would then be flipped to the Patriots.

I’ll take the Patriots to win with comfort and hope the Joe Flacco in the Playoffs story is put to rest.

Panthers @ Seahawks

The Panthers and Seahawks couldn’t be further away in the standings. However, they play similar styles of football with an aggressive defense and run first offense.

Throughout the season, the Seahawks executed that style better since they had 12-4 regular season record versus the 7-8-1 mark of the Panthers.

Continuing with the similarities, each of these teams have played some cupcake games recently. Seattle finished the season winning six straight games with two games against quarterback-depleted Arizona, two against San Francisco, Philadelphia, and St. Louis.

Carolina has won five straight against New Orleans, Tampa Bay, Cleveland, Atlanta, and a quarterback-depleted Arizona. Nonetheless, these are still professional football players and no opponent should be taken for granted.

The Panthers and Seahawks each have elite defenses. The Panthers defensive numbers are a little skewed as they’ve gotten healthy as the season has progressed and have played much better as of late.

According to The Power Rank, they still rank 13th on defense with the seventh best pass rush. Sacks have disrupted Russell Wilson and the Seahawks offense all season (8.8% sack rate).

I don’t believe this is a knock to the offensive line; Wilson has held onto the ball entirely too long. Lacking a real threat on offense could be the issue.

The Seahawks traded away Percy Harvin, leaving Doug Baldwin and Luke Wilson as the most dangerous weapons on offense. Wilson has been able to improvise with his legs; however, there is no doubt in my mind that Luke Keuchly will be spying him all game.

The Seahawks offense, ranked 17th, should struggle against a fast, opportunistic Carolina defense.

The Panthers offense will be in a similar situation. The Seahawks, who also struggled on defense at the start of the season by their standards, have worked their way up to the fifth best defense per The Power Rank.

Cam Newton has played better lately, but I expect him to have similar issues as Russell Wilson in this game.  Newton certainly has more weapons at his disposal, but he’ll also oppose the better defense.

The books have lined this game at Seahawks -10.5 after opening at Seahawks -11. This game should be much closer than that. Even with the Panthers playing much better lately, 56% of the public has laid all those points with the Seahawks.

I simply don’t think the Seahawks can score enough points to cover a double digit line. I’m going to go out on a limb and say the Panthers have a good chance to win this game with such limited scoring. One big play can change the outcome.

Cowboys @ Packers

The Cowboys narrowly scraped by last week, as we thought they might, with a little help from the referees, of course. The Packers had a week to rest, which should only help them continue their home dominance.

The Packers have a ridiculous offense, which you don’t need me to break it down. The Cowboys also have a great offense, so where is the edge for each team?

For starters, the Cowboys defense is not very good. I was supremely impressed by their second half against Detroit. They shut down the running game, pressured Stafford, and held the Lions offense to three points.

However, the Cowboys defense was terrible in the first half against Detroit. If they lay an egg in either half of this game, Aaron Rodgers will take advantage and put them away early considering the Cowboys defense ranks 27th in passing defense and 29th in sack rate.

The Packers defense may have similar issues. Though the offense started slow last week, the Cowboys have roughed up even the best of defenses, including the Seahawks in Seattle.

According to The Power Rank, Green Bay’s defense now sits 24th in passing defense and 17th in sack rate. They have certainly been better than Dallas, but it’s not a wide margin by any means.

Even with temperatures expected to be around twenty degrees at game time, I expect some points. The books expect the same with a total of 53, only trailing the Broncos-Colts total by one point.

Having an opinion on this game is difficult. I really do trust Green Bay’s home dominance, but I also trust that they will give up some points.

There’s certainly a chance the Cowboys hang in there and win this game, but I wouldn’t bet on it.

The Power Rank has the Packers by a touchdown and I agree with that number. The betting line is also hovering around Packers -6.5.

On a neutral field, these teams are very close to equals. At Lambeau, I’ll take the Packers over any team.

This is a rare game where the hot and cold of the Cowboys isn’t swaying their betting line. If you’re going to take a side, grab the Cowboys and the points, but the books got this one right.

Colts @ Broncos

Many thought the Colts were in trouble after the closing weeks of the regular season. However, their offensive line dominated the Bengals pass rush in their Wildcard game and gave Andrew Luck plenty of time to find his speedy receivers.

The Broncos got the week off they desperately needed. They have some injuries on their offensive line.  Even the Bengals horrendous pass rush was able to exploit those soft spots up front.

The Broncos face a good Colts pass rush ranked 9th in sack rate adjusted for schedule. They also have a good secondary, as the Colts pass defense is very underrated at 10th in The Power Rank.

The Broncos front will be better this week than in recent weeks. Though it’s a tall task with his quick releases, but if the Colts front seven can disrupt Peyton, they might have a chance to win this game.

Ed and I have talked previously and agree that the Broncos are a better team, at least statistics-wise, than they were last year at this point.

The Broncos are the top ranked team in The Power Rank and have the second best pass defense with a strength of schedule adjustment for yards per attempt.

Peyton Manning still has the best overall protection with the aid of his quick timing routes and the best passing attack. Very few would question that.

The questionable part is their now run-happy offense. C.J. Anderson has emerged as one of the better power backs with added quickness in the league. Realistically, though, Peyton Manning should be throwing the ball more often, as he leads the top ranked pass offense.

If the Colts want to survive and advance, they’ll need to get to Manning. It’s that simple. If he has time in the pocket, Manning has proven for nearly two decades that opposing teams have a very small chance to beat him.

I don’t foresee the pressure being sufficient and expect the Broncos to win comfortably. The books have lined this around a touchdown. The Power Rank likes the Broncos by a little more with an ensemble prediction of -8.6.

The difference is the key number of seven points. You want to be on the correct side of that number. I can live with laying 6.5 points with Denver. You probably won’t see less than a touchdown anywhere, though. I also wouldn’t be opposed to taking the points at Colts +7.5.

Outlook

I really can imagine two of the underdogs, Panthers and Cowboys, winning this week. I would rank them in that order of likelihood, as well. The Panthers being double digit dogs may disagree with me, but I love the match up.

With no games inside of 6.5 points in Vegas, they are suggesting a pretty boring Divisional round. However, we know well enough the playoffs are always exciting. Sports have insanely random outcomes in the one game samples you’ll get this week.

Frank Brank founded cheapseatanalytics.com, a site devoted to analytical sports information and betting systems. He majors in baseball but also covers the NFL and NHL. You can follow him on Twitter @realFrankBrank.

Filed Under: Baltimore Ravens, Carolina Panthers, Dallas Cowboys, Denver Broncos, Football Analytics, Green Bay Packers, Indianapolis Colts, National Football League, New England Patriots, Seattle Seahawks

How to predict interceptions in the NFL, backed by surprising science

By Dr. Ed Feng 27 Comments

photoTurnovers play a critical role in football.

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.

nfl_sack_pick_corr

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.

nfl_qb

Peyton Manning is the third point from the right, and he has thrown picks at a higher rate than this regression analysis predicts. Aaron Rodgers has the lowest interception rate of the 3 quarterbacks with better than 65% completion rate.

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.

Filed Under: Denver Broncos, Football Analytics, National Football League, Seattle Seahawks, Sports Data Visualization, Sports Wagering

Grantland, Betting Dork and 3 football predictions

By Dr. Ed Feng 5 Comments

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.

Filed Under: Auburn Tigers, College Football 2013, Denver Broncos, Football Analytics, Football Passing Analytics, Football Rushing Analytics, Georgia Bulldogs, Kansas City Chiefs, Minnesota Vikings, Seattle Seahawks

3 Insights from Accounting for Schedule Strength in Passing and Rushing Analytics

By Dr. Ed Feng 7 Comments

This is a paradigm shift for The Power Rank.

So far, we’ve been mostly about team rankings. Based on a statistical physics Ph.D. from Stanford, some guy developed an algorithm that nicely accounts for margin of victory and strength of schedule in ranking teams. And the rankings give predictions that are more accurate than the Vegas line in picking the winner of college football bowl games.

But analytics on the team level doesn’t provide much insight into American tackle football. It has become clear to us that people want a deeper application of analytics in football. How well does a team pass the ball? Run the ball? Who should win the Heisman trophy when the contenders play schedules of such varying strength? This is our first post towards applying our algorithm to answering these questions.

The Power Rank algorithm in Passing and Rushing Analytics

We’ll start with passing and rushing analytics. Traditionally, the media uses yards per game to evaluate both defense and offense in these two categories. However, this is deeply flawed. Some teams throw the ball much more than others. Using passing yards per game to compare Mike Leach’s Air Raid offense which rarely runs the ball with Air Force’s triple option offense that rarely throws the ball is meaningless.

The first step in passing and rushing analytics is dividing total yards by the number of attempts. This normalization is analogous to tempo free basketball statistics in which points, assists and just about everything else are divided by the number of possessions for a team. It allows for a fair comparison between fast break teams like North Carolina and half court teams like Northern Iowa. Dean Oliver pioneered this analysis with his book Basketball on Paper, and Ken Pomeroy uses it in his college basketball analytics.

However, yards per attempt still does not account for strength of schedule in evaluating passing and rushing. We apply our algorithm to adjust yards per attempt for schedule strength. This is particularly important in college football because of the wide range of team strength. Oregon might rush for almost 10 yards a carry against Missouri State. These rushes all count in their raw yards per rush attempt. Here, we adjust this number to account for a lower subdivision defense.

Let’s look at some rather surprising insights from these passing and rushing analytics in college football.

1. How good was the Texas pass defense?

Don’t let all those words per day fool you. Matt Hinton of CBS Sports is a numbers guy. When he served as Dr. Saturday over at Yahoo Sports, he did a very complete analysis showing the predictive power of recruiting rankings in college football. So when he recently wrote an article about how Texas’s defense struggled against top passing offenses in the Big 12, we took notice. He comments how poorly the pass defense performed against Baylor, Oklahoma and Oklahoma State last year.

Well, Baylor certainly ripped apart Texas through the air. Robert Griffin III threw for an astounding 13.7 yards per attempt against Texas, earning Griffin the Heisman trophy. But Baylor tore up everyone, topping our pass offense rankings. Our analytics predicted they would throw for 9.12 yards per attempt against an average bowl subdivision pass defense.

However, the Texas defense actually performed well against Oklahoma and Oklahoma State, holding both below their season average in yards per attempt. Overall, Texas had the 6th best pass defense last year. This is much better than the 13th they rank in raw yards per pass attempt, since they faced some very good pass offenses in the Big 12.

2. How good was Alabama’s passing defense and offense?

It’s not that surprising that Alabama had the best pass defense in the nation last year. They finished first across the board in yards per game, yards per attempt and our adjusted yards per attempt. Our analytics predict they would allow a microscopic 4.02 yards per attempt against an average subdivision pass offense. The secondary had 3 players drafted in the NFL draft, including safety Mark Barron and cornerback Dre Kirkpatrick in the first round.

However, it may be surprising that Alabama had the 10th best passing offense in the country. Quarterback AJ McCarron and crew racked up 7.22 yards per pass attempt, good for 27th in the country. When adjusting for schedule strength, they get upgraded due to 2 strong performances against LSU. Against this 2nd best pass defense, Alabama threw for about 6.2 yards per attempt in both meetings, well above the 4.53 that LSU gave up on average.

Alabama’s strength in both pass offense and defense played a large role in their National Championship run last year. Passing correlates to winning more than running. Remind us to write an article about that.

3. Which back up running back should I draft on my fantasy team?

Utah State really stands out in our rushing offense rankings. They finished 3rd, behind only the up tempo style of Oregon and the offensive line tradition of Wisconsin. Even after adjusting for schedule strength, Utah State’s rushing attack ranked higher than the pro style offenses at Alabama (11) and Stanford (21). Robert Turbin and Michael Smith, the two running backs that powered this attack, were both taken in the NFL draft and could make for interesting additions to anyone’s fantasy team.

Seattle drafted Robert Turbin, which most likely makes him Marshawn Lynch’s back up this season. While Turbin was Utah State’s leading rusher by total yards, Michael Smith actually had a better yards per carry. His 7.63 yards per rush attempt over a significant 114 carries was quite a bit better than the 6.09 of Turbin. Tampa Bay drafted Smith, and according to Athlon, he has LeGarrette Blount and fellow draft pick Doug Martin of Boise State to compete with for carries.

Here’s where analytics makes a rather bold prediction. Boise State ended last season with the 80th best rushing offense. Yes, the run first pro style offense led by quarterback Kellen Moore finished just above the bottom third of teams. They didn’t earn enough yards per attempt against rather poor rush defenses. Of course, rushing offense strongly depends on the offensive line. However, left tackle Nate Potter of Boise State got drafted, while no linemen from Utah State cracked the 7 rounds of the NFL draft. This analysis suggests that Michael Smith is a better running back than Doug Martin.

You probably don’t even need to draft Michael Smith on your fantasy team. Just take him off the scrap heap mid season.

What else?

With these passing and rushing rankings for both offense and defense, we have 480 new numbers to sort through from last season. We could go on for days writing about the passing and rushing analytics. But it would probably be better just to post last year’s rankings and let you figure it out for yourself. To see the rankings, click here.

Thanks for reading.

Filed Under: Alabama Crimson Tide, Football Analytics, Football Passing Analytics, Football Rushing Analytics, Seattle Seahawks, Tampa Bay Buccaneers, Texas Longhorns, Utah State Aggies

NFL Rankings, Week 5

By Tom Kellogg 2 Comments

Okay New England, we get it.  You’re good at football.  And St. Louis, it is likely that you’re already thinking more about the race to acquire Andrew Luck than the race to make the playoffs.  But today I’m not interested in the highs and lows of The Power Rank, I’m taking a shot at it’s sweet, juicy center.

To get a look at what truly constitutes the center of the Power Rank grouping, I used a mathematical formula for Standard Deviation, something that defines the variation from the mean (or average) in a data set.  If you’re enough of a nerd to not stick your tongue out at that definition and want to know more, you can look at Wikipedia’s explanation.

If you’re like me and most math classes made you go crossed-eyed and start drooling on yourself, all you really have to understand is that the bulk of a group (about 68%) falls within 1 standard deviation of the mean on either side, and that the bulk of the remainder (about 27%, for a total of 95% of the whole) falls within 2 standard deviations of the mean.

In other words, teams whose rating falls within 1 standard deviation of the mean (always 0.0 for the Power Rank) are all horribly mediocre.  Ok, that’s my inner pessimist coming out.  A more optimistic view for Eagles and Falcons fans might be to say that they are “on the bubble” when it comes to elite NFL teams (or horrible NFL teams, but we won’t dwell on that).  On the other hand, teams that exceed 2 standard deviations of distance from the mean are truly in a class of their own, either high class or low class depending on which side of the curve they are on.

That’s about as much explaining as I can do, although further questions about the mechanics of this process can be emailed to Ed, who will no doubt be able to give you a thorough explanation of the math that goes into this process.  For my part, I just plug numbers into a free online calculation program and analyze the output.  Ah… sweet, sweet technology.

On to football.

The standard deviation in this week’s power rank is 5.49.  That means that the bulk of teams will fall between 5.49 and -5.49, almost all teams will fall between 10.98 and -10.98, and teams beyond those ratings are truly special.

Congratulations to the Patriots (#1, 15.79) and the Packers (#2, 11.31) for pushing the limits and existing beyond the norm.  Perhaps even more congratulations are deserved by St. Louis (#32, -9.89) for not exceeding the norm…

Very few teams fall between the first and second standard deviations.  On the high side only Baltimore, Detroit, and New Orleans (by a hair) make the grade as especially good teams, whereas on the low end Denver, Arizona, Cleveland, Kansas City, Seattle, and St. Louis all currently qualify as truly not very good teams.

That leaves the other 21 teams in the true statistical middle of the road.  Being in the middle isn’t all that bad, as you are supposedly as close to the top as you are to the bottom.  This is great news for 2010’s weekly bottom dweller Carolina, who finds themselves just within the boundaries of that first standard deviation, but not great news for teams hoping to return strong and make another playoff run like Pittsburgh, Atlanta, or Philadelphia.  Most importantly for these middling teams, their current ratings are not a death warrant for the season, they have no cause for alarm and no need whatsoever to join in the chase for the Andrew Luck Sweepstakes.

A few things to consider for these middle teams:

1.  The current standard deviation is almost 1 point bigger than it was at the end of last year when it ended up at 4.59.

2.  At the end of last season The Power Rank was a little more balanced with one team above 2 standard deviations (New England) and one team below (Carolina).  Currently the two teams exceeding 2 standard deviations from the mean are both on the high side. Most likely, either New England or Green Bay will fall back into the sweet center during the season.

3.  When one (or both) of the juggernauts fall they will bring that standard deviation down with them.  This will cut some teams out of of the running for average status (look out Indianapolis, Jacksonville, and Carolina!) but on the upside a few teams may be thrust into greatness without needing to earn it (it may finally be the year for Houston or San Diego to go all the way).

4.  When the standard deviation shrinks a couple struggling teams may also become hopeless.  But come on, we are only one quarter of the way through the season!  Now is the time for Vikings fans to Ponder over whether or not they can finish out 12-4, Miami fans to Marshall their courage, and Colts fans to…  oh, who am I kidding?  Without Manning they have lost their identity…  they should focus on battling St. Louis and Kansas City in the race for the #1 draft pick in 2012.

Filed Under: Arizona Cardinals, Atlanta Falcons, Baltimore Ravens, Carolina Panthers, Detroit Lions, Green Bay Packers, Indianapolis Colts, Kansas City Chiefs, Minnesota Vikings, National Football League, New England Patriots, New Orleans Saints, Philadelphia Eagles, Pittsburgh Steelers, Seattle Seahawks, St. Louis Rams

« Previous Page
Next Page »

Predictions from Ed Feng

I use my Stanford Ph.D. in applied math to make football and March Madness predictions.

To get a sample of my best American football predictions and March Madness cheat sheet, sign up for my free email newsletter.

Enter your email and click on "Sign up now!"

Popular Articles

  • How to win your NCAA tournament pool
  • The ultimate guide to predictive college basketball analytics
  • How to predict interceptions in the NFL
  • Accurate football predictions with linear regression
  • The surprising truth about passing and rushing in the NFL
  • Football analytics resource guide
  • The Reason You Can’t Avoid The Curse of Small Sample Size
  • The essential guide to predictive CFB rankings
  • How computer rankings make you smarter about sports
  • How to win your college football bowl pool
  • Do you make these 3 mistakes with college football statistics?
  • The Top 10 Things to Know About The Power Rank’s Methods
  • 5 insights from academic research on predicting world soccer/football matches

Recent Articles

  • Members: College basketball predictions for Saturday, February 26, 2021
  • Podcast: Ed Feng on How to Win Your March Madness Pool
  • Podcast: Adam Stanco on Predicting March Madness 2021
  • Podcast: Rufus Peabody on Predicting the Super Bowl and Props
  • Members: Super Bowl Props

© 2021 The Power Rank Inc., All rights reserved.

About, Terms of Use, Privacy Policy

Get a sample of my best football predictions

While I usually save my best predictions for paying members of the site, I offer a sample in my weekly email newsletter.


To get this service, sign up for my free email newsletter.


Enter your email and click on "Sign up now!"

No thanks, I'll make predictions without data and analytics.

{"cookieName":"wBounce","isAggressive":false,"isSitewide":true,"hesitation":"","openAnimation":false,"exitAnimation":false,"timer":"","sensitivity":"","cookieExpire":"","cookieDomain":"","autoFire":"","isAnalyticsEnabled":true}
  • About
    • About The Power Rank
    • Start Here
    • Contact
  • Predictions
    • Games
    • March Madness
  • Content
    • Must Read
    • Blog
    • Podcast
    • March Madness Book
  • Rankings
    • College Basketball
    • NFL
    • College Football
    • MLB
    • Cluster Luck
    • CFB yards per play
    • World Soccer/Football
  • Members
    • My Account
    • Login
    • Become a member
    • COVID-19 Policy