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Remembering Earl Morrall

Morrall in Super Bowl V

Morrall in Super Bowl V.

Five days ago, Earl Morrall passed away at the age of 79. His story is well-known to many, but it’s one worth recounting for the uninitiated.

Born in Muskegon, Michigan, Morrall was a star quarterback and baseball player at Michigan State.  He made it to the College World Series in 1954 as an infielder, and a year later he guided the Spartans to a 9-1 record as a senior and a victory over UCLA in the Rose Bowl. Morrall was selected by San Francisco with the 2nd overall pick in the 1956 draft, where he sat behind Y.A. Tittle for a year.

In that draft, Pittsburgh used the first overall pick on safety/kicker Gary Glick, who had been a jack of all trades in college, but the team quickly had buyer’s remorse. After the 49ers selected John Brodie with the third pick in the 1957 draft, the Steelers saw an opportunity to acquire Morrall, and did so by sending two future first round picks (and linebacker Marv Matuszak) to the 49ers for Morrall.1

Why was Pittsburgh so desperate to trade for him? Because Pittsburgh really needed a passer: the only other quarterbacks on the roster at the time were a pair of 22-year-olds named Len Dawson (yes that Len Dawson), whom the Steelers selected with the 5th pick in the ’57 draft, and Jack Kemp (yes that Jack Kemp). The Steelers knew you couldn’t count on young quarterbacks — the team released a 22-year-old Johnny Unitas two years earlier — which explains the trade with the 49ers.  As a reminder, just about everything Pittsburgh did before 1970 was a disaster.

Morrall produced solid numbers as the Steelers starter in ’57, but threw seven interceptions in his first two starts with the Steelers in 1958. Pittsburgh’s head coach at the time was Buddy Parker, who had coached the Lions from 1951 to 1956.  Parker was not content to turn the job over to Dawson, so he traded Morrall and a pair of picks2 to Detroit for his old quarterback, Bobby Layne. [click to continue…]

  1. The trade occurred in September 1957, so the two first round picks were Pittsburgh’s 1958 and 1959 selections. Neither panned out for San Francisco — the players selected were Jim Pace and Dan James. []
  2. One of whom likely turned into the great Roger Brown []
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Why Aren’t Teams Better At Drafting Now?

The NFL Draft has emerged from an afterthought to the center of the sports world every April spring. A cottage industry of draftniks has emerged. Teams spend more time, money, and other resources on scouting than ever before. Scouting departments have grown exponentially in both size and sophistication. The Draft used to be much less important, as evidenced by the way teams happily traded away future first round picks like they were fringe benefits. Over the last 45 years, teams should have become a lot better at drafting. But have they?

Measuring how well teams draft in the aggregate is not easy.  But suppose teams were perfect at drafting. In that case, the first pick would always turn out to be better than the second pick, the second pick would always turn out to be better than the third pick, and so on.  Right?

Well, maybe not. Nobody quite knows the ratio, but player development is a crucial part of the drafting process. Prospects do not come to the NFL as finished products, and it’s up to the team (and the player) to turn that college athlete into an NFL player. Making a selection on draft day is just step one, not the final step. When a player busts, is it the fault or the person in charge of the draft or the person in charge of the development?  When a player booms, is it because of the GM or the coach? I don’t know.  You don’t know. Nobody knows.

But we do know that player development is an important variable, so even in a perfect drafting world, we probably wouldn’t expect each player to turn out to have a better career than the player drafted after him. But comparing draft status to player production seems like the most basic and obvious way to measure draft efficiency. Frankly, I don’t know even how else one would measure draft efficiency than by comparing draft slot to player production.  I’m open to other ideas in the comments, but here’s what I did. [click to continue…]

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Last Wednesday, I looked at every time a team traded away a future first round draft pick in the last ten years. Today, the reverse: the times a team traded for a future first round pick.  I’ll again be focusing on the general manager or other person responsible for making the trade: that’s because future first round picks are generally discounted, and I’m curious to see how often patience is rewarded.  As we’ll see in our first example, hurting the team in the short term — even if the move looks brilliant in retrospect and is a win in the long term — does not necessarily mean much for the man making the deal.

1) Cleveland trades Trent Richardson to the Colts for a 2014 first round pick (Sept. 2013)

As a reminder, it was Tom Heckert who drafted Richardson with the third overall pick, so Lombardi doesn’t deserve any blame for the poor decision there.  In theory, Lombardi should have been rewarded for managing to still get a first round pick for Richardson, but instead, he just stacked the 2014 draft for Farmer.  For the franchise, it’s hard to view this trade as a great deal, because it’s connected to Richardson the draft pick (the Browns turned the 3rd pick in 2012 into the 26th pick in 2014). But as an isolated move, this one looks pretty strong for Cleveland and definitely for Lombardi, especially after how poorly Richardson performed in Indianapolis in 2013.

2) St. Louis trades 2012 first round pick (#2; Robert Griffin III) to Washington for 2012 first round pick (#6; Morris Claiborne), 2012 second round pick (#39; Janoris Jenkins), and 2013 first round pick (#22; Desmond Trufant) and 2014 first round pick (#2 overall) (March 2012)

A year ago, this trade arguably would define the Snead/Fisher era — in a bad way. Now, the Rams have managed to use one very valuable asset to restock the roster. Along with other trades, St. Louis wound up with four top 50 picks in 2012, two first round picks in 2013, and two more this year, including the second overall selection.  That hasn’t translated into much success on the field yet for Snead and Fisher, but it’s important to remember how bare the cupboard was when the duo arrived in 2012. Right now, this trade looks like a lopsided deal, but if RG3 can replicated his rookie season in 2014 — and Sam Bradford had another mediocre year — and the pendulum could swing again.

It’s worth noting that few decision makers would have been tempted to pull off this move. Fisher came to St. Louis in 2012 and was handed significant control.  That’s vital when a major part of the compensation involved a two year wait; that wasn’t a concern for Fisher, but I suspect it would be for most.

3) Cincinnati trades Carson Palmer to Oakland for 2012 first round pick (#17; Dre Kirkpatrick), 2013 second round pick (#37; Giovani Bernard) (October 2011)

Bernard and Kirkpatrick both look to be long-term starters in Cincinnati, while Palmer may have retired if the Bengals hadn’t traded him. This was an all-time great trade for Cincinnati and Lewis. The cherry on top is that Hue Jackson, who orchestrated the trade for Oakland, was Bernard’s position coach last year and will be the Bengals offensive coordinator in 2014. While the compensation wasn’t quite as generous, that’s as if Mike Lynn, the Vikings old general manager, moved on to the Dallas front office after the Herschel Walker trade.

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Turnover Among Targets, Part II

Yesterday, I looked at team turnover in the passing game for every team in 2013. You can review the pretty complicated1 formula in that post, but the short version is to give each player credit for the lower of two values: his percentage of team receiving yards in Year N and his percentage of team yards in Year N-1. Today, I use that same concept to analyze team passing for every year since the merger.

And the team with the greatest receiving turnover in NFL history (even including pre-1970 teams) is the 1989 Detroit Lions. Take a look at the players who caught passes for Detroit in 1988:

Receiving
No. Age Pos G GS Rec Yds Y/R TD Y/G
82 Pete Mandley 27 PR/WR 15 14 44 617 14.0 4 41.1
33 Garry James 25 RB 16 16 39 382 9.8 2 23.9
80 Carl Bland 27 wr 16 2 21 307 14.6 2 19.2
89 Jeff Chadwick 28 WR 10 8 20 304 15.2 3 30.4
83 Gary Lee 23 KR/wr 14 6 22 261 11.9 1 18.6
30 James Jones 27 FB 14 14 29 259 8.9 0 18.5
87 Pat Carter 22 TE 15 14 13 145 11.2 0 9.7
49 Tony Paige 26 rb 16 2 11 100 9.1 0 6.3
81 Stephen Starring 27 6 0 5 89 17.8 0 14.8
38 Scott Williams 26 11 0 3 46 15.3 0 4.2
81 Mark Lewis 27 te 3 3 3 32 10.7 1 10.7
41 Paco Craig 23 8 0 2 29 14.5 0 3.6
26 Carl Painter 24 12 0 1 1 1.0 0 0.1
Team Total 26.2 16 213 2572 12.1 13 160.8

[click to continue…]

  1. While I admit to it being complicated, I think the added value in accuracy is worth the added layer of complexity; frankly, I can’t think of a simple way to calculate turnover that really captures what analysts value. []
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Turnover Among Targets, Part I

Cam may need to really be Superman in 2014

Cam may need to really be Superman in 2014.

The Carolina Panthers have experienced a lot of turnover this offseason. Steve Smith (Baltimore), Ted Ginn (Arizona), Domenik Hixon (Chicago), and Brandon LaFell (New England) are all gone. Those four players were the only wide receivers to catch a pass for Carolina in 2013, and they accounted for 59% of the Panthers receiving yards. last year. What does this mean for Cam Newton? Last August, a couple of star quarterbacks appeared to be going through some similarly significant turnover among their targets.

Tom Brady lost four of his top five targets from 2012 and the fifth was Rob Gronkowski; in retrospect, most people underestimated how big of an impact this would have on Brady’s numbers. Meanwhile, Ben Roethlisberger’s receivers were a big question mark entering the season, but a monster year from Antonio Brown prevented Roethlisberger’s numbers from tanking. As it turned out, Roethlisberger didn’t wind up having much turnover, but the quarterback who experienced the second-most turnover wound up winning the Comeback Player of the Year award.

For Carolina, I think some of the departures have been overblown. The defense should again be one of the best in the NFL, and it’s not as though the passing game was outstanding last year. Greg Olsen led the team in receptions, receiving yards, and receiving touchdowns last year, and he’ll be back in 2014. In addition, the Panthers averaged 7.4 yards per attempt on passes to Greg Olsen last year and 7.1 yards per attempt (the league average) on passes to all other players. Carolina signed Jerricho Cotchery, Jason Avant, Tiquan Underwood, and Joe Webb, should draft a receiver or two in May, and has a potential sleeper in Marvin McNutt. I think they’ll be just fine, mostly because that’s all the passing game was last year.

Since it’s still a bit early to figure out exactly how the Panthers passing game will look in 2014, I thought we could use some time this weekend to review some history. Which teams have experienced the most turnover among their targets? And how do we even measure such a thing? [click to continue…]

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Peyton Manning’s time in Indianapolis was peppered with record-breaking moments that have been very well-publicized. But a relatively unknown record occurred during the nascent days of the Manning Era. In 1999, Edgerrin James rushed for 1,553 yards, an impressive accomplishment in any era. But here’s what’s really crazy: Manning was second in the team in rushing yards with 73! Keith Elias was the only other running back to record a carry, and he finished with 28 yards (Marvin Harrison and Terrence Wilkins added six total rushing yards). This means James recorded 93.6% of all Indianapolis rushing yards that season, still an NFL record, and one that is in no danger of being broken in the near future.

Second on the list of “largest percentage of the rushing pie” is … Edgerrin James for the Colts the following season. In 2000, he was responsible for 91.9% of all Indianpolis rushing yards. Only three other players have ever gained 90% of all team rushing yards: Emmitt Smith, Barry Sanders, and … Travis Henry. The table below shows the top 100 seasons as far as percentage of team rushing yards: [click to continue…]

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The 2014 NFL Schedule

The color-coded NFL schedule is back!

Download the Excel file here: 2014-NFL-SCHEDULE

That Excel file contains full page and wallet-sized copies of the schedule, in both color and black and white. On the wallet-sized copies, the line between weeks 8 and 9 has been enlarged — that is where you want to fold the paper in half to put in your wallet.

iPhone page: http://www.footballperspective.com/wp-content/uploads/2014/04/2014-iphone-schedule.png

Go to that page on your phone, then hit your power and home button at the same time to take a photo (or hit the button on the middle of the Safari browser and click ‘save image.’) The schedule has been formatted to fit an iPhone screen, so you can always carry the schedule with you.

Of course, you don’t need an iPhone or Excel to view the NFL schedule: [click to continue…]

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When a general manager trades away a future first round pick, it’s worth wondering if the transaction was the effect of the principal-agent problem. A general manager is supposed to act in the best interest of the franchise, but he may instead choose to act in his own self-interest. If he’s on the hot seat, trading a future first round pick for something right now may be a pretty attractive option, as he may not be around when the bill comes due.

Does that happen in practice? The most obvious example I can think of involved the Raiders in 2011.  On October 8th, Al Davis passed away. Eight days later, starting quarterback Jason Campbell went down for the season with a collarbone injury. With the owner and general manager positions unsettled, head coach Hue Jackson became the de facto head of football operations. And he traded first and second round picks to Cincinnati for Carson Palmer. Had the move worked out and the 4-2 Raiders gone on to make the playoffs, Jackson would have been very happy. When the move failed, the Raiders missed the playoffs and Jackson was fired. As a result, it was Reggie McKenzie sitting at the table when the bill arrived.

[click to continue…]

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By now, you know about guest blogger Andrew Healy, an economics professor at Loyola Marymount University and author of today’s post. There’s now a tag at the site where you can find all of his great work. He’s back with a cap to his excellent series about playoff performance, and today’s post will not disappoint:



The Purple People Eaters never won a Super Bowl

The Purple People Eaters never won a Super Bowl.

We know the teams that have experienced consistent heartbreak at the altar. But is it the Vikings, Eagles, or Bills that are the most unlikely to have never won a Super Bowl? On the flip side, we know the teams that stacked championships on top of championships. But is it the Packers, Steelers, or 49ers that have made the most of their chances?

For the latter question, it turns out that it’s option D, none of the above.  One mystery team has won four championships despite having had a pretty decent chance of never winning a single Lombardi.  The most unlikely team never to win a Super Bowl turns out to be a team that lost “only” two Super Bowls, but that has led the NFL in DVOA four times since 1979.

To figure this stuff out, I’ve utilized DVOA ratings and estimated DVOA ratings to rerun the NFL playoffs. In the simulations, the slate is wiped clean, which means there’s no reason The Fumble or The Helmet Catch or The Immaculate Reception have to happen this time around.

In last week’s post, I went decade by decade to look at the best teams, and also those that most let opportunity slip through their fingers. Today, I bring it all together. I compare what might have been with what actually was for the NFL from 1950 to 2013. I’ll also hand out awards for the teams that were the most unlikely winners and the most unlikely losers of all time. [click to continue…]

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Johnny Jaguar

Johnny Jaguar.

A couple of years ago, I wrote that when a team misses on a first round quarterback, someone tends to gets fired (update here). I identified 22 quarterbacks drafted in the first round between 1998 and 2010 who did not turn into stars: in nearly every case, the offensive coordinator and/or head coach was fired.

Jacksonville has underdone significant upheaval over the past few years. In January 2012, Shahid Khan acquired the Jaguars. The general manager at the time was Gene Smith: after a 2-14 season, Smith was fired, and Khan brought in his man, David Caldwell.

Caldwell brought in his own man, too, when he replaced Mike Mularkey with Gus Bradley. The new management team also inherited Blaine Gabbert, the 10th overall pick in the 2011 draft. After two poor seasons from Gabbert before they arrived, Caldwell and Bradley could have decided to select a quarterback in the 2013 draft. But with the 2nd overall pick, there was no Andrew Luck or Robert Griffin III available, and the Jaguars selected offensive tackle Luke Joeckel.

When Jacksonville was on the clock at the top of the second round, the only quarterback off the board was EJ Manuel. The Jaguars could have drafted Geno Smith, but instead selected Jonathan Cyprien. In the third round, Mike Glennon was still available, but the team picked Dwayne Gratz. In the fourth round, before Matt Barkley, Ryan Nassib, Tyler Wilson, and Landry Jones were drafted, the Jaguars took Ace Sanders.

[click to continue…]

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Running backs getting shorter and heavier

Short and stout is what NFL teams look for in a running back

Short and stout is the ideal look.

In December, I noted that fewer rushing yards are coming from first round picks. That’s a trend that seems very likely to continue in 2014, and perhaps for the foreseeable future. As it turns out, running backs are also getting shorter and heavier.

LeSean McCoy, Alfred Morris, Frank Gore, Knowshon Moreno, Zac Stacy, DeAngelo Williams, Maurice Jones-Drew, Ray Rice, Giovani Bernard, Trent Richardson, Doug Martin, Danny Woodhead, and Mark Ingram are all 5’10 or shorter. As you can probably infer from the sheer quantity of the group, those players aren’t significant outliers: the “average” running back, weighted by rushing yards last season, was only five feet and 11.1 inches tall. That means backs like Jamaal Charles (6’1), Matt Forte (6’1), and Adrian Peterson are more outliers than the 5’10 backs.

This is a weighted average, so McCoy (who had about 3% of all rushing yards from running backs last year) counts three times as much as, say, Donald Brown when calculating the 2013 (weighted) average running back height. Regular readers will recognize that this is the same methodology I used when calculating the average (weighted) average of each team’s receivers last season. The graph below shows the average weighted height of all running backs since 1950: [click to continue…]

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Interesting stat about LeBron James courtesy of Tim Reynolds: The Heat superstar has increased his field goal percentage in seven straight seasons. Take a look at his field goal percentage by season:

Season Age Tm FG%
2003-04 19 CLE .417
2004-05 ★ 20 CLE .472
2005-06 ★ 21 CLE .480
2006-07 ★ 22 CLE .476
2007-08 ★ 23 CLE .484
2008-09 ★ 24 CLE .489
2009-10 ★ 25 CLE .503
2010-11 ★ 26 MIA .510
2011-12 ★ 27 MIA .531
2012-13 ★ 28 MIA .565
2013-14 ★ 29 MIA .567

Now as you guys can probably figure out, I’m not terribly invested in the career of LeBron James or basketball stats. But one thing I know is that improving on any metric in seven straight years is really freakin’ rare.

How rare? Only one quarterback in NFL history has increased his passing yards output in six straight years. That quarterback actually increased his passing yards per game in eight straight seasons, but no other quarterback can come close to matching that feat, either. Can you guess who our mystery quarterback is?

Trivia hint 1 Show
Trivia hint 2 Show
Trivia hint 3 Show
Click 'Show' for the Answer Show

Here, take a look at his career stats:

Click 'Show' Show

So while 1) my interest in basketball is limited, and 2) as Neil would tell me, field goal percentage is meaningless, simply increasing your performance in any stat for seven straight years is remarkable. No running back has ever increased their rushing output in seven straight years, although Earl Ferrell (if you count his rookie year of zero rushing yards per game, 1982-1988) and Pete Johnson (1977-1983) both increased their rushing yards per game in six straight years.

No receiver has seen a seven-year increase in any stat, either.  However, three players have increased their number of receptions in six straight years: Jason Avant (2006-2012), Raymond Berry (1955-1961), and Reggie Wayne (2001-2007). However, none of them managed to pull off that feat in receiving yards.

But two other players did: Tim Brown (1989-1995) and Marcus Pollard (if you count his rookie year of zero receiving yards, 1995-2001) increased their receiving yards in six straight seasons. And Leonard Thompson (1977-1983), Brown, and Pollard were the only players to increase their receiving yards per game in six straight years.

So whatever you think of LeBron, just know that here’s one more reason a stats geek could find his career fascinating.

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Which College Conferences Dominate the NFL Draft?

On Sunday, I used my draft value chart to determine how NFL teams valued various positions. Today, I’ll use the same method to see which schools and conferences dominate the NFL Draft. You are not going to be surprised to discover that USC Trojans have dominated the draft over the last ten years. You’ll be even less surprised to see that SEC teams have accumulated the most draft value, and the most value per team, of any conference. But let’s put some numbers on what we all know. Here’s what I did:

1) Using these draft values, assign a value to every pick in every draft from 2004 to 2013.

2) Calculate the amount of draft capital assigned to each college team by summing the values from each draft pick for each player from that college.

3) Sum the values for each school in each conference. Note: I am using the school-conference affiliations as of the 2013 season, so the SEC gets credit for the last ten years of Texas A&M, and the ACC gets a decade worth of Pitt draft picks. (Speaking of Pitt, regular readers may recall last year’s two posts on college and NFL team connections). On the other hand, Maryland and Rutgers are not credited to the Big Ten… yet. This is almost certainly not the ideal way to handle the situation, but any other approach would be too time consuming and as a reminder, nothing about college football makes any sense, anyway.

Based on that methodology, the table below shows the 100 schools that have produced the most draft value from 2004 to 2013. By default, I’m listing only the top 10, but you can change that in the dropdown box to the left: [click to continue…]

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In January, I calculated the AV-adjusted age of every team in 2013. In February, I looked at the production-adjusted height for each team’s receivers. Today, we combine those two ideas, and see which teams had the youngest and oldest set of targets.

To calculate the average receiving age of each team, I calculated a weighted average of the age of each player on that team, weighted by their percentage of team receiving yards. For example, Anquan Boldin caught 36.7% of all San Francisco receiving yards, and he was 32.9 years old as of September 1, 2013. Therefore, his age counts for 36.7% of the 49ers’ average receiving age. Vernon Davis, who was 29.6 on 9/1/13, caught 26.5% of the team’s receiving yards last year, so his age matters more than all other 49ers but less than Boldin’s. The table below shows the average age for each team’s receivers (which includes tight ends and running backs) in 2013, along with the percentage of team receiving yards and age as of 9/1/13 for each team’s top four receiving leaders: [click to continue…]

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In case you haven’t heard, the St. Louis Rams are running a contest to predict the team’s 2014 schedule. lThe prize is $100,000, which sounds nice until you realize that to win, you must accurately predict not only the opponent each week, but the location and the exact day of the game. Nobody is going to win this contest. Nobody is going to come close to winning the contest. It’s a personal information/PR grab and nothing more.  Normally, this wouldn’t bother me, but it’s not like the Rams are giving away a billion dollars.  For a hundred grand — which is less than two percent of the amount of dead cap space being allocated to Cortland Finnegan this season — the team shouldn’t have needed to make it impossible for anybody to win. Considering the rules, St. Louis might as well have announced that the grand prize is eleventy billion dollars.

So what are the odds of winning this contest? Let’s start with an easier problem than the one at hand: predicting the Rams opponent in each week of the season.

With 17 weeks, there are 17 possible opponents once you include home/road designations and the bye week. Therefore, you have a 1-in-17 chance of correctly guessing the Rams opponent in week one. By extension, you have a 1-in-16 chance of correctly guessing who St. Louis plays in week two, assuming you were correct with your guess in week one (this is what we mean by conditional probabilities). Do this for every week of the season, and by week 17, you have a 100% chance of correctly guessing who is on the team’s schedule.

It may not be intuitive exactly how daunting a task this is. But this is much, much harder than Warren Buffet’s bracket contest.  For example, you only have a a 1-in-272 chance of correctly guessing who the Rams opponents will be in the first two weeks of the season. That drops to 1-in-4,080 through three weeks, 1-in-8.9 million through six weeks, and 1-in-8.8 billion through nine weeks. That already makes it harder than the bracket contest, and you still have the back eight to play. The odds of correctly guessing the opponent each week is 1-in-356 trillion. And remember, this is quite a bit easier than the actual contest!

But let’s make some adjustments based on the information we know (which will lower the odds) and the added conditions one must satisfy (which will drastically increase the odds).

Adjustment #1

The first adjustment to our 1-in-356 trillion likelihood lowers the odds. If we assume that each team plays a division opponent in week 17, that makes the contest ever so slightly easier. If we work in reverse order, you now have a 1-in-6 chance of guessing the week 17 opponent (remember, you need to specify game location), a 1-in-16 chance of guessing the week 16 opponent assuming your week 17 selection was correct, and so on. This improves your odds all the way to 1-in-126 trillion. Hooray? [click to continue…]

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Ranking the Almost Dynasties, Part II

Andrew Healy is back with a sequel to his popular post. As always, we thank him for his generous contributions. Andrew Healy is an economics professor at Loyola Marymount University. He is a big fan of the New England Patriots and Joe Benigno.



A couple of weeks ago, I went decade-by-decade since the 1970 AFL-NFL merger to identify the teams that were the best of their eras and the teams that nearly became the teams we remember most instead. In those rankings, I used Pro Football Reference’s Simple Rating System to estimate team strength. Today, I use Football Outsiders’ DVOA ratings and go back an additional twenty years. Using DVOA produces some pretty notable differences that were bigger than I would have guessed.

What are some of those changes?

  • The Steelers have been supplanted as the true team of the ‘70s.
  • The best team to win no titles changes for three of the decades.
  • The ‘70s Vikings get replaced by a more recent what-might-have-been team as the best to win nothing in the Super Bowl era.

Before we get to that, I cover the 1950s and 1960s, identifying the true teams of those decades and the what-might-have-been teams. In a follow-up post, I’ll bring it all together and identify the franchises that have maximized their championship potential the most, and those that have left the most money on the table. [click to continue…]

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Luck's rushing ability makes him a QBR star

Luck's rushing ability makes him a QBR star.

A few weeks ago, I put ESPN’s Total QBR under the microscope. Today, I want to look at the quarterbacks whose passing statistics most differ from their QBR grades.

Total QBR grades go back to 2006, so to start, I ran a regression using Adjusted Net Yards per Attempt to predict Total QBR. The best-fit formula was:

Total QBR = -13.5 + 11.23 * ANY/A

For those curious, the R^2 was 0.80, indicating a very strong relationship between ANY/A and Total QBR. What this formula tells us is that a passer needs to average 5.65 ANY/A to be “projected” to have a QBR of 50; from there, every additional adjusted net yard per attempt is worth 11.2 points of QBR. Last year, Peyton Manning averaged 8.87 ANY/A, which projects to a QBR of 86.2. In reality, Manning had a QBR of “only” 82.9; this means Manning’s QBR says he wasn’t quite as amazing as his excellent efficiency numbers would indicate (to say nothing of his otherworldly gross numbers). One likely reason for this result is that Manning ranked 29th in average pass length in the air (according to NFLGSIS) and 6th in yards after the catch per completion; this matters because ESPN gives more credit to quarterbacks on the yards they accumulate through the air. (Throughout this post, we will be forced to deal with educated guesses, because Total QBR is a proprietary formula.)

As it turns out, Manning rating higher in actual QBR than projected QBR is a stark departure from prior years. In 2012, he finished 7.2 points higher in actual QBR than projected QBR, but that’s nothing compared to his time with the Colts. In five years in Indianapolis during the Total QBR era, Manning finished at least 10 points higher in actual QBR each season.

Along with Manning, Matt Ryan and Andrew Luck are the two quarterbacks who are most likely to over-perform relative to their “projected” ratings. Let’s be careful about exactly what this means: whatever the ingredients that go into the QBR formula that don’t go into the ANY/A formula, Manning, Ryan, and Luck seem to have a lot of them.

Luck is a fascinating case. In 2012, he ranked just 20th in ANY/A, but 11th in QBR. I wrote several articles during Luck’s rookie season about how his QBR ratings surpassed his standard stats.1 Last year, he ranked 16th in ANY/A and 9th in QBR. Does this make Luck the quarterback most underrated (if you buy into QBR) by his traditional passing numbers (if you buy into ANY/A)? [click to continue…]

  1. Although now I can’t recall if his 2012 ratings were inflated because of his 4th quarter comebacks.  And I can’t check, because once ESPN decided to cap the clutch weight associated with each play, they retroactively applied the current formula across past years. []
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Analyzing Position Values in the NFL

Every draft pick has a value, as seen in my draft value chart.  When the first overall pick is used on a quarterback, that means the quarterback position gets credited with 34.6 picks. If you assign a value to every pick in each of the last ten drafts, you can get a sense of the amount of value spent on each position in the NFL in an average draft. The graph below shows the percentage of the draft value pie attributed to each position; for example, quarterbacks are selected with 7% of all draft capital:

[click to continue…]

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2014 Running Back Free Agent Market

The free agent running back market has been as peculiar as it’s been quiet. There have been no big contracts doled out and only a few sizable ones of note, although some of the ensuing narrative about the demise of the running back position has been overblown. Today I want to look at the ten biggest free running back signings1 of 2014 and see what conclusions we can draw.

Player contracts are notoriously complicated to analyze; I won’t pretend that we can truly and fully measure contracts handed out by ten different teams. But I won’t let the perfect be the enemy of the great: armed with the understanding that this analysis is not perfect, we march onwards. Over The Cap publishes detailed salary cap information, including the total value of the contract, the average per year, the amount of guaranteed money (which is never as clear as it sounds), the guaranteed money per year, the percent guaranteed, and the number of years.  I’ve added one additional column: the approximate value of the contract in the first two years, which in itself is pretty tricky to calculate.2 It’s not close to perfect, but no method is, and I thought this was a better metric by which to sort the table than any other. Take a look: [click to continue…]

  1. Excluding Joique Bell, who was a restricted free agent. []
  2. For players on one-year contracts, I averaged the guaranteed amount and the total amount, and multiplied that average by two. For players on two-year contracts, I averaged the guaranteed amount and total amount. For players on three- or four-year contracts, I treated the first two years as fully guaranteed and ignored the remainder. []
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Owen Daniels and Gary Kubiak, Together Again

A couple of years ago, I wrote this post about Josh McDaniels and Brandon Lloyd. Well, with Owen Daniels reuniting with Gary Kubiak in Baltimore — lest you forget, Kubiak is the Ravens new offensive coordinator with Jim Caldwell now head coach in Detroit — I thought it might be fun to look at previous examples of a tight end playing with a head coach or offensive coordinator in two different cities. I’ve found nine examples since 2000 (minimum 400 yards by that tight end in at least one season of his career), including another Kubiak favorite.

Dallas Clark and Jim Caldwell in Baltimore in 2013 (after Indianapolis)

Clark was a productive tight end/slot receiver in Indianapolis for nine years, but he was released in the post-Peyton Manning makeover after the 2011 season.  Caldwell was with the Colts from ’02 to ’11, including as the team’s head coach in his final three years. After Dennis Pitta dislocated his hip in the summer of 2013, Caldwell — by then the Ravens offensive coordinator — decided to bring in Clark.  With Ed Dickson dealing with a hamstring injury, Clark made an immediate impact in week 1 with 7 receptions for 87 yards against the Broncos. Clark wound up finishing with the most receiving yards of any Ravens tight end last year, but still totaled just 343 yards in 12 games. [click to continue…]

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Megatron at his best

Megatron at his best.

In his seven-year career, Calvin Johnson has already recorded 9,328 receiving yards. And for those curious about these sorts of things, he’s the career leader in receiving yards per game at 88.0, too. But Johnson has also benefited greatly from playing on teams that have thrown a weighted average of 635 pass attempts per season.

What is a weighted average of team pass attempts? I’m defining it as an average of pass attempts per season weighted by the number of receiving yards by that player. Why use that instead of a simple average? When thinking about whether a receiver played for a run-heavy or pass-happy team, we tend to think of that receiver during his peak years. If he caught 10 passes for 150 yards as a rookie on a very pass-happy team, that should not be given the same weight as the number of pass attempts his team produced in his best season. For example, here is how I derived the 635 attempt number for Megatron.

Twenty-one percent of his career receiving yards came in 2012, when Detroit passed 740 times (excluding sacks). Therefore, 21% of his team pass attempts average comes from that season, while 18% comes from his 2011 season, 16% from his 2013 season, and so on. In the table below, the far right column shows how we get to that 635 figure: by multiplying in each season the percentage of career receiving yards recorded by him in that season by Detroit’s Team Pass Attempts.

YrRecYdTPAPercTM * %
2013149263416%101.4
2012196474021.1%155.8
2011168166618%120
2010112063312%76
200998458510.5%61.7
2008133150914.3%72.6
20077565878.1%47.6
Total93284354100%635.2

There are 121 players with 7,000 career receiving yards. Unsurprisingly, Johnson has the highest weighted average number of team pass attempts, which must be recognized when fawning over his great raw totals. Marques Colston is just a hair behind Johnson, but no other player has an average of 600+ team pass attempts.

The table below contains data for all 121 players (by default, the table displays only the top 25, but you can change that). Here’s how to read it, starting with the GOAT: Jerry Rice ranks first in career receiving yards, and he played from 1985 to 2004. Rice played in 303 games, gained 22,895 receiving yards, and his teams threw a weighted average of 547 passes per season. Among these 121 players, that rank Rice as playing for the 25th highest or most pass-happy team. Rice also averaged 76 receiving yards per game, which ranks 5th among this group. [click to continue…]

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Is Matt Schaub washed up? Is he the next Jake Delhomme? For the first six seasons of his Texans career, Schaub was an above-average quarterback in both Net Yards per Attempt and Adjusted Net Yards per Attempt. But last year was disastrous in a way that his poor conventional stats fail to completely capture (for example, Schaub threws picks six in four straight games).

But does that mean hope is lost? Schaub turns 33 in June, which means more than you might think. Sure, Peyton Manning and Tom Brady can defy the odds, but 33 is still six years to the right side of the peak age for passers. Perhaps even more damning, Schaub’s steep decline in 2013 was his second in two years; he averaged 7.8 ANY/A in 2011, 6.5 in 2012, and then 4.5 last year; his NY/A averages (7.7, 6.6, 5.7) have followed a similar pattern. The graph below shows Schaub’s Relative NY/A and Relative ANY/A — i.e., his averages compared to league average — for each year of his Texans career:

[click to continue…]

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What Does Chris Johnson Have Left?

CJ1K?

CJ1K?

After six seasons in Tennessee, Chris Johnson is now a free agent. The star running back has had an up-and-down career. The successes are easy to document: since 2008, only Adrian Peterson has more rushing yards, and Johnson has rushed for 1,299 more yards than the next closest back, Matt Forte. Johnson was just 32 yards shy of 10,000 yards from scrimmage with the Titans, the second most in the league over that period behind only Peterson. There was a magical 2009 season, where Johnson rushed for 2,000 yards, averaged 5.6 yards per carry, and set the still-standing record for yards from scrimmage in a season with 2,509.1

But there’s also the bad. In the four seasons since his Hall of Fame-caliber performance, Johnson has had 24 games with five or more carries where he averaged three or fewer yards per rush, the most such games in the league. In the last three seasons, Johnson has recorded 10+ carries and averaged 3.0 YPC or worse in 17 of his 48 games, also the most in the NFL. The man known as CJ2K became famous for his big play ability but has recorded a below-average YPC rate in two of the past three seasons.  And while he’s never been a success rate star, he’s still checking in at below-average in percentage of successful runs in recent times, so it’s not as though the lower YPC average is a reflection of a style change to become a more consistent back. Last year, Johnson ranked 53rd in Advanced NFL Stats’ measure of success rate out of 84 eligible backs.

Johnson’s a pretty complicated back to analyze. He’s boom or bust, but he’s also displayed excellent durability over his career and is a consistent yardage machine. But he now rarely make big plays and is at an age where nothing is assured. In 2009, Johnson had 22 carries of 20+ yards; last year, he had only five such runs. So I decided a fun way to project Johnson’s 2014 season would be to run him through a similarity program based on nine factors. [click to continue…]

  1. Less relevant but one of my favorite Johnson moments came in the 2007 Hawaii Bowl against a Boise State team that would go 38-2 over the following three seasons. In that game, East Carolina won 41-38 as Johnson rushed for 223 yards and scored two touchdowns on 28 carries. That’s the second most rushing yards allowed by Boise State to any player since 2000. []
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Head Coach Retention Rates

In the footnotes (always read the footnotes!) to one of Neil’s posts at 538, he included a fun chart displaying the likelihood that a baseball manager would be retained by his team X seasons from now. That made me wonder: what is the NFL head coach retention rate? And, as is often assumed by the football commentariat, are coaching seats hotter than ever in this “win now” era?

Just nine teams will have the same coach in 2014 as they did entering the 2009 season. Those nine men are Mike Smith, Marvin Lewis, Mike McCarthy, Sean Payton, Bill Belichick, Tom Coughlin, Rex Ryan, Mike Tomlin, and John Harbaugh.  A 28% five-year retention rate sounds pretty low, but is it? Does a 28% rate back up the claim that trigger fingers are itchier than ever, and owners are impatient and irrational Donald Trumps?

No. Let’s flash back to the start of the 1993 season. Don Shula was in Miami, of course, while Marv Levy had just taken the Bills to three straight Super Bowls. Levy had been the head coach in Buffalo since the middle of the 1986 season, which is the same year Jim Mora began as head coach in New Orleans. Mora was still with the Saints in ’93, and… well, that was it. Those three coaches were the only ones who had been with their teams for five straight years.

The same fact was true six years later: at the start of the 1999 season, only Dennis Green (Minnesota), Bill Cowher (Pittsburgh), and … Norv Turner (?!?) had been with their teams for five years. The graph below shows the percentage of head coaches who were still with the same team five years later for the period 1970 to 2009:

[click to continue…]

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A Passing League

In some ways, the premise of this post is geeky even for this site. And that’s saying something. There is a debate over the proper way to measure league average. For example, when we say the average completion percentage in the NFL is 61.2%, this is generally assumed to reflect the fact that in 2013, there were 18,136 passes thrown in the NFL, and 11,102 of them were completed.

An alternative method of measuring completion percentage in the NFL is take the average completion percentage of each of the 32 teams. That number won’t be very different, but it won’t be identical, either. The difference, of course, is that this method places the same weight on each team’s passing attack when determining the league average. The former, more common method, means that the Cleveland Browns make up 3.755% of all NFL pass attempts and the San Francisco 49ers are responsible for only 2.299% of the league-average passing numbers. The latter method puts all teams at 3.125% of NFL average.

Wow, Chase, is this really a football blog? Two paragraphs on calculating the average in a data set? Believe it or not, that background presents an interesting way to look at how the NFL has become more of a passing league.

For example, let’s look at the 1972 season. Miami led the NFL in points scored and in rushing attempts, while ranking 24th out of 26 teams in pass attempts. Does this mean the Dolphins weren’t a good passing team? Of course not; in fact, Miami had the highest Adjusted Net Yards per Attempt average of any team that season! That year,only two teams threw over 400 passes: New England and New Orleans. And both teams were below-average in ANY/A, with the Patriots ranking in the bottom three.

In 1972, the average pass in the NFL gained 4.28 Adjusted Net Yards.  But an average of each team’s ANY/A average was 4.34, because good passing teams like Miami and Washington passed less frequently than bad passing teams like New England and New Orleans.  The league-wide average was only 98.5% of the “average of the averages” average; whenever that number is less than 100%, we can conclude that the better passing teams are passing less frequently.

Fast forward 39 years. In 2011, three teams topped the 600-attempt mark: Detroit, New Orleans, and New England. Tom Brady’s Patriots and Drew Brees’ Saints ranked in the top three in ANY/A (and the Lions in the top 7), while Aaron Rodgers’ top-ranked Packers in ANY/A still finished above average in pass attempts. The Tim Tebow Broncos were last in pass attempts, and in the bottom ten in ANY/A. The Jaguars, who finished last in ANY/A by a large margin, were in the bottom five in pass attempts, too, as Maurice Jones-Drew led the league in rushing. In 2011, the league-wide average ANY/A was 5.90, while the “average of the 32 teams” ANY/A was 5.85; that’s because the best passing teams were throwing more frequently than the worst passing teams (the ratio here was 100.8%). [click to continue…]

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Interactive Trivia: Jerry Rice And [_______]

One of only two players to ...

One of only two players to ...

If you play with enough filters of the “my dad can beat up your sister” variety, you can get some pretty counter-intuitive results. For example, Jerry Rice and DeSean Jackson are the only two players in NFL history to catch 350 passes, gain 6,000 receiving yards, and average 17.1 yards per reception through their first six seasons. Here’s proof.

Here’s another one: Jerry Rice and Brett Favre are the only two players to ever catch a pass after turning 40 years old.

Like touchdowns? Rice and Cris Carter are the only two players to catch 35+ touchdowns from inside of five yards.

And one more: Jerry Rice and Doug Flutie are the only two players to ever score a touchdown after turning 42 years old.

But putting Rice in a group with Hall of Famer (or future Hall of Famer) isn’t very fun, and even Flutie and Jackson are good enough players that the trivia isn’t shocking. Hence today’s post: I want to see who can come up with the worst player to be in a bit of Rice trivia along these same lines. I will defer to mob rule to select a winning entry.

The rules:

1) The trivia must take this form: “Jerry Rice and [___] are the only two players…”

2) Everyone must be eligible, so no restrictions based on team. So it can’t be “Rice and Terrell Owens were the only two 49ers to… or “Rice and Deacon Jones are the only two players from Mississippi Valley State to….”. However, a “Rice and [__] are the only two players to [________] for two or more teams would be acceptable. Make sense? If not, hey, give it a shot and maybe the crowds will approve.

Fire away, and remember, the PFR play index is your friend. Multiple entries are not just permitted, but encouraged.

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Matt Waldman Rookie Scouting Portfolio

Every April 1st, friend-of-the-program Matt Waldman (@MattWaldman) releases his Rookie Scouting Portfolio. The RSP is, well, insane. It’s a 251-page draft guide that not only provides rankings and analysis of 164 players, but also provides over 1,000 pages of scouting checklists and play-by-play notes.

Matt does top-notch work year round, and I can confidently state that the Rookie Scouting Portfolio is the most comprehensive analysis of rookie draft prospects at the offensive skill positions I’ve ever seen. But it’s not just about rankings and his analysis; he makes the evaluation process as transparent as possible to the reader, by identifying:

  • Players that have boom-bust potential, players who may have already maxed out their potential, or players with great upside.
  • Breakdowns/rankings of players by individual skills at the position.
  • Player comparisons to past NFL players based on style and builds.
  • Overall rankings and comparisons in cheat sheet/table format with pertinent measurements and workout results.
  • Overall rankings with written explanations in paragraph form.
  • Overrated, underrated, and long-term projects.
  • Fantasy-friendly tiered cheat sheets.

Matt documents what he sees with play-by-play detail. Yes, that’s a lot of work. No, you don’t have to read that part of the book to get tremendous value from the RSP. And here’s something pretty neat: Matt ranks every player graded by position and then writes a post-draft analysis with rankings assembled in a tiered cheat sheet. This is free with the RSP purchase and available a week after the NFL Draft.

The RSP is $19.95 and available at www.mattwaldman.com. Matt donates 10 percent of every sale to Darkness to Light, a non-profit that combats sexual abuse through individual community and training to recognize how to prevent and address the issue. All told, the RSP contains nearly 1300 pages this year. If you’re the type who likes to read testimonials, well, Matt has lots of those. He’s also provided a few sample evaluations from prior years that you can review.

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Scoring Distribution Since 1940

We all know that scoring is on the rise. The 2013 season was the highest scoring season in NFL history, just narrowly edging out the … 1948, 1950, and 2012 seasons. Scoring soared in the aftermath of World War II, but quickly dropped off in the middle of the 1950s. Scoring fell to its nadir in 1977, prompting the 1978 rules changes regarding pass blocking and pass coverage. After another lull in the early nineties, scoring has steadily increased over the last twenty years. Take a look at the average points per game for professional teams (including the AAFC and AFL) since 1940:

nfl ppg [click to continue…]

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The Best Kickoff Returners in NFL History

Two weeks ago, I looked at the best punt returners in NFL history; today, a look at the top kickoff returners. Again, we begin with a graph of the league average yards per kickoff return from 1941 through 2013. The variation here has been relatively minor, falling in a 5-yard window from 18.9 yards per return to 23.7.

kickoffs [click to continue…]

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Ranking The Almost Dynasties

A couple of weeks ago, Andrew Healy contributed a guest post titled, “One Play Away.” He’s back at it today, and we thank him for another generous contribution. Andrew Healy is an economics professor at Loyola Marymount University. He is a big fan of the New England Patriots and Joe Benigno.


What teams do we remember the most? Going back to the merger, the 1970s Steelers, the 1980s 49ers, the 1990s Cowboys, and the 2000s Patriots seem to stand above the rest. Each of these teams earned that place in our collective memory by winning the most Super Bowls in the decade.

How different could it have been? In other words, were the dynasties that happened by far the most likely ones? Or were there others that were equally, or even more likely? Think of teams that have suffered unusually cruel sequences of defeats (cue nodding Vikings, Bills, and Browns fans). We all know that those teams could have won Super Bowls. But maybe the more interesting question is whether those teams realistically could have won multiple Super Bowls, or even have become the dominant team of the era.

Today, I estimate the chances that different teams had of becoming the Team of the Decade (the TOD) for the ’70s, ’80, ’90s, and ’00s. Some of the results are surprising. One of the teams that became the TOD was actually much less likely than another to dominate that decade. Only two of the four teams truly stand out as being clearly the single most-likely team to be the TOD.

Even more interesting are the teams that might have been dynasties instead of the ones we’ve come to know. In most cases, these teams won at least one Super Bowl. In one case, though, a team that became famous for losing easily could have been not just a one-time winner, but a team that became a dynasty and dominated the decade.

To come up with the estimates of a team’s chances of winning Super Bowl, I simulated the playoffs 50,000 times. I used the actual playoff brackets and then created win probabilities for each game based on team strength. In tables that follow below, I’ll describe the probabilities that teams won multiple titles in a decade. I’ll also pick a True Team of the Decade (most expected Super Bowl wins), a What-Might-Have-Been-Dynasty that Won Nothing, a Team that Wasn’t as Good as We Remember, and a A Bottom-Feeder Team(s) for each decade.

First, a brief description of how I performed the simulations before getting to the rankings:

  • The playoffs were run under the rules in a given year: All rules relating to seeding, home field, and number of teams were used. If there was a rule in place preventing matchups between divisional opponents in a given round, I also applied that rule. To some extent, the fewer teams in earlier years helped make dynasties more likely in those decades.
  • Pro Football Reference’s Simple Rating System was used to measure team strength: I used PFR’s for all years to be consistent. It’s worth noting that their ratings and DVOA usually match up closely. Another possibility is to try to simulate DVOA ratings, but it seems simpler to just use SRS throughout. In some cases, there are some differences, such as for the 1998 Broncos and 1999 Titans.
  • I used the beginning of the NFL season to define the decades: So 1970-79 means Super Bowls V-XIV. An interesting thought experiment is to consider Super Bowl time instead of calendar decades. Then the Raiders would have been the team of Super Bowls XI-XX. Anyway, I’ll stick with the convention. It’s worth noting that my results suggest the Raiders were not as good as we might remember.

1970s

The table below shows each franchise’s probability of having won 0, 1, 2, 3, 4, 5, or 6 Super Bowls during the decade according to the methodology described above. The final column shows the expected number of Super Bowl wins for the decade.

Team0123456E(Wins)
PIT0.1450.330.3120.1560.0490.0080.0011.659
DAL0.2090.3770.2750.1110.0240.00401.377
MIN0.2360.4070.2610.0810.0130.00101.232
MIA0.3430.4220.1910.0390.004000.941
RAM0.390.3990.1690.0370.005000.87
OAK0.3950.4020.1650.0340.005000.853
BAL0.5610.3550.0760.0080000.532
WAS0.6010.3330.0610.0050000.469
SD0.6410.359000000.359
DEN0.6540.320.0250.0010000.373
SF0.7430.2350.0220.0010000.281
DET0.7620.238000000.238
NE0.8320.1610.00700000.175
CIN0.8820.1140.00400000.123
KC0.8920.108000000.108
STL0.90.0970.00300000.103
GB0.9050.095000000.095
PHI0.9240.0750.00100000.077
CLE0.9650.035000000.035
HOU0.9720.028000000.028
TB0.9740.026000000.026
BUF0.9750.025000000.025
CHI0.9820.018000000.018
ATL0.9980.002000000.002
NYG10000000
NYJ10000000
SEA10000000

The True Team of the Decade: Pittsburgh Steelers
The Steelers had only a 14.5% chance of winning no Super Bowls in the ’70s and a 4.9% chance of winning the four that they did. The expected value of SB wins for Pittsburgh was 1.67, the highest value for any team in any decade.

The What-Might-Have-Been-Dynasty that Won Nothing: Minnesota Vikings
The Vikings are not too far away from the Steelers and Cowboys. There was only a 23.6% chance the Vikings would have won nothing in the ’70s. And they certainly could have won multiple championships. There was over a 35% chance the Vikings would have won at least two titles and a 9.6% chance they would have won at least three. Of all the teams that won nothing, the 1970s Vikings are the best candidate for the team that could have been the TOD.

The What-Might-Have-Been Dynasty that Won Nothing, Part 2: Los Angeles Rams

A little bit behind the Vikings are the Rams. Los Angeles had only a 39% chance of winning no Super Bowls in the ’70s and a 20.3% chance of winning multiple titles.

The Team that Wasn’t as Good as We Remember: Oakland Raiders
When I starting working with the data, I expected the Raiders to challenge for the TOD. Five losses in the AFC championship to go with the one title. Seven playoff appearances. Despite all that, the Raiders only had the sixth-most expected titles in the decade. In fact, they didn’t really underperform at all in terms of titles. They had a 39.5% chance of winning none at all. The Raiders’ SRS ratings explain this. Oakland was never really great, only passing +10.0 in a year (1977) where they finished second in the division.

Bottom-Feeder Teams: New York Giants, New York Jets
Only two teams played the entire decade and missed the playoffs every single year. They happened to be the two teams that played in New York. The chance that two teams would miss the playoffs every year and New York would happen to miss playoff football entirely: about 0.2%.

1980s

Team0123456E(Wins)
SF0.1460.3370.310.1560.0420.0070.0011.637
CHI0.2890.4810.1980.030.002000.975
MIA0.4160.3970.1540.0290.003000.805
WAS0.3920.450.1410.0170.001000.785
DEN0.4730.4020.1120.0120000.664
CLE0.5370.3710.0830.0090000.565
PHI0.5850.3550.0560.0030000.478
DAL0.6010.3290.0650.0050000.475
CIN0.6080.340.0510.0010000.446
NYG0.6250.3320.0420.0010000.419
OAK/LA0.6430.3020.050.0050000.417
SD0.70.2710.0280.0010000.329
BUF0.7070.2620.030.0010000.324
MIN0.7560.2250.0180.0010000.263
NYJ0.7720.210.01800000.247
ATL0.7840.2160.00100000.217
RAM0.8370.1520.0100000.174
NE0.8690.1290.00200000.134
NO0.8720.128000000.128
SEA0.9010.0970.00300000.102
GB0.9020.098000000.098
PIT0.9090.0880.00300000.094
TB0.930.07000000.071
HOU0.940.0590.00200000.062
BAL/IND0.9570.043000000.043
DET0.9720.027000000.028
KC0.9830.017000000.017
STL/PHX0.9970.003000000.003

The True Team of the Decade: San Francisco 49ers
Unlike the 1970s, the ’80s weren’t close. The Niners were similar to the ’70s Steelers with an expectation of 1.64 Super Bowl wins in the decade. The ’80s 49ers had about a 4.2% chance of winning the four Super Bowls they did and 51.7% chance of winning at least two. And, while not shown in the table above, it’s exciting to note that the Niners had a 0.004% chance of winning seven Super Bowls in the 1980s.

The What-Might-Have-Been-Dynasty that Won Nothing: Miami Dolphins
I was really surprised by this one. The Dolphins come in third in the 1980s in expected SB wins with 0.81. Based on their consistency in the first half of the decade, the Dolphins had an 18.6% chance of winning multiple Super Bowls in the 1980s. That’s substantially higher than the 12.4% chance for their nearest competitor: the much better-remembered Denver Broncos who were annihilated in three Super Bowls.

The Team that Wasn’t as Good as We Remember: Oakland/LA Raiders
Despite never being close to dominant, the Raiders won two Super Bowls in the 1980s. According to the number of SB wins we would have expected them to have, the Raiders actually rank 11th, behind six teams that won none in the decade. They had about a 5.5% chance of winning multiple titles in the decade.

A Bottom-Feeder Team: Houston Oilers
For teams that played every season since the merger, the Oilers had the least hope of winning a title over the 1970s and 1980s combined. That’s a little surprising given that they had at least one memorable moment in the playoffs during that stretch, unlike some of the teams ahead of them.

1990s

Team0123456E(Wins)
SF0.1510.3310.3080.1560.0460.0070.0011.639
DAL0.3120.4160.2160.0510.005001.023
GB0.3630.4870.1380.0110000.799
WAS0.3950.5630.0410.0010000.647
BUF0.5190.3710.0960.0140.001000.607
KC0.5130.3830.0950.0090000.601
DEN0.5520.3510.0860.010000.557
MIN0.550.3990.0490.0020000.504
PIT0.5930.3280.0720.0070000.495
RAM/STL0.5780.422000000.422
HOU/TEN0.6580.3010.0390.0020000.386
NYG0.7640.2260.0100000.247
JAC0.8020.1920.00600000.204
MIA0.8130.1730.0130.0010000.202
NYJ0.8010.199000000.2
LA/OAK0.830.1670.00300000.173
NE0.8420.1510.00700000.166
ATL0.850.1490.00100000.151
SD0.8660.1290.00500000.139
IND0.8660.1330.00100000.135
NO0.8710.1250.00300000.132
DET0.8860.110.00400000.118
CAR0.8990.101000000.101
PHI0.9050.0920.00300000.097
TB0.9160.0830.00100000.086
CLE/BAL0.9190.081000000.081
CHI0.9560.043000000.044
SEA0.9590.041000000.041
CIN0.9930.007000000.007
PHX/ARI10000000

The True Team of the Decade: San Francisco 49ers
This one almost leaps off the page. Not only were the Niners on top in the 1990s in terms of expected SB wins, they were way on top. Given the Cowboys’ relatively short run, it’s not surprising that they would do worse here, but they’re closer to the 10th place Rams on this list than they are to the 49ers. Even though they only won one in the decade, the Niners had the same number (1.64) of expected titles in the ’90s as they did in the ’80s, and a 51.7% chance of multiple titles.

The What-Might-Have-Been-Dynasty that Won Nothing: Buffalo Bills
The Bills actually do worse on this list than I would have expected. They were about even money to win the zero titles that they did in the ’90s. They had an 11.0% chance of winning multiple titles, making them the top-ranked no-title team of the ’90s, but ranking them well behind the ’70s Vikings, the ’70s Rams, and the ’80s Dolphins.

The What-Might-Have-Been-Dynasty that Won Nothing, Part 2: Kansas City Chiefs
On the field, the ’90s Chiefs only went to one AFC Championship game and no Super Bowls. Nevertheless, they’re about even with the Bills in terms of the Super Bowls they could have won. They had a 10.4% chance of winning multiple titles in the ’90s.

The Team that Wasn’t as Good as We Remember: Pittsburgh Steelers
I’m not sure there’s a great candidate in this category, so I was tempted to just pick the Raiders again to keep the pattern. You could go with Broncos here, but the 1998 Broncos are one case where there’s a clear gap between SRS and DVOA, which gives them more credit. The ’90s Steelers had four playoff byes in a run of six straight playoff appearances. Still, they had a 59.3% chance of winning no Super Bowls and only a 7.9% chance of winning multiple titles.

A Bottom-Feeder Team: Phoenix/Arizona Cardinals
The worst team in two consecutive decades. Over twenty years, the Cardinals had 0.003 expected titles. That’s only 0.003 more expected titles than the Houston Texans and they weren’t even in the league yet.

2000s

Team0123456E(Wins)
NE0.170.4160.2990.0980.0160.00101.38
IND0.4150.4020.1480.0310.004000.807
PHI0.4280.3990.1430.0270.003000.78
PIT0.4630.3990.1220.0160000.693
OAK0.4690.4320.0970.0020000.633
STL0.4940.4320.0720.0020000.584
TEN0.5780.3470.070.0050000.501
SD0.5890.3470.060.0040000.48
BAL0.6220.3160.0570.0050000.445
CHI0.6390.3190.0410.0010000.404
NYG0.6470.3070.0440.0030000.403
NO0.6410.3260.0330.0010000.393
GB0.6990.260.0380.0030000.344
TB0.710.2650.0240.0010000.316
DEN0.7160.2680.0160.0010000.3
SEA0.740.250.0100000.27
DAL0.7870.1990.01400000.227
MIN0.7880.1970.01400000.226
KC0.8010.1980.00100000.199
CAR0.8560.140.00400000.149
NYJ0.8690.1240.00600000.138
ATL0.9140.0830.00300000.088
MIA0.920.0790.00100000.082
WAS0.9520.048000000.049
SF0.9630.037000000.038
JAC0.9710.029000000.029
CIN0.9750.025000000.025
CLE0.9910.009000000.009
ARI0.9910.009000000.009
BUF10000000
DET10000000
HOU10000000

The True Team of the Decade: New England Patriots
Less dominant than the other True TODs, the Patriots of the aughts still have a healthy gap over their closest rival, the Colts. There was only a 17% chance the Patriots would have gotten shut out in the ’00s. There was a 41.7% chance that the Pats would win multiple titles in the decade, more than double the chance of any other team.

The What-Might-Have-Been-Dynasty that Won Nothing: Philadelphia Eagles
The Eagles rank third in expected titles in the ’00s with 0.78, just a hair behind the Colts for second. They also look similar to the 1970s Rams and 1980s Dolphins in terms of multiple-title potential. They had about a 17.4% chance of winning multiple titles in the aughts.

The Team that Wasn’t as Good as We Remember: Tampa Bay Buccaneers
Hopefully, it’s not too hard to remember a decade that ended with President Obama in the White House, but the Bucs come in lower here than I might have guessed. They made the playoffs five times, but still are only 14th in expected SB wins. They actually had a 71% chance of winning no titles in the decade. Even in their best year, 2002, where they ranked #2 in SRS and #1 in DVOA, they were far from dominant and so had only about a 21% chance of winning the title.

Bottom-Feeder Teams: Buffalo Bills, Detroit Lions
Neither team made the playoffs in the decade, a more impressive accomplishment than the ’70s Giants and Jets in an era of expanded playoffs. Both cities also suffered through deindustrialization and so seemed to deserve better football as a compensating differential.

Closing Thoughts

I was excited to check this out because I wanted to compare teams like the ’90s Bills and the ’70s Rams. That comparison makes it pretty clear that the ’70s Vikings are hands-down the clearest What-Might-Have-Been-Dynasty that Won Nothing. This is all post-merger, so arguably the best Vikings team of that era (the ’69 edition) doesn’t even count in the calculation. If you count the 1969 Vikings, there was only about a 1-in-6 chance that those Vikings would end up with no Super Bowls.

Maybe the most remarkable regularity over the years is how the Cardinals have been so bad for so long. Even though Arizona came close in 2008, the Cardinals had only an 11.2% chance of winning any of the last 44 Super Bowls. In fact, they were lucky just to make the one Super Bowl that they did (in more ways than one).

Finally, a couple of thoughts about this decade. While we’re only four years in, this decade could wind up resembling the 1990s. The Patriots right now are playing the role of the ’90s Niners, while the Seahawks may be the best candidate to be the Cowboys. So far, the Patriots have been (perhaps surprisingly) dominant. There’s only about a 27% chance that New England would have no titles in the 2010s and there was even a 28.5% chance that the Patriots would have already won multiple titles; that likelihood is more than four times more as any other team. Despite having none on the field through four seasons, the ’10s Patriots are on pace through four years to have the most expected SB wins for any decade. They already have 1.07 expected wins, more than double their nearest competitor.

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