Air Yards 2011

Imagine that football were just invented and we had to figure out how to credit passers with all the yards they generate, and I said let's include all the yards that the receiver runs after the catch. I'd be laughed out of the room. But that's the convention we've been handed.

It's not that QBs shouldn't be credited at all, because if a pass isn't completed there can be no yards after catch at all. And the argument that a very accurate QB that can hit a receiver in stride or lead him to open space to create YAC can't be ignored. Scheme matters too. But it's evident that some QBs feast on the YAC-gaining abilities of their receivers much more than others, distorting their overall stats.

I came up with Air Yards a few years ago as a method to compare passers with their receiver's YAC removed. Air Yards is simply the complement of YAC. It's the yardage a pass travels through the air forward of the line of scrimmage. AY is a unique and interesting way to view QB performance, but it's not perfect. A QB would be penalized for completing a short screen that's caught a yard to two behind the line of scrimmage. But those plays are few and far between, and I don't lose any sleep worrying about them. We should also keep in mind that a QB's performance is never just his own. But AY might be an inch closer to isolating the individual QB's contribution than if we look at total passing yards alone.

Here are the leaders in AY for the 2011 regular season. The table is sorted by default according to Air Yards per Attempt (AirYPA), but you can re-sort the table by clicking on the column headers.

Sterling Moore and Split-Play WPA

Sterling Moore posted a stellar +0.47 +WPA in Sunday's AFC championship game. That's very good -- only Patrick Willis (+0.52) and teammate Dane Fletcher (+0.49) beat that mark for defenders on championship weekend. After all, Moore made arguably the defensive play of the weekend when he knocked what would have been the go-ahead touchdown pass out of Lee Evans's hands with mere seconds to go.

But most of Moore's +WPA actually comes from his contributions on the following play, the failed third down pass targeted for Dennis Pitta which set up the fateful fourth down on which Billy Cundiff kicked the Ravens out of the playoffs. The Ravens were still in excellent shape on that third down, and the failure to convert or score a touchdown took their win probability down from 83% to 43%, giving Moore a +0.40 WPA on the play. That leaves just +0.07 for his other successful play, the strip of Evans in the end zone.

That seems intuitively way too low, and that intuition is correct. Although technically the entire play from snap to throw to almost-catch to strip just cost the Ravens 7% of a win, if Evans holds on to the ball and Moore doesn't strip it, Baltimore's ticket to the Super Bowl is all but punched. But with the way the data is fed into our system, it's impossible to give out separate credit for different aspects of plays.

But let's say for a second it was possible. How would each aspect of that play have played out in the eyes of WPA?

On Opponent Strength and Team Strength Correlation

This post at Football Outsiders caught my eye today. The IgglesBlog noticed something odd with their team rankings. I’ve notice the same phenomenon in my own systems—that team ranking methods that adjust for opponent strength tend to produce rankings that correlate (inversely) with a team’s strength of schedule. In other words, top ranked teams appear to have weaker schedules and low ranked teams appear to have stronger schedules. The problem is, assuming that a ranking method properly adjusts for opponent strength, it ostensibly should produce no correlation between each team’s ranking and its opponents' average ranking. In fact, we might expect the opposite result because of the two “strength of schedule” games each season—Last year’s 1st place teams play other 1st place teams, and so on.

In 2011 FO’s “DVOA” method correlated with opponent strength at -0.66, which is considerable. Here at ANS, Generic Win Probability correlated with Average Opponent GWP at -0.60 this season. FO notes that in other years the correlation isn’t nearly as strong, but there is an apparent tendency for negative correlations for most seasons.

This phenomenon was first pointed out to me a couple years back by a reader, and I too thought it was either a) randomness, or b) a flaw with my methodology. But I soon realized this is exactly what we should expect given the NFL’s scheduling rules. It’s neither luck nor a flaw. In fact, it's a sign the method is doing something right.

Consider a fictional four-team football league. Presume we have a perfect team ranking system that can peer omnisciently into each team’s soul to know its True Winning Probability (TWP). The Sharks, Knights, River Dogs, and Jack Rabbits each have a TWP of 0.75, 0.60, 0.40, and 0.25. (Notice the TWPs average to 0.50, as they would have to.)

Should The Niners Have Kept The Punt?

Who would have thought that Ted Ginn Jr.'s absence might have made all the difference in the NFC championship game? Kyle Williams' two fumbles on punt returns kept the Giants in the game and all but won it for them in OT. During the course of this 22-punt game, Jim Harbaugh was forced with a few 4th-down decisions. Earlier this year, Brian wrote about Harbaugh's decision to keep the 3 points after David Akers made a 55-yard field goal and the Cowboys were called for a 15-yard penalty. In the third quarter, down 10-7, the Niners were faced with a similar conundrum, this time with a punt. On 4th-and-6 from midfield, Andy Lee hits a beautiful punt the to the Giants' 7-yard line. Justin Tuck is called for running into the kicker, but Harbaugh declines and takes the punt, pinning the Giants deep. But, was this the right decision?

After the punt, the 49ers win probability was 37% (and their expected points were +0.34, meaning they were actually expected to be the next team to score even though the Giants had the ball). So the question is as follows: does going for it on 4th-and-1 after the penalty increase the Niners' chance of winning? The estimated success rate on 4th-and-1 is 74%. If San Francisco succeeds, their win probability jumps to 47%; if they fail, it falls to 31%. So, if we let x be the chances of converting on 4th-and-1, we have the equation 0.31*(1 - x) + 0.47*x > 0.37. Thus, the 49ers should go for it if x > 37.5%. Since the estimated conversion rate is 74% (almost twice our break even point of 37.5%), this seems like a no-brainer: the correct decision would be to take the penalty and go for it.

Roundup 1/21/12

Using portfolio theory to analyze fantasy football strategies. I tinkered with portfolio theory a while back, but ultimately understood it's not appropriate for real football analysis. It is however, well-suited for fantasy analysis.

A commenter linked to this a couple weeks ago. Correlation != causation.

2011 Giants = 2010 Packers? I buy that.

A different kind of look at Flacco.

Is the new rookie wage scale the reason for the record number of underclassmen declaring for the draft?

This is a good analysis of when teams ahead should try to score rather than run out the clock. I agree and made the same observation at the time on the WP graph comments. Fans and analysts typically call for teams to 'run out the clock' far too early. The sport has changed over the years to where offenses only need 1 minute to drive the length of the field for a TD. The 2-minute drill is an antiquated term. Two minutes is an eternity. (See the NO-SF game: 4 TDs in the 4 final minutes.) Helmet-knock: FO.

And Then There Were Four

A lot of media attention naturally goes to the quarterbacks at this point in the season. Much of it this week has shone on Joe Flacco in particular. While it's true he didn't light up the scoreboard like the other three QBs did last week, he was the only one playing against one of the league's best defenses. The others faced the 17th, 22nd, and 29th ranked defenses in terms of overall efficiency. A lot of the debate on Flacco has revolved around the notion that he just wins. I hear a lot of people cite his overall win-loss record as a starter as well as mentioning he has a very good defense backing him up. On one hand he's been to the playoffs 4 out of his 4 seasons, but on the other he's not the reason the Ravens win.

Win Probability Added seems it was made to settle debates just like this. And WPA says that since his second season in the league, Flacco is one of the main reasons why the Ravens have been a winning team. In fact, over his entire career his WPA has averaged +0.10 per game.  And his last two seasons were +0.21 and +0.19 WPA, well above average. In other words, his performance would make a .500 team a .700 team, all other things being equal. But not everything is equal. In particular, quarterbacks naturally have positive WPA simply because passing is more lucrative than running, plus it's been getting easier over time.

Running in the Cold

A few posts ago, we looked at how temperature affected the passing game. This time, we’ll look at the running game. Often, analysts will discuss how winds and cold might affect passes, but unless the conditions are exceptionally snowy or muddy, rarely does anyone consider how cold weather affects running. And why would they? I’d agree there isn’t much reason to suspect that cold temperature alone would cause runs to be any longer or shorter than in moderate weather.

Before we look at the numbers, I should note that running and passing are connected in game theory terms. The better a team’s passing attack, the more an opposing defense needs to respect it, possibly allowing bigger running gains. And same goes for a great running attack. The better it is, the more the defense needs to be on guard near the line of scrimmage, lowering its guard against the pass.

Cold temperatures, or at least the kinds of conditions that go along with cold temperatures, appear to reduce the effectiveness of passing. With that in mind, defenses might be worried slightly less about deep passes and stack the box in cold temperatures. Thus, we might expect that cold temperatures could indirectly reduce the effectiveness of running.

This is where it gets really interesting, because that’s not what happens at all.

Conference Championship Game Probabilities

Weekly game probabilities are available now at the Fifth Down. This week, I discuss some considerations about how the four teams are perceived, including factors like recency bias and the randomness of turnovers.

Postseason Projections: Conference Round

We'd previously warned that the eventual winner of the NFC East was not to be underestimated in the postseason, and the Giants showed why in last Sunday's win over the Packers. By a slim margin, the model now sees the Giants as the strongest of the four remaining teams, though their advantage is lessened by the fact that they will have to meet the 49ers on the road. Overall, the model now gives New York about one chance in three to win the Super Bowl, odds on par with those of the Patriots.

None of the remaining teams is particularly dominant at this point and none is a complete long shot. San Francisco, with the lowest probability of a Super Bowl win, is still given a 15% chance. And now, submitted for your approval, the final postseason projections of the 2011 season, with the table below listing each team's percent probability—first of advancing to the Super Bowl and then of winning the whole thing. Enjoy.

Percent Probability to Advance
TeamSuper BowlSup Bowl Champion

Temperature and Field Goals

As a pilot, I'm familiar with the effects of weather on things hurtling through the air. Many people intuitively sense hot, humid air as thicker and heavier, but the opposite is true. Warm air, as we all learned in 5th grade, is less dense than cold air. And the water molecules that make air humid, for some reason I've long forgotten, actually spread all the other molecules out, creating even thinner air. Aviators are wary of the Four H's--hot, humid, high (elevation), and heavy--things that can drastically alter performance and make takeoffs and landings a challenge.

Planes, and jet planes in particular, love cold dry air. The dense air helps engines work efficiently, and it helps the wings produce lift, making for shorter takeoffs and slower landing speeds. Baseballs, on the other hand, love the Four H's. Fans of our national pastime are well aware of the fact that home run rates peak in the hottest months of the season, and that balls tend to fly out of the park in Colorado.

Field goal kicks are affected by the same factors as anything else flying through the air--wind, temperature, and even altitude. In this post, we'll take a look at how temperature affects field goal success.

Team Stat Visualizations Updated

The team stat visualizations are now updated through the division round. If you're looking for analysis of recent trends for the four remaining teams, this is all you need. Use the slider bar to filter out however many weeks you like from the early half of the season, and see how the teams compare on the grid.

  • Are the Giants really winning in the past several weeks thanks to their defense?
  • Which team is the only remaining in the playoffs with both an above average offense and defense?
  • Check out just how far off their games both the Saints and Packers fell this past weekend.
  • Have the Patriots really righted their defensive ship since mid-season?
  • Which team won this past weekend despite their 3rd worst offensive output of the season?
  • How do the four remaining teams compare in terms of passing and running EPA per play, on offense and on defense?

Alex Smith Sheds The Dilfer Name

Earlier this year, I introduced the Trent Dilfer Club - those quarterbacks for good teams who don't typically win games for their teams, but can often lose them. The Club members typically win by limiting their self-destruction and managing the game. This year, nobody followed this concept better than Alex Smith. Among QBs who played at least 9 games, Smith led the league with only 5 interceptions all year (and he played all 16 games!). He added a measly +0.01 WPA per game, but the 49ers entered the playoffs as the number two seed in the NFC with a 13-3 record.

Enter the divisional round. The 49ers are 3.5 point underdogs at home to the hottest team in football, the New Orleans Saints. The only possible way for the Niners to win would be a dominant defensive performance, right? Wrong. Alex Smith made throw after throw - mostly to his favorite target Vernon Davis - keeping the 49ers in one of the most exciting and high-scoring fourth quarters in playoff history. If I told you the Saints would score 32 points, no one would believe San Fran to come out on top. Check out Alex Smith's WPA and EPA/P throughout the course of the season:

Sunday's Division Round Analysis

Here are some quick reactions to Sunday's division round games, with at least one statistical morsel from each game.  Click the game header to see the graph and advanced box score.


The Texans outplayed the Ravens in almost every way except one--turnovers. Jacoby Jones' muffed punt was the costliest. With a 3-point lead in the 1st quarter, the HOU defense forced a 3-and-out. On the ensuing punt, Jones watched the ball bounce in front of him, but made a play for the ball to save field position. The Ravens recovered it at the HOU 6 and went on to score a TD. If you look at the WP graph, it was the signature play of the game, and HOU never fully recovered.

This game was supposed to feature two of the league's premier runners. Instead, it was all defense. Arian Foster had 132 yds on 27 carries (4.9 YPC), but netted -0.01 WPA and only 1.8 EPA. Why? Failures at critical plays. Foster was killed for a 7-yd loss by Ray Lewis on a flare pass forcing a 2nd and 17 when HOU only trailed by 4. On the next play, he was strung out of bounds for just a 1-yd gain, creating a 3rd and 16. On a 3rd and 1 at the BAL 21, Foster was stuffed for no gain. And so on.

Ray Rice did much worse. He was stuffed on several critical goal line plays. And on a 2nd and 1 to seal the win, he was stopped short of the marker. Rice finished with -0.15 WPA and -6.3 EPA. These lunatics at the Baltimore Sun who week-in and week-out clamor for more carries by Rice, who cite fallacious 'when Rice gets 25 carries the Ravens win' stats, need to get a clue. (I'm looking at you Mike Preston.) A long time ago I came to the conclusion that most sports desks at our major city papers don't have the first idea about the sport on which they claim to be so authoritative, but the Baltimore Sun is in a league of its own. Those guys seem like nice folks, but...they have a duty to educate themselves. It's their job. As it is, they're no better than the average fan with his harebrained opinions.

Saturday Division Round Analysis

Here are some quick reactions to Saturday's division round games, with at least one statistical morsel from each game. Click the game header to see the graph and advanced box score.

NO at SF

This was the most exciting of the weekend's games, with a 7.6 Excitement Index. SF had an incredible 1st quarter, taking a 17-0 lead. They clung to those 17 points like life depended on it until Akers hit a 3rd quarter FG to make the game 20-14. Things didn't look so good for SF with 4 min left in the game. Yes, they were up by 6 against NO. But, they were only up by 6 against NO. That's when the explosion occurred. All football hell broke loose. There was one touchdown per minute in the final 4 minutes of the game, 2 per team.

Vernon Davis will be immortalized with his amazing catch on the goal line for the win, but he racked up huge chunks of WPA well before that moment. His 47-yard catch to get the NO 20 was a 0.45 WPA play, and his 37-yarder on the prior TD drive was a 0.39 WPA play. If I'm game planning for the Giants this week, I'm going to take away Davis.

Live WP Graphs and Analysis

Keep up to speed with the live WP Graph for the NYG-GB game. Everyone's invited to join the commentary and analysis thread.

Roundup 1/14/12

When it comes to passing, there's the Packers, Saints, and Patriots, and then there's everyone else.

Tebow is no good, except when he's great.

PFR's AV for 2011 is up.

The future of prediction.

From the Community Site: Bayesian Coach Rankings by David Durschlag. Also, Jim Glass keeps it simple.

Michael Beuoy has also updated his 'futures' market rankings, which I think is very clever. Michael has also recently launched his own site. Check it out.

The NFL continues to be competitively balanced.

The effect of the kickoff rule change.

Weather Effects on Passing

My last post looked at the effect of temperature on home field advantage. We saw that cold weather put dome and warm climate teams at a disadvantage. The post was titled How Does Temperature Affect Road Teams?, but I really didn't answer that question. I measured the size of the effect, but I didn't solve the riddle of actually how temperature makes a difference. This post will begin to look at just how weather makes a difference, starting with the passing game.

Here's how passing fares for home and visiting teams by temperature. The chart below shows  Adjusted net Yards Per Attempt (AYPA), which accounts for sacks and interceptions, according to temperature. Keep in mind there are smaller sample sizes at the extremes.

Division Round Game Probabilities

Weekly game probabilities are available now at the Fifth Down. Again, this week I share some statistical tidbits on all four of the match-ups.

How Does Temperature Affect Road Teams? (And Dome Teams in Particular?)

A few years ago I looked at how well teams from various climates types played when visiting other climate types. The most remarkable result was that dome teams win only about 20% of the time when playing in the cold. But that study was limited in several ways. Instead of actual temperature data, I used December in a cold-weather city as a proxy for cold temperature. I also was limited to regular season games from 2002 through 2006.

With new and better data, I redid the study. This time I have actual temperatures and used all non-preseason games from 2000 through the wildcard round of the 2011 season (last Sunday). Here are the results. The graph below depicts the winning percentage of the road team by temperature at kickoff. Road teams are classified according to their home climate--dome, cold, moderate, or warm.

Podcast at Fangraphs

I recently did another podcast with Carson at Fangraphs. We talked some armchair psychology and looked ahead at this weekend's division round games.

Postseason Projections: Divisional Round

The results of the ever-so-wild Wild Card Weekend shifted the postseason probabilities around somewhat. Without lifting a finger, New England's probability of a Super Bowl appearance increased from 32 to 47%, while Green Bay's probability declined slightly, from 40 to 36%. The model still considers both #1 seeds to be the most likely teams to emerge from their respective conferences.

The Texans and the Tebows
Now that the Steelers are out, the Houston Texans, led by the inimitable TJ Yates, are the highest-ranked team remaining in the playoff field. The difficulty of their path to the Super Bowl—Baltimore and then (most likely) New England, both on the road—makes them only the fourth most likely team to come away with a Super Bowl win, however. Meanwhile, the game probability model stubbornly refuses to accept the fact that All Tebow Does Is Win, giving Denver Super Bowl odds of slightly worse than two hundred to one.

How Much Does A Win Cost?

How many wins does a million dollars of quarterback salary buy? How many points does a million bucks buy? How much should you pay a QB assuming a certain level of expected performance?

I looked at salary data from 2000 through 2009 courtesy of USA Today and compared it with stats like Win Probability Added (WPA) and Expected Points Added (EPA). For those not familiar, WPA measures the impact a player has on his team's fortunes in terms of wins. EPA measure his impact in terms of net point differential. I looked at other stats too, but EPA and WPA fit very nicely with salary, at least for QBs.

Specifically, I wanted to discover what teams are willing to pay in exchange for expected levels of performance. To find out, I plotted the salary cap values of QBs against their performance. First, I made an adjustment for year. Between 2000 and 2009, QB salaries have steadily increased. By 2009, they were about double what they were to start the decade. This fits nicely with overall team cap numbers, which approximately doubled between 2000 and 2009.

QB performance has inflated too, but I haven't yet added a correction. QB performance has increased a total of about 10% since 2000, which pales in comparison to salary. In the future I'll add a correction and it might sweeten up the results a bit.

NFL contracts are notoriously complex, with signing bonuses, guarantees for both performance and injury, roster bonuses, and performance incentives. But none of that matters to me. I just want to know how much of a team's payroll under the cap--its most precious resource--is it willing to spend. How much are they spending, and how much are they getting back? For now, I'm looking at all big-money players, whether they're draft picks or free agents.

Here is how the relationship between salary and performance shakes out. The top graph plots EPA vs. cap hit, and the second graph plots WPA vs. cap hit broken out by season. The plot filters out QBs that earned less than approximately $2M in adjusted salary.

Texans Shut Down Dalton By Shutting Down Green

The Cincinnati Bengals were supposed to be one of football's worst teams in 2011, but nobody told Andy Dalton and A.J. Green. Thanks to a surprisingly competent Bengals passing game -- Cincinnati's 6.0 adjusted yards per attempt ranked 16th in the league -- the Bengals' offense was just good enough to power them to a 9-7 record and a playoff berth.

Green, in particular, was the big play threat and clearly the best player on the offensive side of the ball in Cincinnati. The fourth overall draft pick finished 6th in total WR WPA and 9th in total WR EPA. He was Cincinnati's passing offense, earning substantially more EPA (55.4) and WPA (1.98) than Dalton (27.5 and -0.23 respectively). That is, when Dalton wasn't throwing to Green he was a mediocre quarterback at best. When the ball headed towards number 18, the Bengals offense clicked like a finely tuned machine.

Saturday against Houston, the Bengals offense was completely stifled. For the first time, a team was able to completely neutralize A.J. Green, and the Bengals were left completely stunned.

Deadspin/Slate Roundtable: Fourth Downs Galore

Here's a contribution I had to the weekend's recent discussion at Slate and Deadspin. I looked at some how a few critical 4th downs made the difference in two of the wildcard games and consider some of the factors that are causing the game to evolve.
There are many doubters when it comes to four-down football. If you’re in that camp, indulge me in a quick thought experiment. Let’s imagine a football world where the punt and field goal had never been invented. (Sorry, Ray Guy and Jan Stenerud.) In this universe, there would be no second-guessing: Teams would go for it on every fourth down.

Then one day, some smart guy invents the punt and approaches a head coach with his new idea. “Hey coach,” he’d say, “instead of trying for a first down every time, let’s voluntarily give the ball to the other team.” Our coach would be incredulous at this suggestion. “You want me to give up 25 percent of our precious downs for just 35 yards of field position? Do you have any idea how difficult it would be for us to score?” And the coach would be right.
Catch it here at Deadspin or here at Slate.

Punting "Mainly Blows"

...that is, according to a recent in-depth analysis.

"I've found that, throughout the course of a football game, having the ball is really important and good," said Patriots head coach Bill Belichick, widely regarded as the league's greatest football mind. "Given that the idea behind punting is to willingly and knowingly give the ball away, one would not expect it to be a very popular thing to do. Understood?"
The funny thing is, this Onion article perfectly captures the state of punting in the NFL. Offenses have become good enough to tip the balance further and further toward going for it. Having the ball is good. Not having it is bad. It even discusses the fact that the kickoff following a score has to be factored into the equation.
"You have to give the ball away after you score by kicking it off, and no one likes that, but that's different from punting," Steelers head coach Mike Tomlin said. "For one thing, you're in a good mood because you just scored. And you can't score more than one touchdown each time you have the ball—that's the rule. So you have to kick the ball away, but it's sort of okay, since you can't really do anything else."
Helmet-knock to Eddy Elfenbein for the link.

More Falcons' 4th-Down Decisions

Earlier this year, the Falcons were criticized for going for it on 4th down and failing to convert against the Saints in OT.  Mike Smith was crucified for his "incorrect" decision.  But, as Brian wrote, his decision was correct.  A decision cannot be evaluated based on the outcome, but rather the theoretical expectation of the choice itself.  This week against the Giants, Mike Smith was faced with several 4th-down decision throughout the course of the game.  The first came at the end of a 14-play, 66-yard drive at the start of the 2nd quarter.  Using our Markov model, we can look at how the drive developed:

WP: Redskins' Off-Season Needs

This week's post at the Washington Post's Redskins Insider site takes a look at the Redskins needs based on a position-by-position analysis of player EPA.

2011 Regular Season Play-by-Play Data

Now uploaded. Find it here. Happy cruching.

Wildcard Game Probabilities

Weekly game probabilities are available now at the Fifth Down. This week I share some statistical tidbits on all four of the match-ups.

Special Playoff Viz

I added a team EPA visualization that's limited to the current playoff teams that might shed some light on where teams stand on offense and defense. What I find particularly useful is the week filter slider, which shows how teams have performed over recent games. You can find it on the tab titled '2011 P.O.'

A few things that struck me:

Postseason Projections: Wild Card Round

And then there were twelve. After 17 weeks and 256 games, the field has been winnowed and the playoff bracket is set. For the postseason, we can skip the simulations and calculate each team's chances directly from the win probability model.

Most Likely Super Bowl: Patriots vs. Packers
This shouldn't be much of a surprise. The trifecta of a highly-ranked team, a bye week, and home-field advantage is not easy to overcome, and the model projects the two #1 seeds as the most likely teams to emerge from their respective conferences. That said, there is an 87% probability that at least one of these two will not make it to Super Bowl XLVI.

Longest of Long Shots: Denver Broncos
It seems even three consecutive losses is not enough to put a damper on Tebow-mania. Denver's odds of winning the Super Bowl are variously listed as anywhere from 50/1 to 120/1, but, regardless, the Broncos are still over-valued, with the model estimating their true probability of a Super Bowl win to be less than one in eight hundred.

End of Season Team Rankings

Google search: "Andy Reid sad"
With the final games in the books, we can finally get around to seeing where teams ended up in the rankings when all was said and done.

Best Team to Miss the Playoffs: Eagles
The Philadelphia Eagles were pretty close to being a dream team, at least according to these rankings, but they were unable to work their way into the postseason. At least the Eagles made it to .500, and coach Andy Reid will get another year at the helm to prove this was all a bad dream.

Welcome Back, Drone.

Hi there, fellow office drone. I know from the web traffic numbers that about 95% of you read ANS at work. So with most of us taking time off the past several days, you may have missed the year-end posts. If you can pull yourself away from the new QB career visualizations for a few minutes, check out:

QB Career Comparison Visualizations

I'm excited to introduce two new features of the stat visualizations, and I think you'll find them very clever, fun, and useful. They are by far my favorites.

The first new graph, titled "Nth Best", plots each selected QB's career in order of his best through worst seasons. As opposed to a straight chronological plot by year, this presentation provides a very continuous and smooth curve, and it allows an easy comparison of the total career performance of each QB. A chronological plot produces a much more erratic and confusing display of peaks and valleys, making comparisons difficult.

The horizontal axis represents the Nth best season of each selected QB. The vertical axis represents the total EPA for each season. As you view from left to right, the graph will always appear to decline, but don't interpret this to mean the QB's performance is trending downward. It's just that the seasons are sorted from best to worst. Also keep in mind that graph plots total season EPA and not EPA per game or per play, so some of the worst seasons of a QB will be those marred by injury or prior to when he became a starter.

Sunday's Numbers Have Been Crunched

Want to arm yourself with the best numbers for the MVP debate at the water cooler? Sunday's numbers are now available, advanced stat box scores, top players of the week, team stats, and season leader boards.

Jets Lose on Dolphins' Epic Drive

The Dolphins, with nothing to play for but respect, eliminated their division rival Jets from playoff contention on Sunday.  Miami was down 10-6 with 7:56 left in the 3rd when they went on an epic 94-yard, 21-play, 12+ minute go-ahead drive.  Yes, a 21-play drive, tiring out Rex Ryan's prized defense.  Highlighted by six 3rd down conversions, there was a 73% chance of the drive ending in a punt and only 6% chance of a TD on 3rd-and-9 from their own 7-yardline (Play 3).  Using our Markov model, we can see the progression of the drive - and the progression of the Jets' demise.

Best of Advanced NFL Stats 2011

This is my favorite post of the year. I get to look back at the work I've done and say, 'Wow. I can't believe how much time I wasted doing that.' This year is different, though--it's 'how much time we wasted doing that,' thanks to all the great work done by the new writers: Keith, Carson, Jack, Zach, Josh, and Marc, and sometimes John. A big thank you goes to all the contributors this season.

Also, a big thank you goes to the readers and commenters, who make this a fun and lively site. A special thank you also goes to Ed Anthony, who edits the Community Site. We had some very good contributions this season. Keep 'em coming.

It was another big year for ANS. It has become even more of a full-featured site. It started with the blog, and then came the win probability graphs. Last year, we added advanced stat pages for teams and players. Now this year, we've added two major features: the advanced stat box scores and some really interesting visualizations.

Like I did for 2009 and 2010, I'll highlight some of the best posts and features of the year. Keep in mind this list is only a small fraction of the 276 posts of 2011. We'll start last January and go in chronological order.

Billy Cundiff was a kickoff machine last season, and all those touchbacks had the equivalent effect of 20 sacks.

I contributed an article to Slate about how the new OT format changed the equation when it comes to onside kicks.

Foreshadowing the visualization feature, I plotted team Success Rates and used it to develop a strategy for defeating mighty NE. Here's more on plotting SR. Note that running and passing correlate positively on either side of the ball, but team offense and team defense correlate negatively.

Carson somehow managed to merge literary criticism with football analysis. And it worked.

ESPN The Magazine featured ANS prominently in a great article on win probability--the 'killer stat'.