Regression Red Flags

The season is just one week away, and I haven’t been able to do anywhere near as much as I’d like to regarding a season preview.  However, I’ll try to remedy that this week, starting with a lightning-round style rundown of potential areas for regression.  Before I get there though, take a minute to download your copy of the 2014 Eagles Almanac here.  Just $10 for a PDF, and you’ll find a lot of great articles to get you ready for the season.

Now, the important things.

Before last season I spent a lot of time explaining why the Eagles would likely rebound strongly from the 4-12 season.  I projected the team to win 9 games and challenge for the division title when most pundits had them relegated to 5-6 wins.  What did I know that they didn’t?  Regression factors.

It won’t be news to any readers here, but there is a large degree of luck involved in nearly every aspect of the game of football.  A few specific areas, in fact, have a significant impact on the game and are almost entirely random.  That means we can get a lot of information about this year’s expected performance by looking at last year’s statistics and combing for outliers.  For example, the 2012 Eagles recovered just 35% of all fumbles.  Fumble recovery is almost all luck, and we’d expect a team to recover close to 50%.  That means, holding all other factors equal, the Eagles were likely to improve last year because they were very likely to recover a greater percentage of fumbles.  For the 2013 season, the Eagles actually recovered 43.75% of all fumbles.  That’s still less than we’d expect, but it’s a sizable improvement from 2012.

Now that I’ve explained it, let’s take a look at a handful of specific areas for which we’d expect mean-regression.

Pythagorean Expectation

This isn’t really a “mean-regression” candidate, but it’s vital to point out.  Last season the Eagles scored 442 points and allowed 382 points.  That performance would lead us to expect a Win/Loss record of 9.4-6.6 (from Pro-football-reference.com).  The upshot is that the Eagles record was slightly better than they “deserved”.  A difference of .6 wins isn’t big, but the direction is important.  The Eagles weren’t quite as good as their record from last year suggests.

Fumbles and Fumble Recovery Rates

I covered this a bit in the example above, but this is pretty low-hanging fruit as far as statistics with the potential for mean-regression.  Last season, the Eagles recovered roughly 44% of all fumbles.  They fumbled the ball 1.1 times per game.  Both of those numbers are good news for Eagles fans.  1.1 fumbles per game is close to average, and a 44% recovery rate suggests the Eagles are more likely to be better this year than worse.

However, there is one potential flag.  Opponents fumbled the ball 1.7 times per game when playing the Eagles.  That placed them tied for 1st in the league (with 4 other teams). Now, if you remember this post from last year, you’ll know that there is no significant persistence in forced fumbles from year to year.  Here is the chart:

Therefore, we can’t say that the Eagles were “good” at forcing fumbles last year and will be again this year.   Instead, we can expect that other teams will NOT fumble the ball as often as they did last year.  That’s bad.

However, 1.7 fumbles per game is not an outrageous amount.  So while there will probably be some regression, it won’t be huge and it might also be balanced out with positive regression in the overall recovery rate.

Fumbles verdict:  Neutral

Injuries

I covered this a couple of weeks ago, but it’s important enough to repeat.  According to Football Outsiders, the Eagles were 2nd in the league last year in Adjusted Games Lost (behind Kansas City).  That means they were healthier than every other team, as measured by this statistic.  Here’s the good news:  AGL might persist.  I looked at this stat in last season’s run-up, and found a correlation value of .30.  So, at least within the data I had, a good performance in AGL one year DOES suggest an increased likelihood of a good performance the following year.  Also, we have Chip Kelly’s “sports science” regime to consider.  It’s certainly logical to believe improved nutrition and fitness will lead to fewer injuries.  This is actually a really important aspect of the Eagles season to track.  If Chip Kelly really can keep his team healthy to a greater extent than other teams, it will be a big advantage for the Eagles going forwards.

Overall, we still have to expect some regression.  The Eagles will probably not finish in the top 2 again in AGL.  Still, with the modest persistence in AGL and Chip Kelly’s focus, I don’t expect as much regression as we might otherwise assume.

Injuries verdict: Slight negative

Interceptions

I won’t spend much time on this one, because I cover it in the Almanac and have addressed it previously.  Basically, Nick Foles was so good last year at avoiding interceptions that it’s nearly impossible for him to duplicate that performance.  However, Foles college and rookie stats do suggest an ability to avoid interceptions.  Hence, I expect Foles to throw interceptions at a higher rate, but to still rank among the best in the league in that category.  All other things equal, though, this is a negative regression indicator for the team.

Interceptions verdict: Negative

Field Position

This one is a bit under-the-radar.  Net Starting Field position is a byproduct of both turnovers and special teams, making it largely random from year-to-year.  Here is a persistence chart showing 5 years of data from Football Outsiders (2008-2012):

The correlation value is 0.14.  That’s large enough to note, but shows there’s a very large degree of variance from year-to-year.

Last season, the Eagles Net Field Position was 0.93.  That means the offense, on average, started with the ball nearly one yard farther than the other team’s offense.   0.93 was good for 11th in the league last season.  For reference, the 2012 Eagles had a Net Field position value of -6.67 yards, worse than any team from last season.  Kansas City led the league last year with a value of +9.61 yards (which is ridiculous and will definitely regress).

I’ve already explained why the Eagles will likely be worse in the turnover department this year than last.  Thus, we should expect field position to be a bit worse.  However, we also have to account for special teams.  This is a bit qualitative, but it’s clear the Eagles roster is deeper this year than it was last year.  That should result in a stronger STs unit.  I don’t have much confidence in that “analysis”, though.  It sounds reasonable, but STs performance is very unpredictable.

Of course, there’s another major piece to this puzzle that I still haven’t mentioned….Alex Henery.  More accurately, the absence of Alex Henery.

According to Football Outsiders, the Eagles had the 2nd worst performance on kickoffs last season, and Henery had the lowest gross kickoff value in the league.  I have no idea how well Parkey will play, but at the very least, he has a stronger leg then Henery.  Again, that should result in better kickoff performance.  Last season the Eagles recorded touchbacks on just 40% of their kicks, which ranked 24th in the league.

So where does that leave us?  Well we should expect some negative regression due to worse performance in turnovers.  Conversely, special teams can be expected to improve a little, at least in the areas that most directly effect field position.

Field Position Verdict:  Neutral

Wrapping it up

There are other areas to explore, but these are the primary ones.  I know I haven’t said anything groundbreaking here, and this analysis isn’t nearly as fun as it was last year (when there were a LOT of areas with very large positive regression expectations).  However, this is, in general, very good news for Eagles fans.

It says, basically, that last year was not a fluke.  The Eagles improved greatly from 2012 to 2013, and whenever you see a 6-win jump in one year, you should look carefully for luck-driven performance.  That’s not the case here.  The Eagles didn’t win games last year because of anything unsustainable, with the notable exception of Foles interception rate.

Thus, we shouldn’t expect and significant negative regression.   The fill-side, of course, is that the team isn’t likely to get a natural boost from any luck-driven areas.  That means improvement, if it comes, will have to depend more heavily on the actual skill of the players.

Final note: remember that there’s no guarantee the Eagles will finish where we expect them to in any luck-driven category.  Just because the “natural” recovery rate for fumbles is 50% doesn’t mean the team will hit it.  As explained above, teams can and do deviate significantly from the mean every year.  Just because the Eagles weren’t particularly lucky last year doesn’t mean they won’t be unlucky this year.  It’s just not our expectation.

2014 Risk Factors: Injuries

As you all know, we should be thinking about this season in terms of an expected performance distribution.  There are a range of outcomes for the Eagles this season, which varying probabilities for each related to how good/bad the team is.  Today, I want to first talk conceptually about the distribution shape.  Then I’ll move into the main topic: Injuries.

I’m going to assume everyone knows the basics of a Normal Distribution (Bell Curve).  I’ve used it often enough here that it shouldn’t be unknown.  The relevant question is: how do NFL team performance distributions compare?  Using the Normal curve as a baseline allows us to logic our way through certain adjustments, leading us to a better mental model for understanding ex-ante team expectations.

I’m primarily concerned with two dimensions: kurtosis and skew.  Skew is relatively self-evident, and more important for our topic today.  It relates to the symmetry of the distribution and the existence of outliers to either side.  Kurtosis isn’t as well known.  It also relates to the shape of the curve, but concerns the degree of peakedness vs. heavy tails.  In other words, kurtosis tells us how much data is located in the center of the distribution (or, conversely, NOT near the center).  Here’s a visual example:

Screen Shot 2014-08-07 at 10.51.33 AM

Now, to the good stuff.

What do we think the shapes of NFL performance distributions are?

I don’t have any data (yet), so we’re operating conceptually (as usual).  Let’s start with Kurtosis, because it’s relatively straightforward and not as important for out topic today.  In generally, I think NFL distributions are fairly Platykurtic.  There is a LOT of luck in the NFL.  That means a team’s “true” performance level is less likely to actually manifest than if there was little luck.  That means ANY projection we make is fairly uncertain.  As a result, it’s not enough to just say “expect 9 wins”.  Any projection of value will also include an expected range, or at least some explanation of downside/upside outcomes.

Now let’s look at skew, because that’s the more relevant measure right now.  Perhaps the most important thing to note here is that performance for an NFL team, as I’ve defined it here (Wins), is bounded on both sides.  No matter how bad a team is, it can’t win fewer than 0 games.  No matter how good it is, it can’t win 16 games.  Hence, when we’re looking at expected performance in terms of wins, the potential for outliers is limited.  Taking the next step, that means the distributions almost certainly are skewed for every team, provided we accept one more assumption as true: it is possibly, at least in theory, for a team to achieve every possible outcome (0 – 16 wins), regardless of “true” ability or expectation.  The Seahawks will almost certainly will more than 0 games this year…but it’s possible.  Even if the odds of that outcome are extremely small, if they exist they must be present on the distribution curve.

Similarly, a bad team will almost certainly not win 16 games.  But an extraordinary run of luck (like opposing injuries) could, in theory, produce a very positive outcome, up to and including 16 wins.  Again, the odds are close to zero, but they exist.

Therefore, an expected performance distribution for the Seahawks might look like this, with the X-axis representing 0 – 16 wins as you move from left to right:

Screen Shot 2014-08-07 at 11.04.10 AM

That curve is negatively skewed, as are the curves for most “good” teams, for reasons I explained above.

Now that we’ve settled that, we need to think about the reasons a good team might end up in the left side of the curve.  Put differently, we know that the Eagles are a relatively “good” team.  While their curve isn’t nearly as skewed as the Seahawks’, I do believe it’s still negatively skewed.  Given that, we can start to think about WHY, beyond the theoretical reasons (bounded range of outcomes), a team’s left tail might exist/be significant.

The most obvious reason is injuries.

Injuries, especially those to star players, present the type of negative events that can result in a team finishing with an outcome towards the left side of the distribution.  Here’s the important part: the Eagles are particularly susceptible this year, hence the team’s left tail is likely a bit larger than usual.  That’s also a big reason why I’m keeping my expectations for the team’s win total in check.  Outliers to the left side or a fat left tail will pull the mean of the distribution down.  So if we’re just talking about average expected wins (there are certainly other ways to look at this), the Eagles “true” level is likely lower than many fans believe.

If Nick Foles goes down….. If LeSean McCoy goes down….. If anyone on the offensive line goes down….

The Eagles are currently heavily dependent on just a few players.  The defensive depth chart improved a bit this offseason, but the offense (largely responsible for the team’s performance las year) is still very brittle.  The problem is, that brittleness was not readily apparent last year, and therefore is likely to be under-appreciated this year.

Last season, the Eagles ranked 2nd overall in Adjusted Games Lost, a measure from Football Outsiders that quantifies the impact of injuries a team suffers over the course of a season.  Here’s how the site describes it:

With Football Outsiders’ Adjusted Games Lost (AGL) metric, we are able to quantify how much teams were affected by injuries based on two principles: (1) Injuries to starters, injury replacements and important situational reserves matter more than injuries to bench warmers; and (2) Injured players who do take the field are usually playing with reduced ability, which is why Adjusted Games Lost is based not strictly on whether the player is active for the game or not, but instead is based on the player’s listed status that week (IR/PUP, out, doubtful, questionable or probable).

In 2012, the Eagles ranked 18th overall.

Clearly, they were more effected by injuries in 2012 than they were last year.  Similarly, the fact that the Eagles ranked 2nd last year combined with the relatively uncertain (non-persistant) nature of injuries means we should expect some mean-reversion.  Basically, it’s likely the Eagles will be more negatively effected by injuries this year, relative to other teams, than they were last season.

Of course, that itself doesn’t tell us much.  We also need to know it injuries, as measured by AGL, actually affect performance (as measured by Wins).  Well here’s the scatterplot showing AGL and corresponding Wins from 2009-2013.

Screen Shot 2014-08-07 at 11.28.28 AM

As you can see, there’s good news and bad news.  The correlation value is -.185.  If the Eagles revert towards the mean (as I expect them to), they’ll be relatively worse off than last year.  However, the correlation is relatively weak, so the effect might not be catastrophic.

Anecdotally, though, I think there’s reason to be concerned, particularly because I don’t like the QB/RB Depth Chart.  An injury to a starter is bad (and shows up in AGL).  However, if the drop-off in talent to the next guy isn’t huge, the effect won’t be significant.  Unfortunately, the Eagles don’t have that luxury at QB.  Moreover, LeSean McCoy is SO good that it’s really impossible to keep the gap between him and the 2nd stringer small.

I should probably note here that I’m not trying to be overly pessimistic here.  However, if we want to create a reasonably accurate performance expectation, we need to look carefully for risk factors.

Injuries are always a major risk factor.  But in the Eagles’ case, I think the risk is atypically large this year.  That doesn’t mean they’ll occur, but it does mean or ex-ante projection needs to account for them.

There’s much more to say around this topic, and I want to present a new version of the Depth Chart Over Time that will make potential injury risk more obvious.  For now though, believe in the Eagles this year, but recognize that the existence of serious downside potential (negatively skewed) results in a mean win expectation that is lower than some might expect (I’ll get a number on it before the season starts).  We can talk about median expectations some other time….

Lowering Expected Variance: Why the Eagles might be “better” but finish the same.

Quick post today.  We’ll start taking a detailed look at the upcoming season soon (hopefully next week), but I wanted to mention a high-level point today.  The over-arching question is: Are the Eagles better this season than they were last season?

I haven’t ventured a complete answer just yet; I still have a lot of stats to go through.  However, I have stated quite explicitly that, from a pure roster perspective, I don’t think the Eagles improved very much (and may actually have gotten worse).  There’s a problem with that statement, though.  It’s incomplete.  Here’s why:

When we talk about a team’s “true” ability level, we’re not really discussing discrete values.  Although many pundits (i.e. anyone/everyone on ESPN) views season projections this way, it’s a very bad method of forecasting.  In reality, ex-ante (before each season), the best we can do is put together an expected performance distribution.  In other words, before the season, we have no idea how many wins each team will produce.  Beyond our inability to fully quantify all the known controllable variables, there’s a HUGE degree of natural uncertainty (luck) in the game.

I touched on this a bit before last season.  In making my projection for the Eagles, I gave a range of outcomes before settling on 9.1 (if I remember correctly) as the average.  I ALSO explained that the Eagles were among the highest VARIANCE teams heading into last season.  Put simply, the team, prior to last season, had perhaps the largest range of expected outcomes.  So while I thought the team “should” win between 9 and 10 games, I also thought it was reasonably possible for them to go 4-12 or 12-4.  Chip Kelly was a big reason for that range; he brought with him a very large degree of uncertainty.  In hindsight, things works out generally as expected (at least on this site) and the Eagles finished with 10 wins.  Note that, given the point differential, the Eagles “true” performance last year was 9.4 wins (via Pythagorean formula).

So why am I telling you this?

Well, if we think about each team’s expected performance as a probabilistic distribution, then there are TWO main ways for the team to actually improve.  Most clearly, a team can increase it’s average win projection.  For instance, it could sign multiple impact starters, or take a great prospect very high in the draft.  Doing so might shift the teams entire distribution to the right, like so:

This is a graphic I used before the playoff game against the Saints.  The X-axis is wins in this example.  The values don’t really matter.  What matters is that the team has moved from left to right.  Clearly, the blue distribution represents a better team.  It’s average performance is much higher.

BUT, there is another way to improve (several actually but we’re focusing on the big ones), at least conceptually.  A team can keep its average win projection the same, but decrease its expected variance.  For example, the Eagles might still be looking at 9.1 wins this year, but the team’s range may have decreased.  That means our certainty increases.

Visually, it might look like this (again borrowing from this post from last season):

Notice the Cardinals; distribution is much narrower than the Eagles’.  Pretend that both have the same average (i.e. move the Eagles to the right so it’s centered on the Cardinals).

That’s better.  To borrow a finance concept, think of the distribution like a stock.  Many analysts/investors use volatility (technically standard deviation, not variance, but for our purposes they’re the same thing) as a proxy for risk.  When looking at an investment, you have to look at both the expected return AND the risk associated with the investment.  Here, you have to look at both the expected average win projection AND the range of potential outcomes.

It’s important to note here that, assuming a symmetrical distribution, narrowing the range ALSO decreases upside while minimizing downside.  Hence, sometimes it is better to have a wide distribution, like when you are a bad team.  However, since there are diminishing returns at the top end of the distribution (a 10 win playoff team isn’t much worse off than an 11 win playoff team), especially where the Eagles look to be headed (good enough to make the playoff but not good enough to challenge for a bye), a smaller range of outcomes is an improvement for the team.

Here’s the important part:

While it’s unclear whether or not the Eagles have shifted their distribution to the right (i.e. expect to win more than 9.4 games this year), it seems very likely that the team has narrowed its range of expected outcomes.

Chip Kelly is no longer huge unknown.  Nick Foles expected performance is undoubtedly higher this year than Michael Vick’s was before last season.  Personnel-wise, the Eagles have made significant improvements below the starters on the depth chart.  Obviously, injuries are a massive source of uncertainty.  Although the Eagles have not added any impact starters (making it tough to increase projected wins), they have made the roster more robust, particularly on the defensive side of the ball.

So yes, the Eagles likely are better this year, if only in terms of uncertainty.  Whether the team’s average win projection has improved is a separate issue that I’ll address over the next couple of weeks.

Nick Foles YPA Projection; An Eagles Almanac Preview

Update: The Almanac is now available for preorder at http://www.eaglesalmanac.com.

Apologies for the lack of posts over the past couple of weeks.  I’ll remain on a very intermittent schedule for the next couple weeks, but after that my schedule clears a bit and I hope to return to a more consistent schedule just in time for training camp to ramp up.

For today, I’m teasing a section of my article for the 2014 Eagles Almanac.  I hope you all purchased it last year and, more importantly, I hope you all enjoyed it.  For those unaware, a group of the best Eagles bloggers puts together an annual season preview magazine.  I contributed last year and will do so again this year.  I promise you there is no better way to get ready and excited for the upcoming season.  Stay tuned for an announcement on its release date and where/how you can get it.

For my piece, I examined Nick Foles performance last year through the lens of his QB Rating.  I pulled it apart and looked at each of his component statistics, then provided context and a projection.  At the end, I put those projections back together to come up with a final QB Rating and stat line that will form my baseline expectation for Nick Foles’ performance next year.  Here is the Yards Per Attempt section.  Note that I have yet to edit it or really re-read it in great detail, as I just finished it; so sorry for any typos/mistakes.

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Yards per Attempt

Last season, Nick Foles recorded 9.1 Yards per attempt, placing him first in the league.  For his career, Foles’ yards per attempt now stands at 7.9.  Of course, the scheme he is playing in now bears very little resemblance to the one he played in his rookie year, so the quality of that information is suspect.  Of the 37 QBs who qualify under Pro-Football-Reference.com’s leaderboard, the median value was 7.0 yards per attempt.  Clearly, Foles’ performance was a relative outlier.  Aaron Rodgers, second overall, registered a YPA of 8.7 and Peyton Manning, third overall, had just 8.3 YPA.  Historically, Foles 9.1 YPA ranks 19th overall.  However, many of the greatest YPA attempt seasons occurred in a different era (mostly completed by Otto Graham).  Post-merger, Foles’ 2013 season ranks 8th overall.  Is that good?

Well, for a little more context, let’s take a look at the best performances by some other QBs.  The only ones to top Foles are Warner, Chandler, Stabler, Rodgers, Dickey, Esiason, and Manning (the good one).  Notice that no player topped Foles more than once.  Joe Montana’s best YPA season merely tied Foles.  Beyond that, the only players to crack the 9.0 YPA barrier were Bert Jones, Steve Young, and Dan Marino.  Again, nobody in the modern NFL has every cracked 9.0 YPA more than once.  That doesn’t mean it’s impossible to do, but it definitely means that it’s extremely difficult.

So how did Foles do it?  Beyond the factors mentioned above (good team health and a low drop percentage), I’m sorry to say that there’s one particular factor that looms large when looking at YPA.  Perhaps you’re tired of thinking about him, but there’s really no way around it in this context: DeSean Jackson was a huge boon to Foles’ YPA in 2013.  Part of what made Foles’ YPA so great last year was his remarkable success on deep passes.  According to PFF, 17.4% of Foles’ total attempts went farther than 20 yards.  On those plays, Foles registered 14 TDs against just 1 interception.  More clearly, here is part of a chart from PFF, showing Foles’ rating by area of the field (I’ve only included the 20+ yard section):

Screen Shot 2014-07-14 at 11.29.51 AM

As you can see, Foles performed much better when his deep passes were targeted at the middle or right side of the field.  Now, which WR do you think was in that area most often?  Here’s the corresponding chart for DeSean Jackson:

Screen Shot 2014-07-14 at 11.33.10 AM

The first number is targets, the second is receptions.  Comparing the two, it’s abundantly clear that Foles’ deep passing success, a major factor in his great YPA (and every other statistic) was highly correlated with DeSean Jackson’s.  There’s naturally a problem of causation here, maybe Jackson played so well because Foles was so great at getting him the ball downfield. (Yes, Vick threw some of those passes to Jackson, but most were indeed thrown by Foles. I think somebody, maybe me, tackled the Vick/Foles/Jackson conundrum a few months ago.)   Looking at Riley Cooper’s chart supports that theory a bit:

Screen Shot 2014-07-14 at 11.35.55 AM

However, look closely at the target numbers (the first listed).  Jackson was target far more often than Cooper (as he should have been), meaning the bulk of Foles performance was in combination with Jackson.  Regardless of who you believe was more responsible for the performance, the fact that Foles and Jackson no longer play together is a bright red flag for a potential change in performance.

To reiterate, Foles YPA performance last year was phenomenal, and very unlikely to be reproduced, even if every factor from last year’s team was reproduced.  The loss of his best deep threat, Jackson, provides even more opportunity for variance from his performance.  As I showed above, any change from last year in Foles’ YPA is almost certain to be negative.

Now the important question: What can we expect this year?

Let’s take a look at the other QBs who registered 9.0+ YPA seasons.  What did they do over the course of their career?  Here is the chart:

Screen Shot 2014-07-15 at 9.24.57 AM

Wow…that’s a bit worse than I expected.  Granted, we have to at least mention the fact that NFL offenses have evolved since most of these players played, and it’s now easier to achieve a high YPA.  However, the fact that only two of the players on that list even cracked 8.0 YPA for their career’s speaks volumes to just how unusual Foles’ 2013 campaign was.  Even Aaron Rodgers, on his way to perhaps the greatest QB career of all-time, has a career YPA nearly a full yard worse than Foles’ 2013 measure.  So yes, it’s safe to say Foles will not put up 9.1 YPA again next season.

Remember that the median value for QBs with 50%+ snaps last year was 7.0 YPA.  Just 6 players of those players had greater than 8.0 YPA.  Now, I want to make it clear that I think Foles will still produce a strong YPA this season.  As I showed, while DeSean was a major force, Cooper also put up sterling deep passing (receiving) stats last season.  Jeremy Maclin, in 2012, also had very strong deep-ball numbers.  Thus, I think league average or median is overly pessimistic.  This is still Chip Kelly’s offense and there are still good players here.  However, we also can’t pencil in 9.0 yards per attempt, at least not with a straight face.  Looking at last season’s leaders, the historical comparisons, and the quirks of the Eagles’ offense, I think somewhere between 7.5 and 8.5 is fair, and if I had to narrow that range I’d put it at 7.5 to 8.3.  Taking the midpoint, that gives us a rough projection of 7.9 YPA.  That’s still very good, it would have ranked 7th overall (tied with Drew Brees) last season.  But that’s a BIG decline from 9.1.

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In the full article, I also make projections for Completion %, TD Rate, and Interception Rate.  Using those numbers, I also provide projections for QB Rating, Yards, TDs, and INTs.

Lane Johnson’s suspension and the rationality of using PEDs in the NFL

Sorry for the absence, combination of exams/vacation/world cup conspired to occupy all of my time.  Fortunately, not much has happened that needs immediate reaction.  At least until yesterday.

As everyone knows by now, Lane Johnson is looking at a likely 4 game suspension after testing positive for PEDs.  There are a few different angles to view this from, but let’s start with the most obvious, the effect on the Eagles.  Clearly, this is a big loss.  The Eagles offense is dependent on the run game, which in turn relies on the O-Line providing lanes for Shady to work with.  Losing Johnson for four games means the Eagles, regardless of how they fill Johnson’s position, will see a decline in performance at RT.  Moreover, assuming the Eagles fill the need from within (Allen Barbre is the favorite), the team is left VERY shallow at OL for the first four games.  So an injury to another member of the OL would move the unit from a team strength to a glaring weakness.

But you didn’t need me to tell you that.  That’s the easy stuff.

A more interesting angle from which to view this story is the overall use of PEDs in the NFL.  Now I’m going to let you in on a little secret about PEDs….the NFL doesn’t care! Why would they?  They make the players bigger, stronger, and faster; they don’t cost the owners anything; and the fans don’t really care either.  The only real losers in this situation are the players themselves (assuming there are long-term negative health effects from PEDs).  So why do they take them?  It’s essentially a prisoner’s dilemma.  In total, the players are probably better off if nobody uses PEDs.  However, if only a few players take them, they are significantly better off than everyone else.  Given the number of players in the league (hard to trust/coordinate with everyone) and the immense competition for every roster spot, the rational course of action for many players is to take the drugs!  Especially when the first suspension is just 4 games.  They can’t trust the testing policies to catch the cheaters, and they can’t trust the other players not to cheat.  Theoretically, they could actually advocate for very strict testing procedures during CBA negotiations, but that’s a topic for another day.

Ok, so obviously the incentives are pretty badly misaligned and there are structural issues within the league that suggests PED use should be fairly widespread.  That brings me to the next angle to this story, and the only one I think the NFL secretly cares about (if only just a little).  The Seattle Seahawks.

Did you watch them last season?  Bigger…stronger…faster.  The team, top-to-bottom, looked to be in better physical condition than everyone they played against.  Now remember they have a coach, Pete Carroll, who has a history of bending (and outright breaking) the rules.  Most glaringly (perhaps I’m burying the lede here a bit), the Seahawks have led the league in PED suspensions since Carroll took over.

Bruce Irvin…Brandon Browner…Winston Guy…John Moffit…Allen Barbre (oh shit)…Richard Sherman (overturned due to technicality)…

That’s a lot of suspensions.  But that’s not all.  Do you think EVERYONE who uses PEDs gets caught?  I don’t know enough about the testing procedures to suggest a catch rate, but we can use logic to figure this one out.  If 100% of those who used got caught, nobody would use!  Ok, maybe a couple of players who were either really stupid or simply believed their only chance was to use PEDs would still do it, but clearly it would be a very small number.  Moving a bit further, look at the penalty for using.  It’s only 4 games!  Conceptually, think about the expected value of this situation.

Option A: Don’t use PEDs, no chance of getting suspended but you are also at a competitive disadvantage.  What’s the alternative employment for most of these players?  The rookie minimum salary is $375,000.  The veteran minimum is either $450,000 or $525,000 (with 2 years of service).  What would these players earn outside the league?  10% of their NFL salary? 20%?  That makes Option A borderline irrational, at least for players on the fringe.

Option B: Use PEDs, gain competitive advantage (or at least avoid a disadvantage).  We don’t know the odds of getting caught (I personally think they’re VERY low), but let’s be extremely conservative here and say 50%.  So if you take option B, there’s a 50% chance you get away with it (at least for the first year, we can iterate this process to account for testing schedules and PED cycles but the overall point is the same).  Conversely, there’s a 50% chance you get caught.  If you do, you’re suspended for 4 games.  So using PEDs carries an expected value of missing just 2 games?  Against the benefits of using PEDs?

Here’s where I should mention that for true fringe players, the downside of getting caught isn’t limited to just the suspension, it may actually cost them their roster spot and place in the league.  However, we also have to acknowledge the likelihood that some of these players, without PEDs, wouldn’t make the team anyway.  Add in the fact that the PED catch rate is almost certainly far less than 50%, and it’s pretty clear that using PEDs is an extremely attractive risk/reward opportunity.  That ignores potential negative health effects.  That may be important to you and me, but I’d suggest that by playing football (with all of the known concussion risks) is a clear signal that these players are not placing as high a value on long-term health as other’s perhaps would.

The Seahawks appear to have this figured out.  I’m not necessarily suggesting that Seattle has an organized, team-sanctioned PED program.  They almost definitely do not.  However, I am suggesting that there’s probably a don’t-ask/don’t-tell policy, and clearly a relaxed attitude that tacitly condones PED use.  Again, that’s a perfectly rational way for Seattle to run its team.  The team-wide benefits more than outweigh the risks.  The occasional suspension is simply a cost of doing business.  Fans can complain about it and other team’s can claim the moral high ground…but the Seahawks are the Super Bowl Champions.

Enter Chip Kelly.  Unconventional coach with a college background and a history of flouting the rules and pushing the envelope?  Sound familiar? #SportsScience anyone?

Needless to say, Lane Johnson’s suspension does not surprise me.  Not even a little.  Now let’s get controversial….I expect more suspensions under Chip Kelly.  Not necessarily soon, but over the next couple of seasons.

I’m not trying to pass moral judgment here, nor am I taking a side on whether I’d support PED use or not.  Just reading the signs and coming to what I think is the most logical conclusion.  The current league incentives encourage PED use (at least until a player gets their first suspension) and I think Chip Kelly realizes it.

Lastly, this is from a 2013 ESPN article that looked at PED suspensions by team from 2010-2013.  Here are the top 5:

Screen Shot 2014-07-01 at 10.33.31 AM

Note the Bengals, Texans, and Rams also had 3 suspensions each.

Here are the teams that did NOT have a PED suspension:

Screen Shot 2014-07-01 at 10.35.15 AM

The NFL…if you ain’t cheating, you ain’t trying.

 

Special Teams Persistence and a few notes

A couple of notes before we talk about Special Teams:

- This Saturday, June 7th, there is an Eagles signing event at the Rockvale Outlets in Lancaster.  Brandon Boykin, Jon Dorenbos, and potentially two other players will be signing autographs from 11 am – 3 pm outside the Eagles Outlet Store.  Swoop and the Cheerleaders will also be there.  The event page is here: https://www.facebook.com/events/1604355479789634/.  I’ve been to this store several times; it’s worth the drive if you’re looking to stock up on Eagles merchandise (or just need gift ideas for friends).  (Note this is not a paid advertisement, but my father does manage the center.)

- If you’re bored at work on Friday afternoons, give these guys a listen: http://sportsandrants.blogspot.com/p/show-segments.html.  Two guys at St Josephs University do a sports talk show from Noon to 2 pm.  They’ve got a site set up (linked above) with their past segments and interviews.  I usually can’t stand the major Philly Sports talk radio (big surprise), so these guys might be a nice change of pace.  Regardless, always nice to give the young’uns a chance.  You can also follow them on Twitter @SportsAndRants.

———-

Now, Special Teams.

I’ve spent most of my time discussing the offense and defense.  Today let’s start our analysis of Special Teams.  The Eagles have made a number of roster moves this offseason that will change the composition of the STs unit.  That might be a good thing.  Last year the team ranked 25th overall by DVOA (Football Outsiders).  Of course, if changing personnel can HELP the unit’s performance, it can also hurt, so we need to be careful with the assumptions we make.  Unfortunately, the biggest single contributor, Alex Henery, is still on the team.  MurderLeg might give him some competition, but Henery has to be the large favorite for the full-time job.

Before we start analyzing the actual roster moves and the potential consequences, we should probably check the data to see if it even matters.  In other words, is Special Teams performance largely skill or luck?  If it’s luck, it doesn’t really matter what players you run out there (within reason).  Of course, Eagles fans should actually hope it’s largely luck-driven, since that means an improvement is likely (given the poor previous performance). So what does the data say?

I took the last 10 years of DVOA statistics from Football Outsiders and checked for persistence.  Here is the graph:

Screen Shot 2014-06-02 at 11.57.01 AM

That’s not what I was expecting.  My ex-ante hypothesis was that STs performance does not persist with any significance.  The data, however, give us a correlation value of 0.29, which is relatively strong.  That means last year’s performance DOES give some indication of what we can expect next season, though it’s far from determinative.

In the near future, I’ll pull this apart and look at the individual factors that comprise the FO data.  That might shed some more light on what we can reasonably expect from the team this year.  For example, last season the Eagles ranked 11th in “Hidden Points”, which are the factors outside their control (like opposing kickoff distance, opp. FG accuracy, etc…).  Conversely, the team ranked just 18th in Weather Points, meaning they were harmed more than average by Weather effects, though since they play outside we may not be able to expect regression there.   As you can see, there’s much more to do here.

The overall takeaway, though, is important.  Special Teams performance, as measured by DVOA, DOES persist with relatively significant strength.  That might mean we shouldn’t expect a great STs unit this year.  OR, it might mean that significant roster turnover within the unit will provide a bigger boost than some of us expect.

Finally, here are some notes from the data:

- Over the past 10 years, Chicago leads the league with an average STs DVOA of 5.07%.  Cleveland is second with an average of 4.12%.  In case you didn’t realize, STs have an effect on the outcome of the game, but not a large one.

- Indianapolis has the worst average over the past 10 years, with a DVOA of -3.10%.  Washington is next with an average of -2.57%.

- The Eagles have an average STs DVOA of 0.15%.  The worst year for the team was in 2007, when it registered a DVOA of -6.40%.  The best season of the past 10 years was way back in 2004, when the team scored a 6.80%

- The worst single season score within the entire sample belongs to the Washington Racists Football Team from last year.  They registered a DVOA of -12.0%, which is remarkable.  The best single season was by Chicago in 2007, with a score of 11.20%.  That was the year Devin Hester had 6 kick/punt returns for a touchdown.  However, the Bears still won just 7 games that season.

 

Optimizing for Chemistry

It’s no secret I was not exactly satisfied by this offseason.  It wasn’t terrible, but it wasn’t great either (I know it’s not over, but the roster-movement phase is largely done).  Between the draft, free agency, and the D-Jax cut, it’s been hard to find a logic thread connecting all of the moves.  For the most part, it looks like the Eagles realize they’re still in the “build” stage of team construction.  That explains the draft.  Smith, Matthews, and Huff are all fine prospects, but as I’ve covered before, they shouldn’t be expected to contribute a lot in year one (the team knows this, the fans haven’t realized it yet).

It also partially explains the Jackson move.  Howie/Chip don’t want to pay a WR that much, and Jackson’s cap hit was going to hurt at some point, especially when it came time to extend Foles, Cox, Kendricks, etc… Now that doesn’t explain the TIMING of it (why now and not next offseason), but it at least has some logic to it.

On the flip side, though, there’s the trade for Darren Sproles.  If you’re still in “build” mode, you probably aren’t looking to give up draft picks for a 30+ year old running back.  I still haven’t quite figured this one out.  Similar to the rookies, I don’t think the team plans on using Sproles as much as fans seem to think they will.  If that’s true, though, a 5th round pick is a lot to give up for a part-time, fill-in weapon like Sproles.  I think this is mainly insurance.  The Eagles know they are heavily dependent on McCoy, and despite what they say, they know there’s at least the risk that the offense without Jackson wouldn’t be as dynamic (that was phrased very carefully so as to avoid another blogwar).  Picking up Sproles gets some of that dynamism (word?) back, at least in theory.  Using Sproles as a band-aid until Ertz and Matthews are ready to step up might be the play here.  I don’t think it makes sense from a resource allocation standpoint, but I can understand not wanting the offense to slide too far.

So that’s the “build” theory of the offseason.  The Eagles overshot expectations last year, meaning fans are now expecting too much this season (recency bias).  The Eagles are not yet ready to contend, and management knows this.  They’d like to contend for the division this year (and with the competition it doesn’t seem that difficult), but they’re more focused on the year AFTER next season.  That’s when the “window” should really start opening if things go according to plan.

There is another story in here, though.  As the title indicates, it’s Chemistry.  Not only is Chip trying to remake the team on the field, he’s trying to instill a different attitude off of it as well.  I don’t think anyone would argue differently.  Whether you call it chemistry, attitude, locker-room presence, or whatever, it’s clear Chip’s trying to change it.  I’m not going to get into whether that’s good or bad.  The general attitude of the team is important.  I don’t typically address it because it’s intangible and unquantifiable.  There’s not data.  Without data, it’s impossible to form an objective opinion of any real value.

BUT….we can analyze it conceptually.  Let’s assume for a minute that Chemistry is both important AND can be quantified.  So for each player we can assign a Chemistry rating, Madden-style.  So along with things like Speed, Size, Catching ability, etc…, prospects and players are analyzed by Chemistry as well.

Now, what happens if you want to optimize for Chemistry?  In other words, in that situation, if you wanted to increase the overall Chemistry rating of your team, what are the other effects?

First, we need to ask a very important question.  Is Chemistry correlated to any other attribute?  So if we assigned a discrete rating for “Skill” as well, would that rating be tied in any way to the Chemistry rating?  Let me start by saying I don’t think they’re positively correlated.  The most “skilled” players do not seem to be more likely to be high “chemistry” guys.  In fact, anecdotally, it seems more likely that the two are negatively correlated.  For now, though, let’s just assume NO CORRELATION.

If there is no correlation, and you want to optimize for Chemistry, you’re going to face a trade-off in skill.  Note that optimizing for BOTH is the same thing, you’re just trying to minimize the negative trade-offs.   So let’s say you’re choosing between three players with the following ratings:

Player A:  Chemistry (90), Skill (70)

Player B:  Chemistry (80), Skill (80)

Player C:  Chemistry (70), Skill (90)

Which player do you choose?  If you’re overall goal is to improve the “Chemistry” on your team, you will take player A, despite that fact that he is less skilled than the other two.  Or, you might compromise and take Player B.  What you WON’T do is take player C.  So one war or another, you’re NOT maximizing Skill.

If we apply this conception to the Eagles, we can see a few issues.  We believe Chip is actively trying to improve “Chemistry”.  As I’ve just explained, doing so will involve trade-offs with other attributes, most notably Skill.  Therefore, it is reasonable to assume that, in the “Chemistry” building process, there will be at least a near-term shortfall in skill.

Now think about DeSean Jackson.  Great player, but probably an asshole in the locker room and during practice.  Think of him as Player C above.  Cut him and the overall Chemistry of the team improves.  However, the overall Skill also decreases.

Over the long-term, a change in attitude is probably a very good thing.  BUT, assuming that the process of improving the team’s attitude does not involve trade-offs anywhere else is foolish.  NOTHING IS FREE (well except trading 6th round picks for multiple 7ths).

This also might explain the Matthews and Huff picks.  By all accounts, those two players rate very highly in our “Chemistry” attribute.  I can see why Chip liked them.  But if that played a role in their selection, it’s likely the team passed on more “skilled” players.  That’s not necessarily a bad thing and I’m not suggesting that it is.   Long-term, the hope is that this leads to a team that’s not only successful, but one you can be proud to root for.  But it takes time, and it requires tradeoffs.