Top Ten Most Exciting Games of 2010: Cardinals at Rams

Can two of the worst teams in the NFL play a compelling game? Efficiency, after all, though abstract as a concept, is comprised of tangible, felt-in-the-gut events. Inefficient teams suffer missed assignments and general disorganization by their offensive lines. Inefficient teams suffer discordant timing between their quarterback and wide receivers. Inefficient teams suffer poor spacing and reaction time from their defensive backs. The data that inform a 31st ranked passing offense or a 22nd ranked run defense is in fact the distillation of a season’s worth of errant passes, drops, missed blocks, over-pursuit, blown coverages and missed tackles into a number.

So can the worst team in the NFL and the 30th ranked team in the NFL, by efficiency, play an exciting game?

The answer, of course, is yes. And it isn’t “yes” because there are more things in heaven and earth, Brian, than are dreamt of in your statistics. It is “yes” because football is relative, and bad teams tend to burnish each other’s strengths and mask each other’s weaknesses. If only the best of the best talent, playing at the very peak of their ability, in the most expertly crafted and executed system, were able to play a compelling game of football, well then, college football wouldn’t exist.

So surely the Rams and Cardinals could play a compelling game of football in week one of the regular season, but did they? Well, do you enjoy college football? How about a low-scoring slog punctuated by big moments from legitimately great players?

Arizona traveled to St. Louis in week one of the regular season. It was a game filled with portent. It was first overall pick, quarterback Sam Bradford’s first regular season start of his career. Wait, did I write “portent?” I meant to write, it was a game smothered in tacked-on storylines. It was Derek Anderson’s first start as a Cardinal, Arizona’s first chance to defend their illustrious NFC West title, Bradford’s first chance to obscure an expectantly weak rookie campaign with a few sort-of exciting plays, and Larry Fitzgerald’s first chance to sink some poor sap’s fantasy season. It was football and a retrograde strain of it, but it was football and darn it if that isn’t a welcome sight in June.

Unplug

“News is to the mind what sugar is to the body.”—Rolf Dobelli

You may have noticed there has been a labor action here at Advanced NFL Stats. I’m on a work slow-down, taking a vacation from all the lockout noise. Apparently there’s an NFL lockout going on, and there may or may not be full, normal NFL season this fall. That’s all we know, and that’s all we need to know as fans. That’s the signal, and everything else is noise.

Weeks ago I unsubscribed from rumor mills like Pro Football Talk on my RSS reader. I avoid articles in the sports pages about the lockout and change the station when the local sports talk veers into lockout soap opera. Too much of it is gossip, rumor and speculation, and it’s a giant waste of time.

What Happened to the First Round RB?

In the five-year period between 1970 through 1974, running backs made up 20% of all first round NFL draft picks. That's one out of every five. As recently as the 1985-1989 period, RBs made up 19% of first rounders. But by the most recent decade, from 2000 through 2010, RB selection was cut in half--down to about 10%. Last night, only 1 of the 32 players chosen (about 3%) was a RB, and he was chosen 28th, near the bottom of the round.

The graph below illustrates the trends in how teams favor each position over the past 41 years. Most positions are fairly stable. Click to expand.

Draft Needs According to 2010 EPA - Defense

Measuring defensive players is trickier than offensive players for a couple reasons. Most notably, +EPA (Positive Expected Points Added) captures half the story at best. But the idea is that the part of the story we see will correlate well with the part we don't see. In other words, "playmaking" defenders, in most cases at least, are often making unseen impacts as often as they make prominently visible plays.

The table below lists the 2010 regular season +EPA totals for each team by position. Although it doesn't consider free agent losses or injuries, this might be considered a good starting point for determining defensive draft needs.

Unfortunately, defensive positions are not so cut-and-dry. Depending on the base scheme, there are varying numbers of DEs, DTs, and LBs. (The 49ers don't even have a DE position.) Plus, players can sometimes be designated different positions from week to week. Advanced NFL Stats ultimately classifies players according to their most frequent designation in each game's official playbook.

Draft Needs According to 2010 EPA - Offense

Looking at each team's 2010 regular season EPA broken out by position might provide a decent starting point for identifying team needs. EPA (Expected Points Added) is a statistic that measures each play's change in team net scoring potential. Aggregating the EPA production for each team by position can suggest where teams need to be looking to upgrade or more depth.

For example, consider a team whose production from the offensive line, quarterback, running back, and tight end positions all rank somewhere in the top third of the league. But its wide receiver production ranks in the bottom third. It should be no secret where the team should look to improve.

Although it's doubtful the stats will tell us much we don't already know about team needs, they can confirm, underscore, or possible refute the common perceptions.

The table below lists each team's EPA rankings by position. Within each position, the top third of the league is shaded in green, and the bottom third is shaded in red. EPA stats for the QB, RB, TE, and WR positions are straightforward aggregations of each player's EPA by team. But offensive line EPA is measured indirectly, using the concept of -EPA. Each column is sortable.

Top Ten Most Exciting Games of 2010: Skins at Lions

Rex Grossman straps on his helmet; stretches, paces, takes the field. The field mike picks up a Redskin angrily complaining about a missed facemask penalty on the kick return. The camera zooms on Grossman. It’s his first snap of the season. It’s first and ten on the Washington 30, Skins downs six, 1:54 remaining in the game. On the sideline, Donovan McNabb twists his face into various frowns. His expression seesaws between indignity and self-conscious reserve. Grossman breaks the huddle and sets under center. Washington sets three wide, tight end right, single back shaded left. Detroit sets in a 4-2, linebackers cheating back well away from the line of scrimmage.

Snap.

Grossman sets his eyes deep, dutifully awaiting his first read: the bomb. Pressure churns and approaches, is forced back and surges forward again. He senses it. Grossman looks middle-right, towards his second read: Santana Moss. It’s too late. Kyle Vanden Bosch disengages from Trent Williams, blindsides Grossman and forces a fumble masquerading as a lateral.

A lateral to Ndamukong Suh.

Significance

If you're going to be doing sports statistical research, this is required reading. Click to expand. (From xkcd.com)

Improving Statistical Analysis in the NFL

One of the reasons I have always supported and endorsed Brian Burke and his work at Advanced NFL Stats is his recognition of the limitations of statistical analysis. Ever since statistical analysis took baseball by storm and many of its most prominent practitioners were scooped up and employed by MLB franchises, there has been a crush to translate statistical analysis to other sports. And to varying extents, it has worked.

Football remains relatively impenetrable. It doesn’t have the binary pitcher-batter interface of baseball. Apart from maybe touchbacks, there are no true individual stats. One player’s name may appear beside a 20 yard reception but that reception is the product of: one player passing, one player receiving, x number of players running (ultimately) decoy routes, and y number of players blocking.

All those confounding factors tend to test the intuitiveness of advanced stats. Yes, Austin Collie was the second most valuable receiver by EPA/P, but, no, no one thinks Collie is the second most valuable receiver in football. Even aggregate EPA produces some head-scratchers. Was, for instance, Lance Moore truly more valuable than Marques Colston? Probably not, right? But we are short of information to explain exactly why. Keep in mind, a stat like EPA isn’t arguing that Moore is more valuable as a football players than Colston, only that passes targeting Moore were more valuable in toto than passes targeting Colston.

For the time being, advanced stats really must be combined with scouting to create a meaningful whole. However true that may be though and however long that may be true, that doesn’t mean stats are maxed out. There remains huge potential but some of that potential will never be realized unless the NFL itself improves its own stat keeping.

That is the subject of this piece.