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.

Top Ten Most Exciting Games of 2010 - Dolphins at Packers

In light of winning Super Bowl XLV, the Packers home loss to the Dolphins is artistic. Not Artistic like, say, a Rothko color field. More like Varinia leaving for Gaul, showing their newborn son to Spartacus, saying “Please die, my love... die, die now my darling!” artistic. A cave hidden in the great artistic crevasse that is impenetrably deep but opens at the banks of the River Schmaltz.

You see.

The Packers week six loss is a story of spurned ambitions, sudden reversal and anticlimax. It feels essential within the greater narrative of the 2010 Packers. It was the second of consecutive overtime losses, both by field goals, that dropped the Packers to 3-3. It was among Aaron Rodger’s worst games of the season. It was his first following his first concussion of the season. He would suffer another in Week 14.

It was a loss, yet, in the associative, irrational, romantic human brain, it can now be interpreted as a story of manning up, hanging tough and accepting transient defeat in the pursuit of eternal glory. Heady stuff. But in the eternal present of an MP4 file, the Packers know only bitter defeat. Again and again. Forever.

Top Ten Most Exciting Games of 2010: Lions at Bears

Known mostly as the game Gene Steratore and his officiating crew redefined what a catch is, changing the outcome of the entire game and delivering the first big controversy of the regular season, week one’s contest between the Bears and Lions was a division showdown pitting rivals with striking similarities: Two young, hugely-expensive franchise quarterbacks attempting to break through after a poor first season; two dominant defensive lines; two suspect-to-atrocious offensive lines.

Why this game was exciting: This game was exciting as determined by win probability, because the score was within one point for most of the second half, and because the two teams combined for seven turnovers including five fumbles lost (out of seven fumbles total.) That led to wild swings in win probability despite a static and nearly even score.

Turning of the tide: Detroit’s win probability peaked at 85% following a nine yard reception by Matt Forte with 1:25 left in the first half. On the very next play, Forte released out of the backfield into a speed out, Olin Kreutz submarined Julian Peterson with a pretty and perfectly-timed open-field cut block, and Forte ran up the right sideline for 89 yards and a touchdown. Three plays later, Julius Peppers ran under a block by Jeff Backus, turned the corner nearly uncontested, and blindsided Matthew Stafford for a sack-fumble recovered by Tommie Harris. Within little more than one minute of play clock, the Bears surged from 15% win probability to 54% win probability. Stafford would miss the next six weeks including the bye.