Neil's NFL Daily: May 3, 2013
Yesterday I concluded my draft round-up and waited for the NFL news to flood in. Naturally that didn’t manifest quite as I hoped, but at least Baltimore continued their excellent offseason with another positive move.
Additionally, yesterday’s NFL Daily drew an interesting response in the comments section regarding draft analysis. I felt this interesting topic warranted a longer answer, so for those interested in the subject and some discussion about player valuations, read on.
Friday, May 3rd
Bryant McKinnie Re-signs with the Ravens
It’s not that Bryant McKinnie is performing brilliantly at this stage of his career which makes this a good move for Baltimore — he’s not — it’s more the positive ripple effect across the rest of the line. He didn’t start a single game until the playoffs in 2012, and other than the wild card game against the Colts was broadly average in every regard from then on in. However, starting him at left tackle allowed Michel Oher to go back to right tackle which, in turn, gave them the facility to move Kelechi Osemele to left guard. Now, moving Oher didn’t immediately make him a better player but I’m convinced all the changing positions is having a detrimental effect. To get better at any task requires constant repetition — the facility to ingrain the physical into the subconscious and the two positions require different somatic responses. How can a player who is being asked to play two different positions be as good as if he was asked to concentrate on just one? If it was down to me (Ravens fans send a silent blessing to whichever god they worship that I’m not) I’d put him at RT and leave him there — here’s why.
Over the course of his career, starting in 2009, here is our grading for Oher broken down by position:
Position Snaps Grade
Left Tackle 2540 -9.2
Right Tackle 2364 23.8
Yesterday I wrote, “I’m sure some of the draftees will work out, but Bill Belichick’s track record over the past five years has been average”, which elicited the following question in our comments section:
“Neil, on your criticism of Bill Belichick’s drafting, how do you respond to evidence-based analytics that validate both his strategy and performance?” Bill Marcellino
Firstly Bill, thanks for sending me the report, due to my incompetence at the highly technical task of “clicking on a link”, I only got it a few minutes ago so have only been able to scan read it so far. Hence, if I miss any salient points, please shout.
The most obvious difference is that the time frames are different — I specified five years and this report covers 12. However, it would be a little boring (if entirely reasonable) to simply assert there can therefore be no correlation.
I’d be interested to see the results for the past five years and understand if there is any connection between our view, summarised here, and theirs.
I suspect there will be some link (there usually is if the sample set is broad enough) but this statement, on how the data to value players was arrived at, will lead to many variances.
“We also employ two metrics for measuring the success of drafted players where the first assigns a value to each player’s performance for a season. The second was developed as part of this work and is based on a weighted score for games played, games started and recognition as a top player.”
Essentially, they used the Pro Football Reference stat “Approximate Value” (AV) and their own “Appearance Score” (AS).
Look, I’m not about to start picking at a perfectly valid concept like AV (which is based on a lot of work by someone I really admire) because it’s been used as a tool, in my opinion, beyond that for which it was intended. Despite a massive amount of caveats it’s being employed in this context to say Adam Snyder (AV=30) is a better draft pick than Andy Levitre (24), Louis Vasquez (25) or Jared Veldheer (18), although that’s never what it was intended for.
As for AS, it’s based on starts, played and Pro Bowl nominations. It’s clear that in this form of metric how many snaps a player actually played and how he REALLY performed are secondary. Last year Casey Hayward played in 16 games for 769 snaps, started only seven and didn’t go to Hawaii despite us grading him at +23.2. Jermaine Gresham started 15 games and went to the Pro Bowl even though he was our lowest rated tight end at -19.0 (as you know, the Bengals drafted TE, Tyler Eifert as a likely replacement last week). This would give Hayward an AS of 16+2×7+0=30 and Gresham 16+2×15+14=60.
In short, I don’t doubt the methodology employed on the data is valid, but if the data itself is not of sufficient quality how can the results be valuable? Evidence-based analytics is a great title suggesting wonderful results but the foundations need to be solid.
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