Last week in this space, I talked about the changing way NFL teams build and manage rosters, and how it’s forced the people behind the players — agents, wealth managers, marketing professionals, trainers and everyone else — to adapt, though most of them are still not sure how. One of the points I made was about the disposable nature of draftees (even recent ones that were high picks).
My post drew an email from former NFL scout and longtime friend Matt Manocherian. Those of you who follow this column know Matt scouted for the Saints and Browns before leaving to pursue his Masters in Sports Management from Columbia (he got his undergrad from Duke, so he’s not lacking in the brains department). Today, he’s the Director of Football Development at Sports Info Solutions, one of the leading analytics-based services in the game and a vendor to multiple NFL, NBA and MLB teams. Matt’s also spoken at our annual ITL Combine Seminars in 2017 and as a panelist in 2018.
In his email, Matt (politely) took issue with his perception that I blamed analytics for the fact that teams have selected, and already cut, eight players drafted before the end of the third round. He wrote:
“I couldn’t help but get curious while reading the newsletter last week, so I had our intern pull some college stats from 2016 on the guys that you listed as high pick busts from last year. You can see the attachment for yourself, but long story short: most of these guys had poor advanced college stats. One exception is (Cardinals 2017 4/115 selection) Dorian Johnson, who we expected to play better based on our metrics, but in general, at least in the case of this analytics organization, we weren’t the source of volatility on these misses…if anything, we warned of the possibility!”
This prompted a few thoughts.
- I didn’t express myself well. I never meant to blame analytics for these busted picks. I intended to express that we’re in a period where teams are weighing the value of traditional scouting, metrics, cost analysis, positional scarcity and other factors without a consensus on what’s most effective, and it’s created a very uncertain landscape for draft picks.
- Matt listed the SIS analysis of several of the players listed prior to the ’17 draft. He makes a compelling case that, had the NFL been paying attention, teams might have known what they were getting with these players. There are numerous examples, and I encourage you to check in with SIS’ numbers on your own. Many of the better NFL writers I read regularly cite SIS’ work. For example, Ardarius Stewart was the ninth receiver taken in ’17, while Carlos Henderson was 10th, Amara Darboh 14th and DeAngelo Yancey 25th. Yet based on SIS numbers, all of them rank in the 50s and 60s, at best, among key categories like completion percentage, on-target catch rate, yards per reception and drop percentage among the 200 wideouts SIS ranked. Stewart was their No. 55 WO. Henderson was 58, Darboh was 60 and Yancey was 145, and this is just a cursory look at SIS’ work.
- Virtually every NFL team is trying to figure out in-house how to skin the analytics cat. Meanwhile, services like SIS are spending big money to do an incredibly thorough job evaluating college and pro players alike, and they haven’t yet managed to offer a cost-effective information model for the independent consumer, i.e., agents, trainers, etc. This means there are an awful lot of voices out there but not one that everyone is listening to. Not yet, anyway.
- Until one service shoulders to the front of the pack and becomes the industry standard, or one NFL team becomes the Oakland A’s/Moneyball team, I expect volatility to continue.
Remember: if you dig talking about the direction of the game, how different factors affect scouting and the draft, and what football insiders are doing, thinking and saying, I really recommend you sign up for our newsletter, the ITL Friday Wrap. It’s free, and you can do so here.