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| ..... 1. Most teams don’t shy away from analytics. In fact, more than one official was offended by the notion that their team would be called “old school”. When it comes to player acquisition (which is what Moneyball was based on), the average NFL team is using the data. It’s just that it is being used to generate boundaries rather than drive decisions. Teams want to know when they’re making exceptions on one player, and they want to know what they might be missing on another they may have otherwise dismissed. 2. On the coaching side, analytics are generally used to make staffs more efficient. There may only be time for quality-control coaches to break down four or five of an opponent’s games in the week they have leading into a particular game. And that, in the past, would lead to guesswork on tendencies and strengths and weaknesses. The data allows the quality-control guys, and staffs, to crosscheck against larger sample sizes. 3. The limits in those two areas are the number of games (16) and the variance in players’ assignments and situations that affect plays. That makes it more difficult to collect the amount of data necessary to make hard decisions. 4. Conversely, the value of the data in those areas is proven in that nearly the entire NFL has subscribed to Stats LLC and/or Pro Football Focus, and some rely on smaller services, like Pro Scout Inc., which is run by 64-year-old former Utah coach Mike Giddings. 5. There aren’t sure marks of analytics-friendly operations on game days (as there is in basketball, with teams that go for the “two-for-one” possession at the end of the quarter or half). But on the personnel side, you can see it in asset management, with teams that trade down in the draft to pad their margin for error, and use cap space creatively. 6. There is one strong consensus league-wide: Analytics data related to injury prevention, which straddles sports science and comes through player tracking, is useful and will only get better. The NFL is just scratching the surface with this technology, and the floodgates will truly open only when the league makes available all the Zebra data it’s been collecting. Another step here that’s expected to come eventually is in profiling the minds of players. 7. The Walsh/Belichick robot is not on the market. Yet..... |
Yeah, he can use all that sweet GPS tech to located a Barnes & Noble and pick up a book on play calling.
What most of them come to as a conclusion is that predicting if an injury-prone player in college will stay injury prone in the pros or if a healthy player in college will remain healthy in the pros is a case-by-case basis, regardless of the injury. Even when it comes to concussions. Head injuries might speed a player out of the league, but there is not a correlation to if a player has had concussions previously that he's more prone to them, and there are countless examples of players who never had one in college, getting them in the pros.
My fear is that unreliable statistics will be used to predict if a player is injury prone or not, where there are countless examples of player's who had a significant injury in college, being relatively healthy in the pros, or guys like Mantai Teo who were healthy in college and can't stay on the field in the NFL.
No clue, it's why I said WTF? I assume maybe off-field stuff, maybe try and figure out if the player is the type to pick up the playbook?
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Yeah, he can use all that sweet GPS tech to located a Barnes & Noble and pick up a book on play calling.
Yeah... it's not like the guy led the team into a top offense as an OC before. I'm still stunned he got the HC job after the offensive ineptitude shown by the team when he was the OC.
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What exactly do they mean by 'profiling the minds of players' ?
No clue, it's why I said WTF? I assume maybe off-field stuff, maybe try and figure out if the player is the type to pick up the playbook?
I figured it was along the lines of the behavioral/psychological profiling that the Giants and others used to do.
If you collect a few years worth of data and run some models against it, you should be able to build some psychological profiles for the participants, then pick out which were successful and which were busts (if you're using historical data, e.g. profiles for players in prior drafts whose performance in the NFL is known).
The psychological profile may help find out what makes him tick and what makes him so good. Look for players with a matching psychological profile.
I think if anyone in the league is at the forefront of this type of player analysis it probably is the Giants, given their track record in finding high-performing FA.
Using analytics to make minor, relatively invisible tweaks is one thing. Using them to make obvious, radical changes in play calling and game strategy will take some time.
Yoda ears under that hood ?