The NFL's Analytics Revolution Is Here. Adapt Or Get Left Behind.

chevss454

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Much more to the article at the link below. I catch up with Warren Sharp's articles 5-6 times a year. Brilliant mind.



"The smartest teams are getting significantly smarter, the average teams are trying to get better, and the dumbest teams are going to be very dumb if they don’t act soon."

The new information can also help teams simplify play-calling, like going for it on fourth down more often. The Eagles won the Super Bowl in part because of their aggressiveness in such situations—and in part because they went for two-point conversions when it was mathematically smart to do so. Analytics are not new to football, but this depth of knowledge is. The Eagles have had an analytics department for nearly two decades. “We confirmed,” said Joe Banner, the former Eagles president who helped set up the department, “that there’s a competitive advantage in analytics in a league that is structured to prevent you from having a competitive advantage.”

The Patriots have incorporated some level of analytics for years. (Multiple people joked to me that the movement would have taken hold sooner if the Patriots ever discussed their efforts publicly.)

It is amazing,” Warren Sharp said, “how many teams follow me on Twitter.” Sharp is an engineer with his own analytics site and has been playing around with football statistics for about 20 years. He is among the top minds in football not working full time for a team. In fact, when you talk to people inside the league, some think he might be the top mind, period. Though he’s been writing on the internet for many years, he said it wasn’t until 2018 that teams started reaching out to him to discuss analytics. He says he’s heard from at least five and has done work as a consultant.


It makes sense that teams have become interested in outsiders like Sharp. Unlike other sports, which have staffed up their analytics departments over the past decade or so, football doesn’t employ many of the best analytics minds studying the game. (One team decision-maker sarcastically said this is because analytics employees insideNFL buildings are too beaten down from having their ideas ignored by old-school coaches.) Sharp is in high demand because he can help answer a question vexing front offices: Which stats matter? He became interested in how teams win games when he was in college and became convinced of two things, both of which would foreshadow the modern NFL. The first is that an offensive emphasis on passing correlated to wins. The second is more complicated than it sounds. Sharp found that third-down efficiency, long the obsession of announcers and old-school coaches, was not the key to an effective offense. He found that it was better for teams to scrap third downs entirely and move the chains by gaining the necessary yardage on first and second down.


In 2005, University of Pennsylvania professor Cade Massey and University of Chicago professor Richard Thaler (who would later be awarded the Nobel Prize) published a paper called “Overconfidence vs. Market Efficiency in the National Football League,” which argued that top draft picks are overrated and that trading back for more picks is almost always the right decision. The instant reaction to their findings was not positive, Massey told me: “I met an NFL owner at a cocktail thing, he was all with me, and as soon as I started talking about trading back, he thought I was a complete idiot.”




The idea of trading back has since become widely accepted. Bill Belichick is credited with popularizing the idea in the NFL, and the Browns have recently used it to help stockpile the assets needed to build one of the best young rosters in the league. Similarly, sites like Football Outsiders have popularized dozens of influential stats—among them DVOA—that are now widely accepted in the NFL. One NFL decision-maker mentioned “speed score,” which Bill Barnwell, now with ESPN, developed at Football Outsiders.


Schatz said analytics will be fully accepted only once owners start going along for the ride, when a coach can go for it on fourth down because the numbers say it’s advantageous without fear of getting fired. Hornsby said that he can tell analytics is being embraced more because people are starting to separate the decision from the execution of that decision. The example he brings up comes from Super Bowl XLIX: Malcolm Butler’s game-sealing interception. “It wasn’t the pass, it was the type of pass,” Hornsby said. “[The Seahawks] had run that exact play six times during that year and it had been totally unsuccessful each time; the best they got out of it was a 2-yard outlet on a third-and-5 against Carolina.”
The decision to pass was sound. The pass itself was not.



https://www.theringer.com/nfl/2018/12/19/18148153/nfl-analytics-revolution


Rapid and continuous improvement through understanding all that analytics can provide. Yeah, I'm a believer that anything you can measure can be made better or utilized better in some other way.
 
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chevss454

chevss454

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NextGen Stats is one of the very best.



From the Buffalo game it's easy to see that Gronk isn't the same.
Receiver separation

<figure class="e-image"> <source type="image/webp">
<cite>NFL Next Gen Stats</cite> </figure> While Buffalo’s receivers were able to get some separation on the Patriots’ defensive backs but where generally contained well when targeted. The same goes for the Bills defense, which played tight coverage on New England’s primary passing targets: with the exception of Cordarrelle Patterson, who did most of his damage as a ball carrier, the Patriots’ pass catchers were covered tightly. As a result, Tom Brady oftentimes went to running backs and they ended up catching 6 of 13 pass completions on the day.
 

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An interesting topic. In my industry ( I'm an engineer in semiconductors and data storage technology) I work with a number of firms that are managing large amounts of data and using it for analytics. One of them specializes in providing and managing data for sports teams, including most of the NFL, MLB, NBA, even college sports.
It is amazing what's going on. They have players wearing sensors that allow them to be tracked and monitored. So it's very easy to see if a guy has lost a step, or how fast he runs. This uses GPS technology. If you happen to be in a stadium that doesn't have good GPS reception, they actually set up a micro-GPS network right in the stadium. When you see data saying some guy ran at 22 mph on a INT return, that's data. On the MLB broadcasts, you see the data on how far an outfielder ran to get a ball, and what the % chance was of him catching it.

There are technologies optimized for in-game, such as the tablets you see being used on sidelines, and scouting and recruiting as well.

There's a lot more possible discussion on this of course. Just tossing a quick note, as I am actively working with one firm now in the field and it's pretty fascinating stuff.
 

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I know analytics are now a huge thing is sports & will only continue to be more & more advanced. I just don't like it. No more hat on a hat lets see who wins. Things are different now & I get it. Just don't like sports being determined by *“super nerds.” Showing my age I guess.

*Jayson Werth
 

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An interesting topic. In my industry ( I'm an engineer in semiconductors and data storage technology) I work with a number of firms that are managing large amounts of data and using it for analytics. One of them specializes in providing and managing data for sports teams, including most of the NFL, MLB, NBA, even college sports.
It is amazing what's going on. They have players wearing sensors that allow them to be tracked and monitored. So it's very easy to see if a guy has lost a step, or how fast he runs. This uses GPS technology. If you happen to be in a stadium that doesn't have good GPS reception, they actually set up a micro-GPS network right in the stadium. When you see data saying some guy ran at 22 mph on a INT return, that's data. On the MLB broadcasts, you see the data on how far an outfielder ran to get a ball, and what the % chance was of him catching it.

There are technologies optimized for in-game, such as the tablets you see being used on sidelines, and scouting and recruiting as well.

There's a lot more possible discussion on this of course. Just tossing a quick note, as I am actively working with one firm now in the field and it's pretty fascinating stuff.

I recall a Combine a couple years back that ran a clip on the sensored jerseys athletes were wearing in some college and pro programs.

Tracked movement, speed, breathing, heart rate, etc. No more dogging it.
 

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I know analytics are now a huge thing is sports & will only continue to be more & more advanced. I just don't like it. No more hat on a hat lets see who wins. Things are different now & I get it. Just don't like sports being determined by *“super nerds.” Showing my age I guess.

*Jayson Werth

Yeah, not really. Maybe in baseball. It’s man vs ball.

All the others it’s man on man. You can have analytics thru the roof, but if the film doesn’t show you winning one on one battles you don’t have a chance.
 

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This was a very important read, I believe, and reminded me of the college kid that did a term paper on, I believe, going for it on 4th down and that paper found it's way into Belichick's hands (I think it was about a dozen years ago) and he was intrigued enough to meet the kid and discuss the findings and adopted at least some of the metrics from that paper.

It's a new world out there and I'd like to think the Pats are taking this stuff very seriously and putting a lot of focus on data interpretation.

While the numbers and the data can be valuable, putting that into football context requires folks with football minds that could also be described as open to new ways of thinking and only then can useful metrics be produced.

It's a great read. Thanks, Chevs!
 

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From the Buffalo game it's easy to see that Gronk isn't the same.
Receiver separation

<figure class="e-image"> <source type="image/webp">
<cite>NFL Next Gen Stats</cite> </figure> While Buffalo’s receivers were able to get some separation on the Patriots’ defensive backs but where generally contained well when targeted. The same goes for the Bills defense, which played tight coverage on New England’s primary passing targets: with the exception of Cordarrelle Patterson, who did most of his damage as a ball carrier, the Patriots’ pass catchers were covered tightly. As a result, Tom Brady oftentimes went to running backs and they ended up catching 6 of 13 pass completions on the day.

Could you briefly explain what these separation diagrams are trying to show? I have seen many of these and I read this data as Edelmann get separation 2.63 yards off the LOS, Gronk at 1.28 yards off LOS, and Patterson 4.05 yards off LOS or are these Reverse WR Sep Diags? Perhaps I'm missing something.....The Bills clearly have much better schooled M-2-M coverage DBs than the mostly played treacherous Zone secondary coverage of the Pats. This is a great article and you have to be wondering who are the analysis personnel within the Pats?
 
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chevss454

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Could you briefly explain what these separation diagrams are trying to show? I have seen many of these and I read this data as Edelmann get separation 2.63 yards off the LOS, Gronk at 1.28 yards off LOS, and Patterson 4.05 yards off LOS or are these Reverse WR Sep Diags? Perhaps I'm missing something.....The Bills clearly have much better schooled M-2-M coverage DBs than the mostly played treacherous Zone secondary coverage of the Pats. This is a great article and you have to be wondering who are the analysis personnel within the Pats?


It's yards of separation from the defender (not LOS).


Caserio and the old guy wearing the phantom suit, Ernie Adams.
 
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chevss454

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Per Sports Info Solutions (which is partners with Football Outsiders, CBS Sports, Off The Charts and RotoWire)



% of man coverage...Pats lead the league and surprisingly the Steelers come in 3rd. It seems Tomlin has finally learned a new trick


 

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Per Sports Info Solutions (which is partners with Football Outsiders, CBS Sports, Off The Charts and RotoWire)



% of man coverage...Pats lead the league and surprisingly the Steelers come in 3rd. It seems Tomlin has finally learned a new trick



Your post again shows some very interesting statistical data. Although Pats try to play Man Coverage 56.8% of their D play, Pats are rated 22 in Defense/tackles

@ http://www.patriotsplanet.com/BB/newreply.phpdo=newreply&p=2560513

Tackles( Tot=622, Tak=322, saks=26, Interceptions : (PassDef=78 ,Int=18 , TDs=1 , Yrds=156 ).

I think it is clear that Pats total secondary coverage needs much better M-2-M coaching that Josh Boyer has not been able to provide. I wish we knew more about Obi Melifonwu, who is a talent ton but is often healthy scratched or is only played STs in 2 Pats games this year and made 3 tackles.
 

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I know analytics are now a huge thing is sports & will only continue to be more & more advanced. I just don't like it. No more hat on a hat lets see who wins. Things are different now & I get it. Just don't like sports being determined by *“super nerds.” Showing my age I guess.

*Jayson Werth


If I remember Werth's quote in context, he was merely pointing out that even if data analytics tell you to bunt down the third base line to counter the way the other team's infield has shifted on you ... you still have to execute the bunt.


The analytics for the most part are probabilistic models; they can predict what is most likely to happen, but cannot predict with any certainty what will happen. Butler's famous SB interception (mentioned in the article) was a perfect storm of Butler being coached to recognize the play, Butler's in-game decision to react to that play correctly once he saw it, and, most importantly, Butler's ability to hang on the football once he got his mitts on it. That's three major steps: recognition, reaction, and execution. I don't think analytics could have helped much past the first step.
 

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Was listening to Rob Ninkovich yesterday and he was questioning all this stuff for football.

His point was tthat they dont know what the play call, scheme etc entails in any given game.

Sent from my SM-S367VL using Tapatalk
 

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If I remember Werth's quote in context, he was merely pointing out that even if data analytics tell you to bunt down the third base line to counter the way the other team's infield has shifted on you ... you still have to execute the bunt.


The analytics for the most part are probabilistic models; they can predict what is most likely to happen, but cannot predict with any certainty what will happen. Butler's famous SB interception (mentioned in the article) was a perfect storm of Butler being coached to recognize the play, Butler's in-game decision to react to that play correctly once he saw it, and, most importantly, Butler's ability to hang on the football once he got his mitts on it. That's three major steps: recognition, reaction, and execution. I don't think analytics could have helped much past the first step.

You're leaving out two other key aspects of Butler's interception.

Browner also recognizing the play and successfully jamming his WR at the line, thus leaving a clear path for Butler to get to the proper position, in time, to be in position to make the interception.

This is why it wasn't such a brain dead call by Seattle.

A whole lot of things had to be executed perfectly by the Pats to make that interception.
 

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NextGen Stats is one of the very best.



From the Buffalo game it's easy to see that Gronk isn't the same.
Receiver separation

<figure class="e-image"> <source type="image/webp">
<cite>NFL Next Gen Stats</cite> </figure> While Buffalo’s receivers were able to get some separation on the Patriots’ defensive backs but where generally contained well when targeted. The same goes for the Bills defense, which played tight coverage on New England’s primary passing targets: with the exception of Cordarrelle Patterson, who did most of his damage as a ball carrier, the Patriots’ pass catchers were covered tightly. As a result, Tom Brady oftentimes went to running backs and they ended up catching 6 of 13 pass completions on the day.

That stat can be a little misleading.

For one, it doesn't take into account the ability of a QB to put the ball in the one single location where only his receiver can catch it.

Such QB's are willing to make some pass attempts when there isn't a lot of separation.

Where as, QB's who can't or aren't confident enough, to make such throws will only make passes that have greater separation.

Also, it doesn't take into account what the defense is doing.

If they are playing tight man to man, then the separation is going to be smaller, on most plays, than if they are playing zone.

It also does not consider how that coverage may shift due to game circumstances. if one team is playing some sort of "prevent" defense, then they will typically have more separation on the WR's as part of the defensive call.

It doesn't take too many offensive series of this to skew the #'s.

In addition, Buffalo had the #1 pass defense in 2018, so they deserve some credit here.

If you look at the other recent games Gronk's separation is much better. So that would lend so credence to Buffalo's defense having something to do with those numbers.
 

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You're leaving out two other key aspects of Butler's interception.

Browner also recognizing the play and successfully jamming his WR at the line, thus leaving a clear path for Butler to get to the proper position, in time, to be in position to make the interception.

This is why it wasn't such a brain dead call by Seattle.

A whole lot of things had to be executed perfectly by the Pats to make that interception.


Agree, and I think you've reinforced my point ... analytics can only help decide what you should do.
 
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chevss454

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That stat can be a little misleading.


It says quite clearly "from the Buffalo game" and the chart only pertains to separation of receivers in the Pats-Bills game. Perhaps I was hasty when I opined that "Gronk isn't the same". But that's on me - that's my interpretation of the chart and not the fault of the chart itself. Nevertheless, imo Gronk isn't the same guy he was 5 years ago or even last year.


Here's the link for the receiver separation chart from the Jets game which shows Gronk is only a tad better.

https://nextgenstats.nfl.com/stats/game-center
 
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