Cowboys Hire John Park as Director of Strategic Football Operations

[boozeman]

That other link in the snippet goes back to 2019:

Don’t look now, but the Cowboys seem to have built the analytics staff Mike McCarthy promised
Promises made, promises (apparently) kept by the Cowboys.

By David Howman@_DH44_ Aug 20, 2021, 5:30pm CDT


Well, McCarthy got the Cowboys job and then immediately got thrust into an unprecedented offseason that was impacted by a global pandemic. McCarthy was able to build out his coaching staff, but nothing was heard of this Football Technology Department again, much less the eight-person analytics team.

Was it all a lie, designed to entice teams into hiring McCarthy? Did the Cowboys simply reassign certain people in their building into those roles instead of hiring new people? Or perhaps the pandemic - the impact of which first started to be felt shortly after McCarthy had completed his coaching staff - prevented the team from making any hires for the time being.

One thing is for sure: McCarthy was a different coach in Dallas than he was in Green Bay. There’s a snide joke to be made here about his win/loss totals, but the biggest difference is that McCarthy’s decision-making in Dallas was largely in line with what the analytics tend to suggest. Sure, he wasn’t always perfect, but it was a big improvement over his Packers days when he openly derided the practice, as well as a big improvement over his predecessor in Dallas.

Either way, it seems that McCarthy may have delivered on his promise of an analytics team ahead of the 2021 season. There are now four different individuals listed on the coaching staff on the team’s website that are dedicated to analytics. Those four are Kyle Valero, Ryan Feder, Eric Simonelli, and Justin Rudd. Valero, Feder, and Simonelli are all listed as quality control/analytics, while Rudd is listed as video/analytics. Not exactly the most descriptive titles, but enough to catch the eye.

Valero may be a familiar name to some, as he’s been with the Cowboys since 2014. We actually profiled him ahead of the 2018 season, when Valero was listed as the assistant wide receivers coach. He joined the team the same year Scott Linehan did, having worked as a quality control coach in Detroit under Linehan for two years. Prior to that, Valero had been a student assistant at Florida State under Jimbo Fisher.

When Linehan left the team after the 2018 season, Valero remained but shifted duties from assisting with the receivers to assisting with the tight ends. Valero once again remained on staff when McCarthy was hired, although he was reassigned to an offensive quality control position. Now, he’s had the analytics title added to that. Given his background and ties to both Kellen Moore and Doug Nussmeier (whom he worked with closely in 2019, when Nussmeier coached tight ends), it could be that Valero is the gameday analytics foreman for the offense, although that’s not confirmed.

The other three names are a bit unknown, but some excellent super sleuthing (read: perusing LinkedIn profiles) offers some clues as to who these analytics gurus are.

According to his LinkedIn profile, Feder actually joined the Cowboys in January of 2020, meaning he was an early addition under McCarthy. Obviously, this hire flew under the radar. His title on LinkedIn is defensive quality control coach/football analytics, which would seem to suggest he’s the defense’s counterpart to Valero. Prior to joining the Cowboys, Feder was a graduate assistant with the Nebraska Cornhuskers for the 2019 season. And before that, Feder was the football technology analyst for the Packers for nearly five years, creating an obvious connection to McCarthy.

However, it’s what Feder did before all of this that is possibly more intriguing. From 2013 to 2015, Feder was a contributor to both Over the Cap and Pro Football Focus; McCarthy, of course, spent time at the PFF headquarters during his year away from coaching, although Feder didn’t work there at such time. Before those two jobs, Feder worked as a data analyst assistant for Metis Sports Management LLC, and before that as a marketing associate with Prudential Financial. He worked that job as a student at Florida State, where he earned a degree in business, management, and marketing. Coincidentally, Feder was at Florida State the same time Valero was there, although it’s impossible to know if the two ever knew each other.

Simonelli doesn’t have quite the rap sheet that Feder does, but he does interestingly predate McCarthy’s hiring. Simonelli joined the Cowboys in the summer of 2019 as a football research assistant. Shortly after McCarthy took the job, Simonelli was reassigned to the title of special teams quality control coach/football analytics, but has since been changed to offensive quality control coach/football analytics. Before joining Dallas, Simonelli was a student assistant coach at Wesleyan University - notable for being Bill Belichick’s alma mater - for two seasons, in addition to a football research internship with the 49ers during the 2018 season.

Rudd is the most intriguing of these four, as he seemingly has very little experience in football. He majored in sports management at UMass-Amherst before spending three years as the video coordinator for the Rutgers football team under head coach Greg Schiano (during his first stint there). After that, Rudd became an account manager at DVSport Inc before being promoted to vice president of sales and marketing, a role he held for nearly seven years before the Cowboys hired him. That job was located in McCarthy’s hometown of Pittsburgh, and may have played a part in his selection, as Rudd became the football video analytics coach shortly after McCarthy was hired.

As of right now, these are the only four analytics staff members listed on the team website, but that’s because the front office tab only lists members of the Jones family; not even Will McClay is on there! So it would seem plausible that these four make up half of McCarthy’s aforementioned eight-person analytics team, although Rudd may be considered part of the video team instead. Either way, it looks as if McCarthy did indeed install the lofty Football Technology Department he had wanted to, or at least some modified version of it. Here’s hoping that the analytical support combines with better injury luck to deliver a better result in 2021.

 

[boozeman]

That's for BtB. They even have to hype up some rando analytics hire.

I really can't find what exactly he did at the Colts other than that he assisted in "the head coaching search".

The other dude, John Li, that Reich got was a former sportswriter.

If these two dudes were so good, why are they available?

 

[Chocolate Lab]

Damn straight, Mickey.

 

[Newt]

So now we just need to sign a bunch of players that get on base... Asian Jonah Hill and fat Brad Pitt will make it work.

That's a Money Ball reference.... Yeah fuck it, back in the shadows...

 

[Cowboysrock55]

Eh, I have no idea what the guy does but I don't really see any significant downside to this. It just adds another perspective to look at.

 

[ZeroClub]

McCarthy used to get criticized about his game management skills. To the extent that the criticism was warranted, it is a very good thing that he's embraced analytics. Stupid and stubborn gets you beat.

Strange to think, though, that in a couple of years, coaches will get advice directly from AI ("Alexa, what play should I call?")

 

[p1_]

Analytics won’t make him a better clock manager.

 

[ZeroClub]

Link: How The NFL Uses Analytics, According To The Lead Analyst Of A Super Bowl Champion

How The NFL Uses Analytics, According To The Lead Analyst Of A Super Bowl Champion
Liam Fox
Former Contributor, Forbes SportsMoney
Aug 12, 2021,08:00am EDT

As is the case with many sports this century, data has changed football.

Analytics are playing an increasingly large role in the NFL, affecting strategy, personnel decisions and ultimately the outcome of games. For many, analytics may seem a confounding idea that clashes with their traditional view of what football is. For others, perhaps it seems merely a buzzword thrown out by coaches and broadcasters to demonstrate that a team has a modern approach. But how exactly are analytics utilized in the NFL and how does utilizing data impact the game today?

Who better to ask than the data analyst of a recent Super Bowl champion? Ryan Paganetti was an analyst and game management coach with the Philadelphia Eagles for six seasons between 2015-2020. He was the primary voice in head coach Doug Pederson’s ear as far as analytics were concerned and Philadelphia was perhaps the most forward-thinking team in the NFL during his time there. Data-driven strategies and aggressive decisionmaking were part of the reason the Eagles won Super Bowl LII in the 2017 season.

Paganetti studied data for the Eagles to help better-inform the team’s game planning and in-game strategy. The Dartmouth graduate was focused on statistical analysis and coaching analytics, feeding any potential advantage he found in the data to the Eagles’ coaching staff.

“Using things like win probability and expected points added to understand the magnitude of plays,” Paganetti said.

Expected Points (EP) and Expected Points Added (EPA) are metrics widely-used today by NFL teams and members of the media. They measure the value of a play and can better-show how effective a player or team is overall and in certain situations. It is generally accepted that EP and EPA tell us more about production than conventional yardage statistics because not all yardage is created equal. For example, a three-yard gain on fourth-and-2 is not worth the same as a three-yard gain on fourth-and-7. EP provides a baseline for specific situations in games and EPA measures if a player or team performs better or worse in that situation than expected.

By utilizing those metrics and others, an NFL team can better-inform its decision making. Analytics also makes game planning more efficient, because the data can quickly show coaches how often an opposing offense or defense utilizes different plays and formations (i.e. team tendencies) and how successful various plays were against those formations. For example, the data may show that an opposing offense uses 11 personnel (one RB, one TE and three WRs) 50 percent of the time and favors running crossing routes and play action out of that formation. Knowing that information without having to watch several hours’ worth of tape is extremely valuable.

Paganetti was hired by the Eagles in 2015, which coincided with Chip Kelly’s last year there as head coach. He was retained when Doug Pederson was hired and built a great relationship with the aggressive and analytically-minded head coach. The Eagles’ use of data started with being more aggressive in specific situations – fourth downs and two-point conversions – which tracks with the league-wide adoption of analytic strategies.

According to a study done by Football Outsiders, an analytics community favorite, Pederson was the most aggressive head coach in NFL history during his time in Philadelphia. The Eagles ranked either first or second in the league in fourth-down attempts all five years under Pederson. The Eagles also led the league in two-point conversion attempts in both 2017 and 2020.

“I think that was a good example of Doug’s receptiveness. Ultimately, it was going to be his decision ... but he wanted to know the information and be able to digest the information and make the best decision for the football team,” Paganetti said.

Paganetti believes that partly because of the Eagles’ Super Bowl success, other teams around the league have adopted aggressive tendencies based on analytics. Fourth-down attempts and two-point conversion attempts league wide have skyrocketed to historic levels over the past few seasons. “The way the NFL works, when one team wins the Super Bowl, the other 31 teams spend the offseason trying to find ideas to copy from that team,” Paganetti said.

Another major area that data informs is in-game situations, which includes clock management (i.e. when to use timeouts versus when to let the clock run), when a play is valuable enough to use a challenge on and when to accept penalties. All of those in-game charts in Philadelphia were finalized before the season according to Paganetti, but could be altered slightly depending on the Eagles’ opponent.

His in-season work largely involved using analytics to help with game planning. Paganetti would analyze the data pertaining to an upcoming opponent to find any sort of statistical tendencies or notable trends that could be exploited. The result of that research could be anything that benefited the team’s approach for that specific game.

“It really was on a week-to-week basis with some of the game planning stuff. It really could be anything that comes up that could be pertinent to that particular week and that is something that I really enjoyed,” Paganetti said.

The timing of communicating that data-based information was crucial. Paganetti needed to have it ready for the coaches when their game planning began, which usually meant either early in the week or even in the week prior to the game to give coaches enough time to install corresponding strategies into their game plan. Paganetti says that he was involved in many of the Eagles’ coaching meetings as well, which gave him more credibility with the staff and players, and helped him understand how the information he was sharing could be utilized and implemented.

He would sit up in the booth during games and meet with Pederson at halftime to share potential strategy changes based on the data he was analyzing during that specific game. Paganetti’s insight was only as helpful as the most recent data he was analyzing.

The pivotal game during the 2017 Super Bowl season as far as analytics are concerned according to Paganetti came in Week 2 against the Chiefs. The Eagles were down two touchdowns and scored late in the game to cut the deficit to eight. Rather than kick the extra point, Paganetti told Pederson that the data dictates that it made more sense for the Eagles to attempt a two-point conversion to try and cut the deficit to six points, knowing no matter what that they needed to score another touchdown later on.

It is a concept that has gained in popularity in the years since and is increasingly employed by NFL teams when they are in that specific situation. At the time however, it was a foreign idea to many in the NFL and in Philadelphia. “I shared this information and I had several staff members, during the game, freaking out and borderline having a confrontation,” Paganetti said. Due to the confusion, Pederson went the traditional route and kicked the extra point.

That small moment ended up being a turning point in the season. Thanks to a post-game discussion between Paganetti and Pederson, and then Pederson and his staff, the Eagles further committed to what Paganetti’s analytics were telling them. Philadelphia won nine straight games after that loss to Kansas City and would raise the Lombardi Trophy five months later. It was a moment that Paganetti believes was critical to that season and critical to the NFL’s continuing acceptance of analytics.

“From that moment on, there was never another time that entire rest of the season where anyone questioned the information I was sharing with him,” Paganetti said.

Prior to that season, as he often did in the offseason, Paganetti conducted various league-wide studies. One of those studies involved the success rate of quarterback sneaks. He looked at what worked, what didn’t and the limits to running that play were. The data showed that it was a significant exploitable advantage in short-yardage situations that Paganetti believed was not utilized enough around the league. Even when the opposing defense was aligned perfectly, the offense in those situations usually picked up the first-down when calling a quarterback sneak.

Paganetti presented his findings to the Eagles, including the optimal offensive alignment, quarterback footwork and situations to maximize the potential of a quarterback sneak play-call. Eagles’ quarterback Carson Wentz went a perfect 13-for-13 on QB sneaks in 2017. It was a black and white example of a data-driven strategy that led to success in games.

“For the coaches, I think it increased the buy-in even more,” Paganetti said. “I think that was a wake up call for certain guys.”
The mainstream acceptance of football analytics seems to start with Brian Burke and his work on the website Advanced Football Analytics starting in the mid 2000s. Now with ESPN, Burke has proven to the NFL what analytics can accomplish and once inspired Paganetti’s own passion in the subject. “If Tom Brady is the G.O.A.T. of quarterbacks, then Brian Burke is the G.O.A.T. of football analytics,” Paganetti said.
Other websites like Pro Football Focus and Football Outsiders have helped popularize the acceptance of football analytics as well and modernized how the game is analyzed.

How analytics are utilized is always changing as the concept becomes more accepted by coaches and general managers around the league. On the personnel side, GPS tracking of player movements and machine learning models are being used to project player success from college to the NFL. The understanding of football data is deepening as well and how analytics are implemented is becoming more nuanced of a conversation.

Its early adoptance was heavily tied to increasing aggressiveness, but that is becoming old news. Paganetti says that he is starting to see the analytics community criticize some teams’ overly-aggressive fourth down decisions, which was rarely the case before. Teams need to find other ways to add value through analytics because going for it more on fourth down and attempting more two-point conversions is no longer an edge; it is now a league-wide phenomenon.

“The thing I’m looking at, I think some of these win-probability models that teams might be using are almost overestimating aggressiveness. So, I think you might even see either this year or next year a little bit of a bounce back,” Paganetti said. “I think to some degree, I think we are getting closer and closer to a limit, particularly with fourth downs. We are approaching peak aggressiveness.”

Paganetti says that he expects to do some consulting work with NFL teams this season and will look to reenter the league as a full-time analyst in 2022. He still feels that he has more to accomplish in the league through the use of analytics. Perhaps Paganetti can try to recreate the Super Bowl magic he captured in Philadelphia alongside Pederson and a certain MVP quarterback.

“I certainly think there is a chance that I will link up with Coach Pederson in the future and maybe we get Nick Foles back and try to run it back,” Paganetti said.

 

[Cotton]

Championship!