Cowboys hire 3rd data geek this offseason, but this one's a baller

[fredp22]

Colts, Steelers, Ravens. 3 teams that havent won anything for a while and let their analysts go so we grab all 3. Sounds like a Chinese fire drill of 2nd rate analysts. Should be a riot when they all disagree on same situation.

 

[CowboysLakerBamaFan]

So far this summer, Cowboys have hired director of strategic football operations John Park from Colts, strategic football analyst Sarah Mallepalle from Ravens and now strategic football analyst William Britt from Steelers. Will be interesting how each team perspective contributes

https://cowboyswire.usatoday.com/lists/cowboys-william-britt-analytics/

They're hiring every analytics dork available.

Yet....he won't hire an actual GM.

Well....it's only been 3 decades....I'm sure GM Jerruh only needs a couple more decades and he'll finally have it all figured out. I'm surprised he doesn't coach the team too!

 

[Bobhaze]

I’m sure I’m missing something, but if the “analytics” we are talking about are anything similar to what’s used in baseball, I can’t at all see how it fits or would be useful.

There are too many variables in football to compile league wide numbers and have it matter much in a given moment.

Maybe one of you smart people wouldn’t mind explaining what these folks will be attempting to determine and how. I can’t see it.

Actually analytics in football has proven to be very useful and effective. More and more coaches have begun to embrace data collection that can inform game planning, tendencies of the opponent and help with informed in-game decisions.

Guys like Nick Saban, Bill Belechick, Andy Reid, Lincoln Riley, and many others are recognizing its help in making better decisions based on facts not just feelings.

Here are just a few of ways football coaches use analytics these days:

• Player Performance Analysis: Tracks players' movements and actions on the field, giving insights into a player's situational strengths and weaknesses. This data can be used to optimize training programs, identify areas for improvement, and make informed decisions about optimizing a player’s playing time. It can also help a Coach be better informed when to use a particular player in certain situations.
• Game Strategy Optimization: By analyzing data on opposing teams and their players, coaches can develop better informed game plans that take less time. The data collected on opponents can identify the weaknesses of an opposing team in certain situations, down and distance tendencies and adjust tactics accordingly. It’s all about making better informed decisions.
• Injury Prevention: By tracking data on players' movements and physical exertion, and when injuries tend to occur, teams can identify players who are at risk of injury and take steps to prevent them.

Analytics are a tool to make you better in preparation decisions, as well as in-game situational football.

 

[TequilaCowboy]

So far this summer, Cowboys have hired director of strategic football operations John Park from Colts, strategic football analyst Sarah Mallepalle from Ravens and now strategic football analyst William Britt from Steelers. Will be interesting how each team perspective contributes

https://cowboyswire.usatoday.com/lists/cowboys-william-britt-analytics/

Don't know why they couldn't just come here on CZ and hire those strategic football analysts.....we have lots of them here. And probably far less cheaper so Jerry can restock his liquor cabinet on the yacht. Off the record, i really don't think they will make any difference in the strategory department. It ain't complicated.

 

[MyFairLady]

Jerry still gonna play with his favorite toy however he likes. Hey he owns it so all the power to him. Unfortunately he is an incompetent drunken clown.

 

[MyFairLady]

Jerry is like Lennie tending those rabbits.

 

[Mac_MaloneV1]

I like how people think Jerry Jones has anything to do with these hires lol

All he's done is approve the budget for analytics - without knowing exactly who the analytics team reports to, they're probably either McClay or Wansley hires.

 

[gtb1943]

I like how people think Jerry Jones has anything to do with these hires lol

All he's done is approve the budget for analytics - without knowing exactly who the analytics team reports to, they're probably either McClay or Wansley hires.

The buck still stops with Jerry unless you believe in the Tooth Fairy

 

[gtb1943]

Actually analytics in football has proven to be very useful and effective. More and more coaches have begun to embrace data collection that can inform game planning, tendencies of the opponent and help with informed in-game decisions.

Guys like Nick Saban, Bill Belechick, Andy Reid, Lincoln Riley, and many others are recognizing its help in making better decisions based on facts not just feelings.

Here are just a few of ways football coaches use analytics these days:

• Player Performance Analysis: Tracks players' movements and actions on the field, giving insights into a player's situational strengths and weaknesses. This data can be used to optimize training programs, identify areas for improvement, and make informed decisions about optimizing a player’s playing time. It can also help a Coach be better informed when to use a particular player in certain situations.
• Game Strategy Optimization: By analyzing data on opposing teams and their players, coaches can develop better informed game plans that take less time. The data collected on opponents can identify the weaknesses of an opposing team in certain situations, down and distance tendencies and adjust tactics accordingly. It’s all about making better informed decisions.
• Injury Prevention: By tracking data on players' movements and physical exertion, and when injuries tend to occur, teams can identify players who are at risk of injury and take steps to prevent them.

Analytics are a tool to make you better in preparation decisions, as well as in-game situational football.

Its more organized and on paper, but got news for you. The best coaches and staffs were pretty much doing the same thing since football began.

Its just on computer graphs then in the coaches and staffs heads.

 

[Mac_MaloneV1]

The buck still stops with Jerry unless you believe in the Tooth Fairy

If you think he's spending time interviewing and hiring analysts you're out of your mind

 

[Jumbo075]

Maybe they should hire someone to analyze Jerry and Stephen.
Did I do that right?

Analytics professionals don't make decisions. Their job is to give better information to the decision makers.

I am in a similar situation in one of my roles. In addition to implementing large building renovation projects, I analyze our existing portfolio of 176 buildings to determine which buildings are in most dire need of renovation, which buildings should be torn down, and what new buildings we need to meet organizational goals. That is only about 10% of what I do, but it is an important 10%. Based on my recommendations, we have cancelled renovations for 3 buildings already, moved a data center out of a building to an off-shore facility, and demolished and removed three buildings. I am recommending the demolishing of at least 3 more buildings on our campus, and I sit on the design teams for new buildings. (another 10% of my responsibilities.)

With all that, I don't make final funding decisions. But just to illustrate, I was given $9 Million to renovate an existing old building. Based on my analysis, I determined I really needed $28 million to properly renovate the systems in the building, and then would still have an old building not really designed to be functionally useful for the existing occupants. The building is only worth $56 million, so I recommended they tear it down instead of wasting $9 million on renovations. I didn't make the decision, but they did opt to take away the $9 million they gave me, and are in the process of planning a new building to be erected some time in the next 5 years.

This is the value of analytics. It helps decision makers with making better informed positive decisions, and helps avoid poor decisions being made.

Analytics doesn't run the show, in the same way that I don't make funding decisions for my organization. But it helps decision makers get better information, so that they can make better decisions - in the Cowboys case on what plays to call in certain situations against certain opponents. If you have a problem with that, you're just ignorant, or worse - you want the Cowboys to keep making the ignorant decisions that have kept them from winning championships the last 3 decades.

 

[AbeBeta]

I’m sure I’m missing something, but if the “analytics” we are talking about are anything similar to what’s used in baseball, I can’t at all see how it fits or would be useful.

There are too many variables in football to compile league wide numbers and have it matter much in a given moment.

Maybe one of you smart people wouldn’t mind explaining what these folks will be attempting to determine and how. I can’t see it.

Too many variables?

Gee. Who is good with too many variables? Is it humans or is it computers? (Hint: It is not humans).

 

[CCBoy]

They're hiring every analytics dork available.

Yet....he won't hire an actual GM.

Well....it's only been 3 decades....I'm sure GM Jerruh only needs a couple more decades and he'll finally have it all figured out. I'm surprised he doesn't coach the team too!

C'mon...he is a strong owner, not stupid, and trusts his staffs/coaches. At least hit in a general current target area...

Oh, I get it now...when one grows up he wants to be a brand new pair of bluejeans.

 

[CCBoy]

Analytics professionals don't make decisions. Their job is to give better information to the decision makers.

I am in a similar situation in one of my roles. In addition to implementing large building renovation projects, I analyze our existing portfolio of 176 buildings to determine which buildings are in most dire need of renovation, which buildings should be torn down, and what new buildings we need to meet organizational goals. That is only about 10% of what I do, but it is an important 10%. Based on my recommendations, we have cancelled renovations for 3 buildings already, moved a data center out of a building to an off-shore facility, and demolished and removed three buildings. I am recommending the demolishing of at least 3 more buildings on our campus, and I sit on the design teams for new buildings. (another 10% of my responsibilities.)

With all that, I don't make final funding decisions. But just to illustrate, I was given $9 Million to renovate an existing old building. Based on my analysis, I determined I really needed $28 million to properly renovate the systems in the building, and then would still have an old building not really designed to be functionally useful for the existing occupants. The building is only worth $56 million, so I recommended they tear it down instead of wasting $9 million on renovations. I didn't make the decision, but they did opt to take away the $9 million they gave me, and are in the process of planning a new building to be erected some time in the next 5 years.

This is the value of analytics. It helps decision makers with making better informed positive decisions, and helps avoid poor decisions being made.

Analytics doesn't run the show, in the same way that I don't make funding decisions for my organization. But it helps decision makers get better information, so that they can make better decisions - in the Cowboys case on what plays to call in certain situations against certain opponents. If you have a problem with that, you're just ignorant, or worse - you want the Cowboys to keep making the ignorant decisions that have kept them from winning championships the last 3 decades.

The staff can even keep trends current by an opposing team and circulate stat sheets by half time...great tool.

 

[CCBoy]

Analytics professionals don't make decisions. Their job is to give better information to the decision makers.

I am in a similar situation in one of my roles. In addition to implementing large building renovation projects, I analyze our existing portfolio of 176 buildings to determine which buildings are in most dire need of renovation, which buildings should be torn down, and what new buildings we need to meet organizational goals. That is only about 10% of what I do, but it is an important 10%. Based on my recommendations, we have cancelled renovations for 3 buildings already, moved a data center out of a building to an off-shore facility, and demolished and removed three buildings. I am recommending the demolishing of at least 3 more buildings on our campus, and I sit on the design teams for new buildings. (another 10% of my responsibilities.)

With all that, I don't make final funding decisions. But just to illustrate, I was given $9 Million to renovate an existing old building. Based on my analysis, I determined I really needed $28 million to properly renovate the systems in the building, and then would still have an old building not really designed to be functionally useful for the existing occupants. The building is only worth $56 million, so I recommended they tear it down instead of wasting $9 million on renovations. I didn't make the decision, but they did opt to take away the $9 million they gave me, and are in the process of planning a new building to be erected some time in the next 5 years.

This is the value of analytics. It helps decision makers with making better informed positive decisions, and helps avoid poor decisions being made.

Analytics doesn't run the show, in the same way that I don't make funding decisions for my organization. But it helps decision makers get better information, so that they can make better decisions - in the Cowboys case on what plays to call in certain situations against certain opponents. If you have a problem with that, you're just ignorant, or worse - you want the Cowboys to keep making the ignorant decisions that have kept them from winning championships the last 3 decades.

Thanks for expanding working knowledge and improving perspectives. Good stuff and explains Corporation level function as well.

 

[CCBoy]

Colts, Steelers, Ravens. 3 teams that havent won anything for a while and let their analysts go so we grab all 3. Sounds like a Chinese fire drill of 2nd rate analysts. Should be a riot when they all disagree on same situation.

Buy your lottery and Power Ball tickets yet?

I'm not a changer...or even an ATM machine myself.

Know why a crocodile is so vicious? He has all those teeth and no tooth brush.

 

[Jumbo075]

Thanks for expanding working knowledge and improving perspectives. Good stuff and explains Corporation level function as well.

One example of potentially poor decisions that can be avoided is signing players to contract extensions.

Based on analytics, the Cowboys determined a year ago the maximum contract amount they would offer to Dalton Schultz. When he refused that offer, the Cowboys used a 4th round pick in 2022 and a 2nd round pick in 2023 to find his replacement. In the meantime, they used the franchise tag to keep Dalton Schultz for one more year, with the full intention of dumping his contract this season in favor of replacing him with either (in this case) Ferguson or Schoonmaker.

Analytics would tell you that in 2022, the Cowboys actually scored fewer points with Schultz on the field than without him on the field. That made it easier to make the decision to move on from Schultz - regardless of his pure statistical ranking when considered outside the context of team productivity.

 

[CCBoy]

One example of potentially poor decisions that can be avoided is signing players to contract extensions.

Based on analytics, the Cowboys determined a year ago the maximum contract amount they would offer to Dalton Schultz. When he refused that offer, the Cowboys used a 4th round pick in 2022 and a 2nd round pick in 2023 to find his replacement. In the meantime, they used the franchise tag to keep Dalton Schultz for one more year, with the full intention of dumping his contract this season in favor of replacing him with either (in this case) Ferguson or Schoonmaker.

Analytics would tell you that in 2022, the Cowboys actually scored fewer points with Schultz on the field than without him on the field. That made it easier to make the decision to move on from Schultz - regardless of his pure statistical ranking when considered outside the context of team productivity.

Agreed that team founded stats and influences are pretty important. Opponents know them all on the Cowboys and use them at their own convenience;

 

[Jumbo075]

Actually analytics in football has proven to be very useful and effective. More and more coaches have begun to embrace data collection that can inform game planning, tendencies of the opponent and help with informed in-game decisions.

Guys like Nick Saban, Bill Belechick, Andy Reid, Lincoln Riley, and many others are recognizing its help in making better decisions based on facts not just feelings.

Here are just a few of ways football coaches use analytics these days:

• Player Performance Analysis: Tracks players' movements and actions on the field, giving insights into a player's situational strengths and weaknesses. This data can be used to optimize training programs, identify areas for improvement, and make informed decisions about optimizing a player’s playing time. It can also help a Coach be better informed when to use a particular player in certain situations.
• Game Strategy Optimization: By analyzing data on opposing teams and their players, coaches can develop better informed game plans that take less time. The data collected on opponents can identify the weaknesses of an opposing team in certain situations, down and distance tendencies and adjust tactics accordingly. It’s all about making better informed decisions.
• Injury Prevention: By tracking data on players' movements and physical exertion, and when injuries tend to occur, teams can identify players who are at risk of injury and take steps to prevent them.

Analytics are a tool to make you better in preparation decisions, as well as in-game situational football.

Agree 100%.

But why coaches need good statistical analysts on their staff is lost on many people. It has to do with the quality and relevance of the data. Analytics is data driven, but which statistical measures are relevant, and which are not. For example, when used in personnel selection:

• Arm length is correlated to height, and arm length is very statistically relevant when projecting success for pass rushers and offensive tackles.
• 40 time speed is very relevant for wide receivers, and defensive backs, but almost a non-factor in evaluating quarterbacks.
• A good 3-cone time may be more important for some positions than others.
• Bench press repetitions is not very relevant to how successful a running back will be.
• No one wants to draft a 250 lb. offensive lineman, no matter how agile he may be, or how skilled he may be at using leverage.

The job of the data analyst is not just to crunch the numbers. It is to figure out which numbers are important to crunch, and what data should be left out of the equation. It is not intuitively obvious to the casual observer why a particular statistic doesn't matter, and should be excluded from consideration.

I remember back in 1998, I decided to create my own system for power ranking teams in the NFL during the season. The difficulty was in determining which statistics to measure. It took me 6 years to finally develop a system that was reasonably accurate. That only happened when I dropped all statistics from special teams, which turn out to be only marginally important, and added in penalty yardage for and against a team. Then "suddenly", I had a formula which used 12 basic statistical measures and was > 90% accurate when predicting which teams would make the playoffs. Back in the 2013 season, I was living in Denver, when the Broncos ended up playing the Seahawks in the Super Bowl. A lot of my co-workers asked me who I thought would win. Statistically, it wasn't even close. The Seahawks were far superior to the Broncos, and they proved it in the Super Bowl, much to the chagrin of my neighbors and co-workers in Denver.

I published my own Power Rankings each year on the old DC.com website from 2004 - 2017 for 14 straight years. A lot of people wanted to argue the numbers every season, but after spending 6 years from 1998 - 2003 figuring out what the right numbers to use were, my system consistently out-performed people's gut feelings. The only real glitch was I never could figure out how to incorporate special teams data. One year, the Chargers had both the #1 offense and #1 defense, and yet missed the playoffs due to atrocious special teams play - which just goes to show you that even the best system is not 100% accurate.

Bottom Line: knowing which data to use is highly important. That's why many people "don't trust the numbers." It is because they don't know how to figure out which numbers matter, and what data is irrelevant.

 

[SteveTheCowboy]

Jerry still gonna play with his favorite toy however he likes. Hey he owns it so all the power to him. Unfortunately he is an incompetent drunken clown.

You make it sound like a bad thing.
Well.....bad for us!

Can you imagine having so much money....you can just play around with The Dallas Cowboys. While drinking the very best. Hmmm....fun!