DawgTalkers.net Forums DawgTalk Pure Football Forum Analytics and its place in the NFL...

I have to preface this thread with a couple of things...

***THIS IS MEANT TO BE EDUCATIONAL ONLY***
***THIS IS NOT MEANT TO BE AN ARGUMENT PERTAINING TO THE BROWNS USE OF ANALYTICS*** btw this will be put on every post I make in this thread...lol

If you are here to argue...start your own thread. The purpose of this thread is to explain what Analytics is, in a more in depth forum than it could be in an obscure post within an obscure thread. The sense I get from posts is that Analytics is misunderstood as an entity and therefore the "use" of Analytics is misunderstood. I hope to shed some light on what Analytics actually is and then offer some hypothetical scenarios as to how it can be used in today's NFL. I need to reiterate that they are hypothetical but in my estimation it is reasonable to assume that someone in the NFL is using Analytics in the same manner. But most likely they are more advanced than I can hypothesize.

This is going to be a multi part thread/project. Massive books have been written on the subject of Analytics and I am not going to be able to fit it all into a single post...LOL So if you have questions, definitely ask...but also know that There will be further posts. In fact your questions may help steer the direction of those next posts...

Just a little about me. I have been working with computer data for 22 years. I'd like to say I have worked with 2 of the largest data sources you can find. Land/Title and Healthcare. I have created a Database Application that allowed my company to be the first in the Industry to serve the entire State of Ohio, and now serves the entire country. I have created Analytical Reports in the Clinical arena that led to process changes. In one case, the changes saved my Hospital over $500,000 a year. In most cases the reports I have written led to process changes that saved money. I currently administer reporting systems as well as monitor and support data ETL's (Extracts, Transfers, and Loads) for the top Hospital in my State.

With that said, I am not the end all, be all concerning the topic of Analytics. I am a Data, Systems, and Reporting Analyst, not a Data Scientist. But I work Daily with Data Scientists and Data Engineers in making sure our Hospital is provided the data Insights it needs to both operate today as well as prepare for the future.

I will NOT have all the answers. BUT, if I don't know, I will find out. And as most of my experiences with Analytics have been within the Healthcare field, most of my examples will lean toward in that direction. I ENTHUSIASTICALLY encourage those on this board that work in Analytics, or have worked with the results of Analytics, to post their experiences and take on roles of teachers in this thread as well.

I have to say it one more time...If you are here to argue about the Browns specific use of Analytics, please take your argument to another thread. I will ask Moderators to delete posts that do not contribute to the purpose of this thread.

With that said...Let us Begin!!!


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The purpose of Data Analytics is to provide INSIGHT to those who make decisions, with, indirectly, having the ultimate goal of improving business performance. That is a mouthful.
LOL

Insight, you will hear that word often. So lets start with the straight definition...
noun
1. an instance of apprehending the true nature of a thing, especially through intuitive understanding
2. penetrating mental vision or discernment; faculty of seeing into inner character or underlying truth.
Psychology .
an understanding of relationships that sheds light on or helps solve a problem.
(in psychotherapy) the recognition of sources of emotional difficulty.
an understanding of the motivational forces behind one's actions, thoughts, or behavior; self-knowledge.

So the aim of Data Analytics is to use data to shed light and understanding of a situation.

Analytics rely heavily on 3 things. Good Data, Good Questions, and Good People to work the data.

Good Data...
We have a term we use all the time. Garbage in, Garbage out. Quite simply if you do not have Good data as a foundation, it is impossible to expect beneficial results from processing that data.

Human error is inevitable. Nurses and Doctors may fat finger a number or name. Receptionists see someone with the same name and mistakenly use that record instead of a new one or correct one if it exists. It happens. But if a diagnosis is under the wrong patient, how can we expect to have accurate results when looking for patients with a specific diagnosis history? We take many measures to reduce this possibility. We have a team of people to correct these instances. In any case, we take great efforts to ensure that we have Good Data as a foundation of our Analytics.

Good Questions
You can have the best Data Possible and the Greatest Analytics Team on the face of the Earth. But if you don't ask the right questions, The data results are useless towards the ultimate goal of making great gains in business performance. For example, in the Hospital, this is the difference between having a Business expert and a Doctor asking the questions about saving money on the treatment of a specific infection. Both have extensive experience within their own field. But the questions they ask are going to be (for lack of a better term) biased towards that field. The business man asks questions towards the bottom line money. While the doctor asks questions towards the treatment process. Both have a piece of the question. But as they are just a part of the story, neither are asking a Good question. In order to get good INSIGHT into the situation you need to take into account both the businessman and the doctor. That question becomes very complex, very quickly. And the answers to that question are even more complex.

Good People
It takes a large number of people to produce the results needed. We have people who insure data integrity. We have people who model the data, we have people who move the data around. We have Data Scientist to create the algorithms needed to produce the answers. And we have people that support the hardware and software of all of these systems. Lastly we have Report writers who take these results and present them in a meaningful way. Anyone of these people can drop the ball, and if they do, the results are useless. So it is important to hire the right people. with the amount of data we are working with...it is not a job for just a couple people. This is not a small business Database. It is not a large business database.

To give an idea of the amount of data we work with, take this into consideration. The Library of Congress is the largest library in the world. It is one of the singular greatest collection of human knowledge on the face of the earth. The entire Library of Congress is reported to fit on approximately 10 to 20 terabytes. To go a little more granular. One bit is either a 0 or a 1. To make one character in this post requires 8 bits. 8 bits is 1 byte. 1024 bytes is 1 kilobyte. 1024 kilobytes is 1 Megabyte. 1024 Megabytes is 1 Gigabyte. And finally 1024 Gigabytes is 1 Terabyte. So if you take 1024 and raise it to the 4th power you get a number with 13 digits.(That is Trillions)Add another digit as you are multiplying again for 10-20 Terabytes in the library of Congress. That is a lot of data...So when I tell you that my hospital is performing analytics on data measured in Petabytes...You can get a better idea of the task that is being performed. What is a petabyte? A petabyte is 1024 Terabytes...so now we are at 1024 to the 5th power which is a 16 digit number (Quadrillions)

Much like a fire that relies on fuel, spark, and oxygen. If any one of the items spoken of is taken away...Analytics fails. Good Data, Good Questions, and Good People...Analytics is a three legged table and if any leg is taken away...the table falls.

I hope that is a good introduction and I hope it both gives you a little understanding of the purpose of analytics, the sheer scale of analytics, and what it relies upon to be successful. I also hope that it raise a myriad of questions within you to add to the discussion. In another post, I mentioned the different types of Analytics and how Analytics differs from Statistics. I think that will be a good stepping point into my next post.

I believe the league started sharing "tracking data" last season for players on the field. To me, one of the biggest upside in analytics is using "wearables" to create data for player improvement, and to analyze the opponent.

That is just a "drop in the bucket" in how this plays a role for NFL franchises. I read an article recently, not going to look for it - I'll paraphrase... "If your franchise has a well developed analytics dept, you're ahead of the curve... don't look back and move forward, someone's breathing down your neck. If your franchise is middle of the road, you have a tremendous amount of work to do to catch up. If you don't have this department or it is an afterthought - you're screwed".

The Brown are ahead of the curve and Dorsey understands how valuable certain data is - I'll leave it at that.

I get blown away by the sheer amount of data (in any given endeavor) and the necessary algorithms to make it as valuable as possible. And then the other side - not enough reliable data and how easy (or difficult) it is to determine value of data. A college RB who runs better on turf is much more valuable to the Browns than the Cowboys, yet extrapolating those numbers may mean a small sample size and unreliable data. If some scout falls in love with a player and the data jumps off the page, a hasty decision could be made. Placing proper value on certain data is where GMs will make their money.

Then you come to game planning and game-day play calling. I read another piece that quoted a coach talking about executing plays, late in the game, that kept the ball on the far hashmark, away from the opposing team's bench. Why? Because rotating D Linemen actually do more running on and off the field than they do between whistles... and this approach would tire them out. Crazy stuff. No morsel of data on its own will win you a championship, but paying attention to as many as possible may put you over the top.

I have an example that has nothing to do with football, but illustrates what I feel is how analytics can lead to unforeseen pitfalls.

I own a business and still shop at Sam's Club, I've shopped there less and less over the years. I got tired of the endless relocation of products so I've narrowed my list to the few things that save me the most money.

It puzzles me every time I'm shopping there that certain items are constantly shuffled around the store. It doesn't take a genius to figure it out - the more aisles you walk down, the more you're likely to buy. After a while (and a lot of aggravation), I made it a point to NEVER buy anything not on my list during each scavenger hunt. Yet, somewhere in some boardroom, there are men and women that think they are smarter than everyone else because their ticket averages have gone up. In my case they have as well. Why? Because I've moved away from Sam's trips being a "way of life" and now stock up on the items I buy even more... so I don't have to go there and play their games.

I know, I'm just one customer, but they did initiate a plan to close 10% of their stores last year. I'm sure they will blame it on Amazon and internet trade. Yet, they made it way easier for me to "shop the aisles of amazon" rather then logging ten miles walking around their stores.

Thanks ... looking forward to your next post ... appreciatte the time and effort to educate a dumb ass like me ... ty sir ...

U know what correlation and examples i’m looking for ... u know what questions i want to ask ... its not arguing but U may consider it argumentative ...

1. Can i ask my questions?

2. If so, should i wait til u get further down this road as u may answer them as u delve deeper into it?

Either way thanks and I am looking forward to your next installment ...

Well at this point we are at the very high level and I know your questions are at a level far more detailed. (It is one of the reasons I said I knew it would create a myriad of questions...LOL) There are probably more questions than answers at this point. I haven't yet started to show how the NFL might use Analytics. But I do feel some foundations need to be set. It helps with context.

I say ask your questions when you feel comfortable doing so and when you feel it fits the discussion at the time...Asking early certainly won't hurt anything...

And as I said. I am not the end all be all authority...but if I don't know I can try to find out...

I feel ya, Dawg.

Operate my own business also.

Pisses me off when some schmuck justifying his presence moves things in a Home Depot.

I know these stores better than those who work there.

I feel that analytics are used in almost all businesses. One would be foolish to not make use of analytics. I am a big fan of them and used them for years in education. I was actually asked to lead an analytics team to educate other teachers in our school district.

It's a worthwhile tool.

I’ll wait for now ... i’ll See what direction u take our education on the subject and if my questions “fit” better then ...

Sam Darnold, Teddy Bridgewater.

I'm kinda afraid to ask, but how are those two players connected and how do they fit in a thread about Analytics in the NFL?

Be afraid.

Analytics is mostly important as it pertains to the NFL in “Translation theory”. There have been many guys who tear up the collegiate level who aren’t NFL players, one close to home would be JT Barret. When you see a guy with JT’s production, it’s eye popping, the throwing TD’s, the rushing yards, the wins. Then you turn on the combine numbers, ball speed, ball accuracy “Analytical” measurements and you realize that JT Barret is a plodding running back who could throw.

I was WAY high on these guys for analytical reasons over the past few seasons. Obviously Myles Garret but TJ Watt, Denzel Ward, Marshon Lattimore (his hammy’s were made of glass in college) Joey Bosa. These guys all had the elite athleticism that you can boil down to a few categories for each position type. Example: Edge Rushing, if you don’t have an elite 3 cone, I am chalking you off my list off the top. In the 2019 draft the FOOTBALL players that have elite 3 cones, I would take a long hard look at are Devin Bush and Chase Winnovich. Two highly productive, team leaders with top 10 measurable for 3 cone, which is pivotal for edge rushing.

I’ve greatly over simplified this, there are all sorts of different score ratings these days, SPARQ etc. At the end of the day “analytics” is simply trying to see if the player with the production, has the traits that translate in the NFL. Most of the late round “Boom” guys were guys who didn’t have the elite athleticism, Antonio Brown is a perfect example. There is a reason for that, those guys 90% of the time bust out of the league.

Don't you believe that most experienced football people could see that many skill sets in the NCAA won't transfer well into the NFL? Very few people thought J.T. Barrett would make a good NFL QB.

Maybe JT was a bad example. Not really, I'm a Browns fan so, I absolutely do not believe that most experience football people can see that.

Well then Kansas City must have a great analytics staff too because Dorsey is two for two on franchise QB's.

Apparently, Jonah Williams is an "analytic's dream," or, at least, a believer in them himself.



Link

Thought this was as good a place as any for another example of how analytics might be used in football. Plus, there was a Joe Thomas reference.

"Analytics" has kind of always been a scout's tool. We just haven't always thought of it that way. What is the point of charting if not to analyze the data?

QB is still the anomaly, the measurables mean far, far less.

Thanks Grimm ... more food for thought .... this is logical ... think of me what u may but i am an extremely logical person ,,,, i appreciatte the info u provided .... thanks for that ....

What are they measuring, if they are measuring the wrong things, surely what you say is true.

Well what about, a good head coach, do the greatest HC's have measurables? What are they measuring.

Laser, Rocket, Arm...