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Vacchiano claims Giants think Kyler Murray is...

Mike in St. Louis : 2/11/2019 4:13 pm
too small...

"A team source told SNY's Ralph Vacchiano that Oklahoma QB Kyler Murray is "probably a little too small" for the Giants.

The Giants "prefer to stick to the established measurables they have for a prototypical quarterback," Vacchiano notes. The Giants' organization emphasizes conventional wisdom and inside-the-box thinking, and they haven't started a quarterback that measures below 6-feet since 5-foot-11 Gary Wood went 0-6 in 1966. And "the philosophy hasn't changed all that much (in that over half-century timeframe)," Vacchiano confirms. 6-foot-3 Dwayne Haskins, 6-foot-4 Drew Lock, and 6-foot-5 Daniel Jones appear to be likelier candidates to succeed 6-foot-4 Eli Manning than 5-foot-9 Murray."

Source: SNY.com
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RE: Ok Dan since you asked so nicely, Iím going to summarize our arguments  
Eli Wilson : 2/15/2019 8:28 am : link
In comment 14297164 NoGainDayne said:
Quote:
With some peopleís favorite game!

(To the cadence of wheel of fortune) SCALEÖTHATÖLUDDITE

Thatís right everyone, Hi, Iím Dan in the Springs and Iím the host of Scale that Luddite. Where the winner is always logic and reason and the loser eats Dave Gettlemanís farts. We have two contestants today Fat Luddite (FL) and NoGainDayne (NGD)

FL: Thanks Dan, so happy to be here. I always think I win no matter how much of a loser I am but this game is amazing for me. I just love to eat Gettleman farts, so much.

NGD: While I do love tormenting Luddites this has ended up taking a lot more of my time than I originally intended.

Dan: Good good, now onto the game! On a scale from Henry David Thoreau to Andrew Ng where do you think your opponent rates Dave Gettleman on the Luddite scale?

FL: Ted Kaczynski

Dan: BAM and we are off to the races! Wow aggressive there FL. Famous hater of technology here. Also a murderer, you really donít think NGD likes Gettleman very much do you?

NGD: Marc Benioff

Dan: Interesting. Technology visionary despite the non-technical backgrounÖ

FL: ***interrupting*** GETTLEMAN MANAGED BY SOME ACCOUNTS AS MANY AS 5 DEVELOPERS IN CAROLINA!!!

Dan: Yes, yes, we get it. You love Gettleman. Letís move on. Where do you rate Gettleman?

FL: Bob Iger, canít forget how much Gettleman loves film guys, he loves it, LOVES IT. And heís no slouch on technology. Did I mention they said at his prior job he knew game theory? You know heís hired developers, right? Perhaps youíve heard of the Sloan conference?

NGD: Julie Wainwright, Pets.com CEO. Shown far too much faith despite being late to the party and displaying no real understanding on what it takes to succeed in the tech space

Dan: I think we have our winner. Julie Wainwright is much closer. All the resources in the world but just doesnít seem to get it, the most famous example being mocking the people he needs to help him do his job better going forward and becoming the counter example to teams that embrace analytics. Do you know that one writer even pointed out the fact that the METS had the opportunity to be smarter than the Giants on this? Learn from their mistakes? Brutal, just brutal. We even reached Kaczynski for comment from ADX Florence "not a good look" he says. And thatís our game folks.

FL: Hooray!! Shower me in farts. I am literally available to play this game any time.

Dan: Sadly I fear this wonít be the last time you play.

NGD: ***slinks off a little impressed by the unrelenting support but mostly just disheartened that John Mara most likely shares FLís feelings***


Get some help man. You have a serious issue.
RE: christian hits on a key point  
arcarsenal : 2/15/2019 10:00 am : link
In comment 14297117 Go Terps said:
Quote:
Based on their game management skills, if the Giants are delving into analytics they're pretty clearly doing it wrong. The 2018 team was as poorly coached a Giants team as any I've seen from a standpoint of game management. They were completely incompetent in managing the clock, managing timeouts, managing down and distance.

They were also poor in utilizing personnel. On another thread I broke down how poorly they used Barkley as a receiver... He was not nearly as effective as his talent would indicate that he should be.

You can knock what NoGainDayne is saying, but the proof is in the pudding - there is no indication that the Giants have any awareness of analytics. And it's backed up by the words of the GM.


This supposes that utilizing analytics = success.

Not true.

The Jaguars are case in point. They're doing all of the things people here want the Giants to do with their analytics department and it led them to Blake Bortles under center yet again and a terrible, losing season. They were just as bad as we were.

This time last year, everyone was lauding them.

Things change fast in this league.
.  
arcarsenal : 2/15/2019 10:01 am : link
Also, some of these NGD posts are bizarre.

You're a strange cat, my man.
RE: My game show tie-in..  
bw in dc : 2/15/2019 10:05 am : link
In comment 14297200 FatMan in Charlotte said:
Quote:
would be much quicker.

Me :"I'll take pompous morons for $200, Alex"

Alex: "This moron once stated that Dave Gettleman shuns analytics and doesn't use them"

Me: "NoGaynDayne"

Alex: "Ohh, I'm sooory. It's that prolific moron NoGainDayne". You used a "y" instead.

Yes. Why indeed......


Uh, you are supposed to answer in question form, FatMan.
Alex..  
FatMan in Charlotte : 2/15/2019 10:26 am : link
chided me on the commercial break for that faux pas!
Lol meltdown again Luddite?  
NoGainDayne : 2/15/2019 10:53 am : link
You love to use that phrase. I donít know if you know what it means.

Somehow a meltdown consists of seemingly all the people in the know about analytics agree with me over you. And here comes the classic Luddite misdirection that youíve tried over and over again. Misncharacterizing what has happened.

If you havenít figured it out by now let me fill you in. No one should respect you because you just like to bully people that you think your are smarter then. But you are just a POS.

My game show did not involve a freak out of any kind I just enjoy making fun of Luddites as much as possible.

Iím just enjoying the world of your largely baseless Gettleman worship come crashing down on your stupid head. It seems very hard for you to accept that you donít really have much basis so Iím trying some abstract ways.

Sadly none of them work. You are never going to acknowledge that you came charging into this calling me stupid repeating the same things and never having a point to refute what Iím saying with any real basis . Now Iím pompous? I suppose Iíd prefer that to stupid like you call everyone else who disagrees with you and something youíve had to shift to as your bravado unravels.

But of course as Luddites will continue to try to pick apart things to make themselves feel better instead of accepting they have beeen wrong the whole time. You clearly canít help it, itís the code that runs on your basic OS.

Anyway Iím out of strange ways to make fun of you for now but Iím sure youíll give me more material soon.
Was NGD  
Giantology : 2/15/2019 11:04 am : link
always this batshit, or is this a recent thing?
RE: Was NGD  
arcarsenal : 2/15/2019 11:10 am : link
In comment 14297321 Giantology said:
Quote:
always this batshit, or is this a recent thing?


I don't ever remember his posts/tone being this weird.
arc thing about the analytics = success thing  
NoGainDayne : 2/15/2019 11:20 am : link
itís a long term investment that everyone is going to have to makensooner or later.

To Christianís point the data that exists for this now can predict these data systems but it doesnít mean itís easy to build them. By all accounts the Patriots have been building theirs for almost 20 years. The Eagles maybe longer.

This is a when not an if thing. And if you are just starting when basically many other teams have proven unequivocally that it works you are too late.

Did you read the article on chess centaurs I shared? Even if the Giants finally get with it and hire the right people they are still behind on the reinforcement learning data set and falling further behind even if they hired the best coders in the world they would be dealing with inferior data than those teams that have been using reinforcement learning for all this time.

Also I like that Iím weird.

Human salvation lies in the hands of the creatively maladjusted. ~ Martin Luther King
Holy shit  
figgy2989 : 2/15/2019 11:24 am : link
What did I just read?

Quote:
Did you read the article on chess centaurs I shared? Even if the Giants finally get with it and hire the right people they are still behind on the reinforcement learning data set and falling further behind even if they hired the best coders in the world they would be dealing with inferior data than those teams that have been using reinforcement learning for all this time.



Might as well stop being a Giants fan, the Pats stole all those good hackers from MIT. There is no hope for the Giants because they are behind the curve.
I'm with you NGD  
Jim in Forest Hills : 2/15/2019 11:28 am : link
I think your messaging needs work, but at it's base it makes sense. In essence, the advanced analytic models are extremely difficult and time consuming to build and demand top talent and resources to develop. Its not a guaranteed path to success (depends on how its read and utilized) but helps provide direction into the future with higher probabilities of success.

This isn't a dip your toe into the water, or hire a few guys here and there. It's a full on dept that has to really evolve with a plan and vision behind it. Doesn't look like the Giants at the surface level have attracted the top personnel or invested the time into it as the top teams have. I agree that they 100% should though.
I think NGD is having a "beautiful mind" moment  
figgy2989 : 2/15/2019 11:29 am : link
.  
arcarsenal : 2/15/2019 11:29 am : link
So, what should the Giants do? They can't go back in time 20 years and build their analytics department before every other team.

This is just part of the deal. Some teams are at the forefront, others are going to have to catch up. If the Giants are in the latter category, so be it.

Analytics in football are a very wide and far encompassing term - it can cover all sorts of areas from personnel to in-game strategy, to player health/peak-performance.

Some of you guys are attempting to make a black/white issue out of something with countless variables in a field where we're not even completely privy to everything the Giants are actually doing.

There's a lot of assumption in this debate which leads to faulty logic and incomplete comparisons.

A lot of these posts are reading more like frustrated fans than anything else, if we're being honest. It's almost like... "just do something! Anything!"

The Jags announced this big partnership with Tech Mahindra last year - they've been employing analytics since at least 2013 and still wound up with Blake Bortles playing behind a line with TWO Giants rejects and a 5 win season.

They've been no better than us in that time period.

Analytics are a great tool, and I'm sure it benefits teams to have as much data and information as possible - but we're moving into territory where this is becoming "teams that employ extensive analytics = great, everyone else = bad"

Let's not simplify it to that degree because it's doing a major disservice to the basis of the discussion. it goes FAR beyond that.
RE: RE: christian hits on a key point  
Lambuth_Special : 2/15/2019 11:36 am : link
In comment 14297240 arcarsenal said:
Quote:
The Jaguars are case in point. They're doing all of the things people here want the Giants to do with their analytics department and it led them to Blake Bortles under center yet again and a terrible, losing season. They were just as bad as we were.


I imagine about 100 percent of the league has some form of an analytics department at this point.

You are right that the mere presence of analytics doesn't add value, and that the term itself is way overused in sports and other ventures. But I do wonder, in the case of the Jaguars and other teams, about how often GMs and VPs actually listen and make decisions based on analytical recommendations. I imagine that an analytical team could pretty easily make the case not to draft Mr. 3.3 ypc Fournette in the top 5, but is someone like Coughlin going to listen to a 20-something nerd fresh out of Stanford?
RE: arc thing about the analytics = success thing  
Strahan91 : 2/15/2019 11:42 am : link
In comment 14297345 NoGainDayne said:
Quote:
itís a long term investment that everyone is going to have to makensooner or later.

To Christianís point the data that exists for this now can predict these data systems but it doesnít mean itís easy to build them. By all accounts the Patriots have been building theirs for almost 20 years. The Eagles maybe longer.

This is a when not an if thing. And if you are just starting when basically many other teams have proven unequivocally that it works you are too late.

Did you read the article on chess centaurs I shared? Even if the Giants finally get with it and hire the right people they are still behind on the reinforcement learning data set and falling further behind even if they hired the best coders in the world they would be dealing with inferior data than those teams that have been using reinforcement learning for all this time.

Also I like that Iím weird.

Human salvation lies in the hands of the creatively maladjusted. ~ Martin Luther King

You clearly have very little understanding of reinforcement learning outside of this one article you read. There's too much open-ended complexity and a lack of a good simulation environment for it to be useful in the context of an NFL game. Data sets aren't the bottleneck...
Can't change the past  
NoGainDayne : 2/15/2019 11:45 am : link
but I think the point that many people who have worked in analytics are making is that we have to start now. Starting is better than not starting.

It's a real shame that we decided to not hire a GM that didn't want to make a strong commitment to analytics but it is really as simple as hiring someone with an understanding of how to build software and strong math skills to make sure we aren't all sitting around here 5 years from now saying we should have done this 5 years ago.

McL said it, i'll say it too. I could have something that could start answering the tough questions built in a year. The easy ones like time / clock management in a few months max. I'm not even saying that we are super unique either.

There isn't really any good reason not to other than rejecting the idea that advanced analytics isn't going to change football in the way it's changing every other industry and that's really a negligent thought as a business owner.

Every business generating as much as the Giants with the kind of data that is being produced should have a strong CTO with knowledge of predictive analytics in the building.
Seeing as I'm pulled into this  
English Alaister : 2/15/2019 11:47 am : link
Iím going to take a moment to put my side over on thisÖIíve done it before but it tends to get misrepresented by others on this thread. Itís also really difficult to talk about something as wide as analytics meaningfully. Itís a broad church that covers analysis of strategy, health management, time management, talent identification, recruitment & retention and so on and so on. Each has different business cases for analytics an different maturities / complexities. Of course we all agree the Giants should be thinking analyticallyÖthatís a givenÖjust whether it is best done by maths guys, quality control coaches, scouts or some combo of the above.

Letís start with talent identification & recruitment. Here, I believe the Giants should have a capable front office analytics deptÖI think analytics is a great way of challenging preconceived notions and group think. I would absolutely use it for that. I would not use it as the primary input to decision-making. My scouts would be key. Here are my concerns with analytics in talent identificationÖIt doesnít reflect chemistry, leadership or potential well, the sample sizes are much smaller than baseball, thereís so much data you can generally torture it into confessing what you want (copyright Bill2!). I also question if thereís value in blazing the trail or being a follower. It will take a lot of costly mistakes to get the learningsÖespecially on things like machine learning that are very immature. Think about what goes into analyzing one CB on one play. Whatís his leverage? Whatís his cushion? What was the scheme calling for? How much safety help did he get? What was the quality of the throw? The down and distance> Things the human brain processes very swiftly but are actually very tricky to code for reliably and require a ton of data points to cover.

Regarding strategy, time management and health management I think the benefits are a lot clearer. The data is much more easily measured, more easily applied and should be basics but letís be honest, thereís no silver bullet to these things because no-one wants to put the maths guys in charge. Andy Reid is one of the biggest advocates for analytics in the NFL. He is also a famously bad caller of timeouts. Atlanta are huge proponents of analytics, yet Mike Smith was allowed to be the worst user of timeouts the league has arguably ever seen. Letís not cover them losing a superbowl where basically they could have knelt on every play at a certain point. ARC does a great job discussing the Jags. So I think my point here is that thereís a bunch of value in doing the work but only if you put it in to action effectively, which there is some evidence Shurmur is doing in a limited range. However, letís be honest, his timeouts were atrocious in 2018, especially the first half.

Overall then Iíd characterize my approach to analytics as someone prepared to embrace it very much in some areas and cautiously in others where there are real barriers to implementation and risks of costly learnings. If someone wants to actually lay out how we mitigate those concerns, get the bang for the buck without impacting the available time of the key guys during the season then Iím all ears. Can we just try to keep our responses to less than 3 volumes and a teeny bit sane. Thanks in advance.
This thread is a case study  
Ten Ton Hammer : 2/15/2019 12:15 pm : link
on how to argue something in a completely unlikeable fashion that drives people away from supporting your point.
RE: This thread is a case study  
arcarsenal : 2/15/2019 12:19 pm : link
In comment 14297458 Ten Ton Hammer said:
Quote:
on how to argue something in a completely unlikeable fashion that drives people away from supporting your point.


STFU, luddite.
Analytics  
RomanWH : 2/15/2019 12:27 pm : link
while useful, isn't as efficient at predictive success outcomes in football due to smaller sample sizes. Tracking QB pass attempts over the course of a 16 game schedule pales in comparison to tracking pitches from 30+ starts. Plus there are so many more variables on a given football play versus a baseball play that it is difficult sometimes to differentiate statistical fluke occurrences from true talent and ability rising to the surface. This is why we should all be supporters of the use of analytics as a supplement to the tried and trued methods of scouting talent... aka watching film.

This doesn't have to be one or the other.
RE: This thread is a case study  
NoGainDayne : 2/15/2019 12:43 pm : link
In comment 14297458 Ten Ton Hammer said:
Quote:
on how to argue something in a completely unlikeable fashion that drives people away from supporting your point.


What happens when you argue this point in 4 different threads with the same person and he keeps on acting like he has a point when he doesn't? Do you do it the same way again? Sounds like the definition of insanity. Have to try troll hunting in different ways
RE: RE: This thread is a case study  
figgy2989 : 2/15/2019 12:46 pm : link
In comment 14297530 NoGainDayne said:
Quote:
In comment 14297458 Ten Ton Hammer said:


Quote:


on how to argue something in a completely unlikeable fashion that drives people away from supporting your point.



What happens when you argue this point in 4 different threads with the same person and he keeps on acting like he has a point when he doesn't? Do you do it the same way again? Sounds like the definition of insanity. Have to try troll hunting in different ways


RE: Seeing as I'm pulled into this  
NoGainDayne : 2/15/2019 12:46 pm : link
In comment 14297409 English Alaister said:
Quote:
Iím going to take a moment to put my side over on thisÖIíve done it before but it tends to get misrepresented by others on this thread. Itís also really difficult to talk about something as wide as analytics meaningfully. Itís a broad church that covers analysis of strategy, health management, time management, talent identification, recruitment & retention and so on and so on. Each has different business cases for analytics an different maturities / complexities. Of course we all agree the Giants should be thinking analyticallyÖthatís a givenÖjust whether it is best done by maths guys, quality control coaches, scouts or some combo of the above.

Letís start with talent identification & recruitment. Here, I believe the Giants should have a capable front office analytics deptÖI think analytics is a great way of challenging preconceived notions and group think. I would absolutely use it for that. I would not use it as the primary input to decision-making. My scouts would be key. Here are my concerns with analytics in talent identificationÖIt doesnít reflect chemistry, leadership or potential well, the sample sizes are much smaller than baseball, thereís so much data you can generally torture it into confessing what you want (copyright Bill2!). I also question if thereís value in blazing the trail or being a follower. It will take a lot of costly mistakes to get the learningsÖespecially on things like machine learning that are very immature. Think about what goes into analyzing one CB on one play. Whatís his leverage? Whatís his cushion? What was the scheme calling for? How much safety help did he get? What was the quality of the throw? The down and distance> Things the human brain processes very swiftly but are actually very tricky to code for reliably and require a ton of data points to cover.

Regarding strategy, time management and health management I think the benefits are a lot clearer. The data is much more easily measured, more easily applied and should be basics but letís be honest, thereís no silver bullet to these things because no-one wants to put the maths guys in charge. Andy Reid is one of the biggest advocates for analytics in the NFL. He is also a famously bad caller of timeouts. Atlanta are huge proponents of analytics, yet Mike Smith was allowed to be the worst user of timeouts the league has arguably ever seen. Letís not cover them losing a superbowl where basically they could have knelt on every play at a certain point. ARC does a great job discussing the Jags. So I think my point here is that thereís a bunch of value in doing the work but only if you put it in to action effectively, which there is some evidence Shurmur is doing in a limited range. However, letís be honest, his timeouts were atrocious in 2018, especially the first half.

Overall then Iíd characterize my approach to analytics as someone prepared to embrace it very much in some areas and cautiously in others where there are real barriers to implementation and risks of costly learnings. If someone wants to actually lay out how we mitigate those concerns, get the bang for the buck without impacting the available time of the key guys during the season then Iím all ears. Can we just try to keep our responses to less than 3 volumes and a teeny bit sane. Thanks in advance.


Thanks for this. I'm more than happy to have a measured discussion on it. Think we got off on the wrong foot when more than a few people called me stupid for suggesting it was possible for the Giants to do better with this. I will definitely have a response for you soon. For my part I apologize for being too nasty about this on other threads.
RE: RE: arc thing about the analytics = success thing  
NoGainDayne : 2/15/2019 1:23 pm : link
In comment 14297387 Strahan91 said:
Quote:
In comment 14297345 NoGainDayne said:


Quote:


itís a long term investment that everyone is going to have to makensooner or later.

To Christianís point the data that exists for this now can predict these data systems but it doesnít mean itís easy to build them. By all accounts the Patriots have been building theirs for almost 20 years. The Eagles maybe longer.

This is a when not an if thing. And if you are just starting when basically many other teams have proven unequivocally that it works you are too late.

Did you read the article on chess centaurs I shared? Even if the Giants finally get with it and hire the right people they are still behind on the reinforcement learning data set and falling further behind even if they hired the best coders in the world they would be dealing with inferior data than those teams that have been using reinforcement learning for all this time.

Also I like that Iím weird.

Human salvation lies in the hands of the creatively maladjusted. ~ Martin Luther King


You clearly have very little understanding of reinforcement learning outside of this one article you read. There's too much open-ended complexity and a lack of a good simulation environment for it to be useful in the context of an NFL game. Data sets aren't the bottleneck...


Ummmm. I've been talking about needing to set up a good learning environment with good outcome analysis. The more time you have to train the agents and add to their complexity the better they will be.

And i'm not sure what you are talking about with lack of a good simulation environment? You can run simulations of past games. Feed in Zebra data, build an autoencoder like the Patriots have to deepen the longitude of training set with film. (among many other traditional data sets that you'd expect) So you have even 2 different data trees, film models, your Zebra + film vs. pure film models and you can also compare them against the human agent outcomes. Especially with the autoencoders built from film you build a pretty deep set to find the play calling agents which maximize win total and ultimately Superbowl victories. You can even build in structures to let them manage the cap / resource allocation (by creating a database of graded contracts $/performance) in the off-season in their pursuit of calling more successful plays maybe you want to separate them into funnels, probably you'd try both though. Ideally like in the article I shared you start showing the human "players" the recommendations and seeing what they decide on with that information, that's the holy grail data set that I am advocating we get to as soon as possible.

I also strongly believe that the best probabilistic models are built on top of the metadata on simulations from the reinforcement learning agents, as well as unsupervised and supervised methodologies if we are getting greedy. These goal state optomizers can even feed into larger goal state optimizations. The success outcome and resource allocation could feed into fan sentiment and pricing strategy to feed into profit.

I actually have filed two patents and am about to get my third jointly with a large university with a prominent professor in one of the top applied math schools in the world. The new one is on mass signal interpretation and model verification. The ones we've filed, one of them is for an original approach to multi-agent frameworks and goal state orientation and the earlier one for automated feature engineering, hyper-parameter tuning and an evolving neural network feedback loop. We published on ENNs two years before Sentient wrote about them.

RE: RE: RE: This thread is a case study  
NoGainDayne : 2/15/2019 1:26 pm : link
In comment 14297534 figgy2989 said:
Quote:
In comment 14297530 NoGainDayne said:


Quote:


In comment 14297458 Ten Ton Hammer said:


Quote:


on how to argue something in a completely unlikeable fashion that drives people away from supporting your point.



What happens when you argue this point in 4 different threads with the same person and he keeps on acting like he has a point when he doesn't? Do you do it the same way again? Sounds like the definition of insanity. Have to try troll hunting in different ways





Here is the difference between some of the people arguing my side (that the Giants need to improve their tech commitment yesterday) and the luddites. The luddites are arguing with very limited facts and information supporting their side to needlessly defend a regime that is already in place. The Giants are already doing this with their support or not.

The other side would like to see change in the organization that could really do a lot to help us field more competitive teams going forward and it would certainly help if more fans acknowledged this was a problem instead of pretending it wasn't.
RE: John Mara is no dope  
Gatorade Dunk : 2/15/2019 2:08 pm : link
In comment 14296998 mrvax said:
Quote:
and one of his top priorities is for his team to make as much $ as possible. I'd think he'd be well up on the teams and their use of analytics.

Owners talk to each other. I'd also think by now he isn't going to forgo a tool that is very likely to give his team an advantage.

They DO use analytics, at least nominally. The issue, IMO, is whether they know what questions they're using analytics to answer, and whether they're dedicating enough resources to do so effectively. We'll probably never know about the former - that's proprietary after all - but to the degree that org charts are even semi-public, the Giants' analytics team does seem a bit thin on headcount.
RE: RE: RE: RE: This thread is a case study  
dorgan : 2/15/2019 2:09 pm : link

Quote:


The other side would like to see change in the organization that could really do a lot to help us field more competitive teams going forward and it would certainly help if more fans acknowledged this was a problem instead of pretending it wasn't.



How will fans acknowledging this issue help?
RE: RE: RE: RE: RE: This thread is a case study  
NoGainDayne : 2/15/2019 2:18 pm : link
In comment 14297626 dorgan said:
Quote:



Quote:




The other side would like to see change in the organization that could really do a lot to help us field more competitive teams going forward and it would certainly help if more fans acknowledged this was a problem instead of pretending it wasn't.




How will fans acknowledging this issue help?


The Mara's certainly have a pulse on the fans, it's important to them. The more that it becomes accepted around the fan base that this is something that needs to be addressed the more they hear about it (as a pure theoretical numbers game) the higher their headline risk of not addressing it and the higher chance they will.

Again even if they just bring in a strong CTO type that is in the draft war room, interjecting about what the models are saying, has a real voice. That's the start.

The early value a strong predictive analytics program isn't even answering the tough questions, it's interjecting a different perspective that might re-frame debates. When the debates are re-framed and the shortcomings of the models called out, you figure out what people are seeing that the models aren't find a way to encode that information and it becomes a virtuous cycle of improvement.
RE: RE: Seeing as I'm pulled into this  
Dan in the Springs : 2/15/2019 2:24 pm : link
In comment 14297536 NoGainDayne said:
Quote:
Think we got off on the wrong foot when more than a few people called me stupid for suggesting it was possible for the Giants to do better with this. I will definitely have a response for you soon. For my part I apologize for being too nasty about this on other threads.


The problem you've run into multiple times is NOT what you suggest here. Many people (including myself) can agree that perhaps the Giants can do better in analytics.

The problem is that you have made assertions to the positive about the level of analytics the Giants have made as though you actually know it. You've used "evidence" that includes a single line stated and possibly taken out of context from a press conference, what you could find on Google, what sportswriters say, and what people's LinkedIn profiles say about them (not even their actual resumes).

You have stated that this is ample evidence to support your conclusions. Many people disagree with you on whether that is ample or evidence.

To further complicate your situation, you've taken to labeling those who disagree with you as luddites, which is an absolute mischaracterization of their viewpoints and arguments.

RE: Seeing as I'm pulled into this  
.McL. : 2/15/2019 2:28 pm : link
In comment 14297409 English Alaister said:
Quote:
Iím going to take a moment to put my side over on thisÖIíve done it before but it tends to get misrepresented by others on this thread. Itís also really difficult to talk about something as wide as analytics meaningfully. Itís a broad church that covers analysis of strategy, health management, time management, talent identification, recruitment & retention and so on and so on. Each has different business cases for analytics an different maturities / complexities. Of course we all agree the Giants should be thinking analyticallyÖthatís a givenÖjust whether it is best done by maths guys, quality control coaches, scouts or some combo of the above.

Letís start with talent identification & recruitment. Here, I believe the Giants should have a capable front office analytics deptÖI think analytics is a great way of challenging preconceived notions and group think. I would absolutely use it for that. I would not use it as the primary input to decision-making. My scouts would be key. Here are my concerns with analytics in talent identificationÖIt doesnít reflect chemistry, leadership or potential well, the sample sizes are much smaller than baseball, thereís so much data you can generally torture it into confessing what you want (copyright Bill2!). I also question if thereís value in blazing the trail or being a follower. It will take a lot of costly mistakes to get the learningsÖespecially on things like machine learning that are very immature. Think about what goes into analyzing one CB on one play. Whatís his leverage? Whatís his cushion? What was the scheme calling for? How much safety help did he get? What was the quality of the throw? The down and distance> Things the human brain processes very swiftly but are actually very tricky to code for reliably and require a ton of data points to cover.

Regarding strategy, time management and health management I think the benefits are a lot clearer. The data is much more easily measured, more easily applied and should be basics but letís be honest, thereís no silver bullet to these things because no-one wants to put the maths guys in charge. Andy Reid is one of the biggest advocates for analytics in the NFL. He is also a famously bad caller of timeouts. Atlanta are huge proponents of analytics, yet Mike Smith was allowed to be the worst user of timeouts the league has arguably ever seen. Letís not cover them losing a superbowl where basically they could have knelt on every play at a certain point. ARC does a great job discussing the Jags. So I think my point here is that thereís a bunch of value in doing the work but only if you put it in to action effectively, which there is some evidence Shurmur is doing in a limited range. However, letís be honest, his timeouts were atrocious in 2018, especially the first half.

Overall then Iíd characterize my approach to analytics as someone prepared to embrace it very much in some areas and cautiously in others where there are real barriers to implementation and risks of costly learnings. If someone wants to actually lay out how we mitigate those concerns, get the bang for the buck without impacting the available time of the key guys during the season then Iím all ears. Can we just try to keep our responses to less than 3 volumes and a teeny bit sane. Thanks in advance.


Generally speaking I agree with thispoint of view.

I will point out that Machine Learning is by no means immature. I was involved with machine learning techniques and algorithms back in the 80s. From a computer science perspective, the techniques and algorithms are quite mature. It has only come to the current forefront in the past decade or so because we now have the computing power to make those algorithms worthwhile.

That said, the dichotomy you draw between player health/peak performance& game management (the easier stuff) vs. player evaluation & recruitment (the harder stuff) is accurate. For sure get the easy stuff going first, that's table stakes. The thing about the harder stuff though is that the benefits are not always obvious. The benefits are about helping to make higher percentage decisions. No decision, no matter how much data reinforces it is 100% guaranteed to work.

I don't know if the decision to draft Bortles was driven by any analytics or just desperation to get a QB. And if there were analytics behind, were the right variable being analyzed? No idea. Even if there were analytics on the right variables, you only get an indicator that says you have an (x)% better chance of building a superbowl contender with this pick. The pick can still go wrong. Frankly, I don't see an analytics based approach that would lead to the Bortles pick, I think there was enough in the data to steer away from that one, but what do I know.

Using one failure to discredit an analytics approach is incorrect thinking about it. Any tool that helps you to make the higher percentage decisions is a good tool. Not using a tool that improves your decision making is straight up a bad thing.

Given the revenues of a football team, the cost of building up a decent analytics department is table scraps... There is no reason not to do it. And the sooner you start, the sooner you start building up Intellectual Property on what works and what doesn't. That IP can take years to build up, and the longer you wait, the harder it is to catch up. Other teams are not going to share their IP, the IP is not doing to land in the public domain since it is so highly specialized. It comes down to a black and white decision, only limited use of analytics for the easy stuff and reject it for the harder stuff, or jump in with both feet and do both.

What fans say the Giants reject analytics, what they are really saying is that the Giants are rejecting analytics for the harder stuff. Everybody is doing the easy stuff, so that gets discounted. Fans who are critical of the Giants decision making and know something about computer science and data analysis are frustrated because we know their is a tool out there that can help with those decisions, and that tool is being rejected for specifically those decisions.
RE: RE: RE: Seeing as I'm pulled into this  
.McL. : 2/15/2019 2:40 pm : link
In comment 14297643 Dan in the Springs said:
Quote:
In comment 14297536 NoGainDayne said:


Quote:


Think we got off on the wrong foot when more than a few people called me stupid for suggesting it was possible for the Giants to do better with this. I will definitely have a response for you soon. For my part I apologize for being too nasty about this on other threads.



The problem you've run into multiple times is NOT what you suggest here. Many people (including myself) can agree that perhaps the Giants can do better in analytics.

The problem is that you have made assertions to the positive about the level of analytics the Giants have made as though you actually know it. You've used "evidence" that includes a single line stated and possibly taken out of context from a press conference, what you could find on Google, what sportswriters say, and what people's LinkedIn profiles say about them (not even their actual resumes).

You have stated that this is ample evidence to support your conclusions. Many people disagree with you on whether that is ample or evidence.

To further complicate your situation, you've taken to labeling those who disagree with you as luddites, which is an absolute mischaracterization of their viewpoints and arguments.

No there is much more evidence as to what the Giants are using analytics for. THere are articles where the team has said they use it for peak performance and health management. I think it is safe to assume that they use it from some in game management like when to go for it on 4th or when to go for 2...

Teams that are using it for player evaluation and talent acquisition have much larger departments than the Giants have. All the evidence out there shows that the Giants have 1 guy who has a specialty in the health industry doing their analytics (which goes in line with the fact they use analytics for health and peak performance). When researching other teams, its easy to find out that they have larger departments although the size is not readily available it is referred to as "teams" of computer professionals. And the leaders of these teams have strong backgrounds in field such as computer science, machine learning, big data, statistical analysis and often investment analysis. The Giants have none of that. Without such skills it would be impossible for the team to delve into the player evaluation & talent acquisition side of analytics.
Well I was really only calling one or two people luddites  
NoGainDayne : 2/15/2019 2:40 pm : link
also I think to boil it down to just LinkedIn and google search is losing the most important piece of information.

The on field results have been poor. And there has been zero change in our analytics personnel so it is hard to argue the competence of our staff on that note.

Regardless, the timeout and time management blunders in conjunction with the evidence we found is what makes some of us believe it's a strong argument.

You can post articles about Gettleman understanding advanced game theory as much as you want but when we fail to see simple game theory applied in the games we watch it certainly makes the argument that we aren't committing enough or the right resources stronger than the converse.

When the results on the field are so poor it is incredibly irritating for people to ignore this other evidence. Even the Jags their fan base can say that there is a commitment towards building technology for the future even if the results aren't there now.

Do you really think it is too much to ask for either good performance on the field or a clear commitment to evolving the approach in a rapidly changing tech environment?

Honestly my fear is that they fix the simple game theory stuff this season and never address the team construction things and we find ourselves badly behind on that because voices that are so loud now without any evidence on the low hanging fruit that shows we have the right tech people.

I guess my last question is why is it such a problem to want a company in 2019 that makes billions to have a plan as it relates to technology with more visibility? Why do the people suggesting this deserve ire?

That's what I've been reacting to, my increasing frustration that those of us that want this need to be called stupid or lambasted generally.
RE: Well I was really only calling one or two people luddites  
Dan in the Springs : 2/15/2019 3:56 pm : link
There's a lot of assumptions made here. I'll address them one at a time.

NoGainDayne said:
Quote:
also I think to boil it down to just LinkedIn and google search is losing the most important piece of information.

The biggest thing that we've gone round and round about relates to determining the disposition of the Giants towards analytics. An assertion has been made that they are NOT supportive of analytics. Over time it appears that assertion has softened, but I think what remains is an attitude of certainty about how the Giants are currently approaching the use of data in all of their football operations.


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The on field results have been poor. And there has been zero change in our analytics personnel so it is hard to argue the competence of our staff on that note.


For someone like me it is puzzling how you can say with certainty that there has been zero change. First of all, it is most likely (imo) that the Giants recognized their limitations in this area and determined (as has been their M.O. in the past) to contract OUTSIDE the organization with people who are best qualified to help.

How would any of us possibly know if they are using the same or different people/methods than they were in years past? It seems really out there to suggest WITH CERTAINTY that zero changes have been made.

Furthermore, the analysis of abilities based on LinkedIn seems ludicrous to me. If you checked my LinkedIn profile you would see NOTHING that I've been working on for the past 6-8 years. My skills have completely evolved and yet I prefer NOT to update my resume or profile. Why? I already have the job I want.

While it may be very likely that those named by the Giants as overseeing analytics are not skilled enough to start up and run an intensive analytics department, it is very possible that the skills needed by the front office in terms of understanding the findings/analysis of said department and communicating it well to those who make decisions. Truth be told, a skill that is highly prized (and needed) is the ability to tactfully navigate between those who do deep analytical work and those who execute in operations. There seems to be ample evidence that not all people who are at the forefront of this technology are excellent diplomats in relating to those who run a football team.

Quote:
Regardless, the timeout and time management blunders in conjunction with the evidence we found is what makes some of us believe it's a strong argument.

You can post articles about Gettleman understanding advanced game theory as much as you want but when we fail to see simple game theory applied in the games we watch it certainly makes the argument that we aren't committing enough or the right resources stronger than the converse.


You are correct that poor results are strong evidence that things are working, but off the mark (imo) to use such an incredibly small sample set to come to that conclusion. IMO newly hired football leaders need time to reverse course when it comes to how the team performs. It is very possible that DG and all the front office is unhappy with PS's performance and that if it continues, there will be a change. Isn't that just as likely a conclusion as one that suggests the Giants have no ability to use game theory to develop strategies in such simple situations?


Quote:
When the results on the field are so poor it is incredibly irritating for people to ignore this other evidence. Even the Jags their fan base can say that there is a commitment towards building technology for the future even if the results aren't there now.

Do you really think it is too much to ask for either good performance on the field or a clear commitment to evolving the approach in a rapidly changing tech environment?

Honestly my fear is that they fix the simple game theory stuff this season and never address the team construction things and we find ourselves badly behind on that because voices that are so loud now without any evidence on the low hanging fruit that shows we have the right tech people.

It's one thing to be frustrated with results (we all are) or to have a fear of something. I think most Giants fans have similar if not identical fears. It's entirely another to draw conclusions about cause and promote them as proven based on evidence when that evidence is not clear to everyone.

Heck, if you took the approach from the start that all of your assertions were your opinion instead of presenting them as evidence-backed facts, I never would have involved myself in these discussions. I am not in a position to argue against analytics, nor am I in a position to provide evidence to support any claims about the level of investment the Giants have. I am super-curious about it though, so I took the time to read through a HUGE thread where you claimed to have left ample evidence and didn't find anything that rose to the level I would allow a HS student to use to back a claim.


Quote:
I guess my last question is why is it such a problem to want a company in 2019 that makes billions to have a plan as it relates to technology with more visibility? Why do the people suggesting this deserve ire?


It's not a problem to want the Giants to have a plan for tech. Not sure I agree that it should have a high-level of visibility. Maybe because I'm not trying to make a living in that field?

I don't think anyone who wants this deserves ire either.


Quote:
That's what I've been reacting to, my increasing frustration that those of us that want this need to be called stupid or lambasted generally.


This is why I asked you yesterday to focus on FMiC's main point - it seems you look beyond the idea that what is evidence enough for you is NOT evidence enough for everyone else, and instead turn this into something it hasn't been - an argument for or against analytics.
yeoman's work  
dorgan : 2/15/2019 4:21 pm : link
there, Dan.

Well done.
Ok a few quick things but i'm more focused on responding to  
NoGainDayne : 2/15/2019 4:28 pm : link
English Alastair.

1) I think this is just where we believe different things. For me not having a strong technology leader, having a leader speak out against analytics, your "rising star" not having advanced math or software experience (and yes people can learn things but it's definitely pretty hard in a full time job and Sean Harrington for example probably had what looks to be 7 years of computer science and software engineering work head start on Ty Siam), poor applied game theory demonstration, advocating secrecy (I've explained on this thread why this is a backwards way of thinking), other teams having good press and public leadership embracing analytics. That to me constitutes a negligent attitude a non-supportive attitude in general of the types of inroads you need to make compete in a large and quickly changing technological industry. We just disagree on this, I feel others with knowledge of analytics other than you agree with me but I don't think this position should have ever been called stupid.

2) I just really disagree that you should have time to get the timeout thing right. I think Christian spoke very well on this above. Not hard to hire someone whose job it is to talk to Shurmur about these probabilities. The Eagles clearly do it for much more complex things. Fact is the talent in New York is wildly better than Philly or many other cities to this should be even less of an excuse.

3) When I said zero change I meant zero public change. We've outlined the merits of having internal vs. external people and I think the points I made about needing to build our own data sets are extremely salient. If you hire outside talent you not only essentially making the intellectual capital of your team available to others for purchase but you run the risk of being extorted for money or sent back to the stone age.

4) I think your burden of proof is unrealistically high and while we are throwing insults like HS student around. There were more than a few people who appreciated the evidence and research I put into that post. If you are so confident that what you are doing is better you aren't afraid to put out old stuff to pull in talent. Every successful tech enterprise does this including the Patriots. Nobody is asking the Giants to put their code in a public git. If you aren't talking it is way, way more likely that you don't have anything to talk about or people want to research than you are ahead of the curve. Not wanting to talk about what you do screams of a fear that you might have only had "one good idea" people invest in you, people hire you, etc. if they believe you have had ideas that other people don't and will continue to do so.
As you have stated you don't make a living in this field  
.McL. : 2/15/2019 4:29 pm : link
Those of us who do know hoe to recognize the footprint left behind if deeper analytical/tech methods were at work.

Not only do the folks in the software development and tech industry look at linked in. There are other places that probably carry more weight. For example, I have found the GitHub repositories of various people working on analytics for other teams. GitHub is a place where people can manage their source code. Things that are not protected IP can made publicly available. Companies today will often look to an individual's GitHub repo for evidence of their prowess with a specific tech or sub field. Furthermore they look for a continuous history, not just recent updates, so not keeping GitHub up to date really hurts candidates unlike LinkedIn. On GitHub people may not say exactly what they are working on, but they will usually say for whom they are working. Contractors will name the client company. There is nobody that I can find that has a GitHub repo that mentions the Giants. There are literally hundreds of mentions of other teams. Its easy to find people who've worked for the Patriots, Browns, Panthers, Eagles and Chiefs. In fact, the vast majority of teams can be found referenced in GitHub... The only mention of Giants is the SF Giants, not the NY Giants.

If there were contractors doing this sort of thing for the Giants, reporters would ferret it out. Perhaps not the details, but that it does exist.

Furthermore, the idea of using contractors or outside experts for anything involving true IP is a very BAD idea. No team would want the knowledge gained by working on their proprietary models to be taken to another team. Any agency worth their salt would market this expertise to other teams if they had it. SO I believe that it is highly unlikely that ANY team will outsource any of their models, algorithms or data analysis.
My post above was in reference to this in Dan's Post  
.McL. : 2/15/2019 4:33 pm : link
Quote:

For someone like me it is puzzling how you can say with certainty that there has been zero change. First of all, it is most likely (imo) that the Giants recognized their limitations in this area and determined (as has been their M.O. in the past) to contract OUTSIDE the organization with people who are best qualified to help.

How would any of us possibly know if they are using the same or different people/methods than they were in years past? It seems really out there to suggest WITH CERTAINTY that zero changes have been made.

Furthermore, the analysis of abilities based on LinkedIn seems ludicrous to me. If you checked my LinkedIn profile you would see NOTHING that I've been working on for the past 6-8 years. My skills have completely evolved and yet I prefer NOT to update my resume or profile. Why? I already have the job I want.

While it may be very likely that those named by the Giants as overseeing analytics are not skilled enough to start up and run an intensive analytics department, it is very possible that the skills needed by the front office in terms of understanding the findings/analysis of said department and communicating it well to those who make decisions. Truth be told, a skill that is highly prized (and needed) is the ability to tactfully navigate between those who do deep analytical work and those who execute in operations. There seems to be ample evidence that not all people who are at the forefront of this technology are excellent diplomats in relating to those who run a football team.
This is also what is a little disturbing to me here  
NoGainDayne : 2/15/2019 4:47 pm : link
there seems to be like all this cheer leading on the side of the people battling those of us that are suggesting that our knowledge of the field allows us to see some things that perhaps others wouldn't. And maybe have a valuable knowledge base in this?

Dorgan - you are in the coaching field if I remember correctly yes? I would think you have a deep connection to the traditions. Understandable. And there seems to be a bunch of pitchforks out with people being like. We want proof, proof! But not much evidence supporting your cause other than pointing out that we might not know the absolute complete picture about what is going on behind closed doors.

Instead of fighting us might it be nice that we all agree that it would be nice to get these answers from the team? I don't think people are grasping that I would be very happy to be wrong here, if there was a secret skunksworks of ex google engineers working in the basement. It's just very unlikely and hardly a reason to assume that maybe it is time that fans agree that this is addressed publicly in some way. I just think it is very very hard to hide that stuff. How do you keep those interviews quiet? Are these people not allowed to leave the building? Talk to their friends?

It seems like many would really just prefer to see a world that we are in good hands despite our franchise looking objectively pretty bad right now.
I know all about GitHub...  
Dan in the Springs : 2/15/2019 5:16 pm : link
just this morning I was teaching students to use it to build their first servers. Granted I don't get deep into machine learning with them at all, nor do I on the side.

I do have many years experience working with technical contractors. Among other things, I was a project manager for a large U.S. bank (the largest in the U.S. at the time) on a major technical initiative which won me a major company award (awarded once a year to a single employee out of >120,000). I know about what gets shared publicly and how to create contracts (and often more importantly relationships) that ensure silence. The supposition reporters can and will ferret out the truth is acceptable to me, given enough time and interest in the topic. I expect that some day the truth will be revealed and it may prove to be very embarrassing for the Giants. To this point however, reporters have been shooting blanks at the topic.

I will say that the comments on your findings on GitHub are very, very interesting (far more interesting than what was presented earlier as ample evidence) and significantly strengthen the claims made, but still (imo) cannot be considered conclusive.

There is evidence that has been presented before (which I am unwilling to research again) that contract work is being done for NFL franchises. I believe that is far more likely than the alternative narrative - that the Giants eschew any tech advantages and are stuck in the realm of spreadsheets and the like.

Bottom line is this: The arguments I've made both past and present relate to how much evidence is necessary for one to make significant claims. I see no point or need to debate it further. If you are hurt by how people react to you may I suggest you temper your assertions in the future by stating your opinions less as fact and more as insights, as qualified as they may be.

Peace to you - may the Giants figure this thing out so we can start winning championships again.
I'm not hurt  
NoGainDayne : 2/15/2019 5:20 pm : link
I was just saying I would have reserved the comment about your ideas not likely being that good if you were afraid to share them until I heard that from you.

I do value civility when it is afforded to me.
RE: I know all about GitHub...  
.McL. : 2/15/2019 5:56 pm : link
In comment 14297786 Dan in the Springs said:
Quote:

Bottom line is this: The arguments I've made both past and present relate to how much evidence is necessary for one to make significant claims. I see no point or need to debate it further. If you are hurt by how people react to you may I suggest you temper your assertions in the future by stating your opinions less as fact and more as insights, as qualified as they may be.

I have certainly never complained, nor do I feel hurt, about how anybody has treated me on this particular subject. Neither have I stated unequivocally that the Giants eschew analytics. Quite the contrary, it is my opinion that they do use them but in a limited capacity. We also know that every team buys data, that is certainly worthwhile outsourcing. No need to collect that data yourself when it can be bought for cheaper. However, no team in the league is going to want their proprietary models escaping, those will be closely guarded in house just like every investment company guards theirs. Outside contractors get nowhere near that IP. As those models mature, teams will realize that they need specialized data points to further their predictive capabilities. This will likely be data that is not readily available and will have to be gathered by the team. Again, this is not an activity that the team would want to be outsourced. They don't want other teams to know what data points they deem important.

Given that you work generally in tech for the financial industry, these should be concepts with which you are familiar.

The fact that the team's list of employees (which is public information, though not everybody's function is public) does not include anybody with an appropriate background is pretty strong evidence in my opinion. FYI, in another thread a few weeks ago, I and a few others went through the list of employees that had no clear function (only about 10 or so people) and searched out their work history (most turned out to be secretaries, some no info was available).
...  
christian : 2/15/2019 8:06 pm : link
I have a different, outside, and hopefully more tempered perspective having built a number of programs and having a pretty decent network of connections directly in the industry.

I have never once in the engineering, program, product, or applied science level ever heard of or known anyone who has worked on a project for the New York Giants. The Giants have never presented at or showcased to an industry group I've been associated with, and have never been mentioned in any peer reviewed or referenced study. I've never known anyone recruited to or approached by an agency or vendor associated with the Giants.

Of course that's not to say they don't have a solid team. Being a huge Giants fan and knowing literally thousands of people in the industry and having hired teams and vetted many agencies in the field, I suspect I would have heard something. Maybe not.

But again, even if the Giants have a team of a hundred people, they suck at the basics.
RE: ...  
.McL. : 2/15/2019 8:10 pm : link
In comment 14297872 christian said:
Quote:
I have a different, outside, and hopefully more tempered perspective having built a number of programs and having a pretty decent network of connections directly in the industry.

I have never once in the engineering, program, product, or applied science level ever heard of or known anyone who has worked on a project for the New York Giants. The Giants have never presented at or showcased to an industry group I've been associated with, and have never been mentioned in any peer reviewed or referenced study. I've never known anyone recruited to or approached by an agency or vendor associated with the Giants.

Of course that's not to say they don't have a solid team. Being a huge Giants fan and knowing literally thousands of people in the industry and having hired teams and vetted many agencies in the field, I suspect I would have heard something. Maybe not.

But again, even if the Giants have a team of a hundred people, they suck at the basics.

+1
LOL
Wow..  
FatMan in Charlotte : 2/15/2019 10:28 pm : link
Quote:
What happens when you argue this point in 4 different threads with the same person and he keeps on acting like he has a point when he doesn't? Do you do it the same way again? Sounds like the definition of insanity. Have to try troll hunting in different ways


C'mon man. It still hasn't sunk in over 4 threads what my point was, has it? My point was very simple.

Gettleman doesn't shun analytics and implemented the department in Carolina. Full Stop.

It is why McL brings value to these discussions - he's not arguing that point. He's not being an ignorant cock.

He's claiming that the Giants may not be on the cutting edge of analytics, or which I don't think anyone is denying.

Let me say this very plainly since you think I speak in platitudes. Gettleman doesn't shun analytics and implemented a system in Carolina. Both points of which you claimed weren't true. That's it. I have not argued any other point on any of those 4 threads.

And your response? Numerous references to Luddites and eating farts. Spectacularly moronic.
I needed a luddite free weekend but let's review something  
NoGainDayne : 2/19/2019 1:28 pm : link
My evidence:

- Gettleman literally mocking the value of analytics publicly on a decision where it could really help

- The lack of presence of really any of the skills needed to build advanced analytical models in house

- No press on the Giants commitment or efficacy in analytics in the press and much more of this information on many other teams

- Most importantly the lack of seeing simple applied game theory on the field for the Giants (which is what brought me to speaking about this in the first place)

Your evidence

- One article which the above points really call into question

I started talking about farts and making fun of you in extreme ways because you have this seemingly steadfast loyalty to DG and the Giants despite very little evidence supporting your points.

What's more, you started calling me stupid assuming I didn't have any basis for my points before you even dug into my reasoning. You make fun of me for listing my credentials but a lot of that came out of you suggesting how could I possibly understand things that the GIANTS don't.

You get on me for jumping to conclusions but it is you who came at me with a lot of vigor and your bullying tendencies and I reacted by treating you with the same level of respect, somehow that makes me "pompous" and an asshole, funny coming form you a notorious asshole who just assumed I was coming at this uninformed when I was very informed and have read about this for years including the article you've harped on time and time again.

I never contested whether or not he hired engineers or went to the sloan conference, I contested that DG or the Giants have the kind of people that actually understand what it is possible with analytics and how to identify and bring in the RIGHT people to build these systems.

I like Christian's line about them potentially having vans of PhD's in the parking lot and still getting easy table stakes analytics / game theory things wrong. You can quote that article a billion times about Gettleman using advanced game theory but it isn't unreasonable for fans like me that understand game theory to say it doesn't matter what that article says.

There isn't proof but there is just a lot more evidence that Gettleman doesn't understand the capabilities or how to use / integrate analytics properly than he does.

I think there is an apples & oragnes thing here  
.McL. : 2/19/2019 6:46 pm : link
NGD, do you consider what Ty Siam is doing regarding player health/peak performance to be applied analytics?

I can understand a position where one could say "no that is not what I mean by applied analytics". I can understand saying that is health management and is separate.

My guess is that for you, that is not considered to be applied analytics. correct?

One thing I might add, the process the Giants have regarding health management/peak performance started under Coughlin, somewhere around 2008. So Gettleman would have been here at the time, and probably saw some value in it. When he got to Carolina, I am guessing he instituted something similar.


McL  
I think this is one of the key things. Analytics is many things. Ty Siam may be well qualified to handle and process physiological data but less/not at all qualified to deal with a hugely complex talent evaluation model.

What I'd say about this is I have interacted with Deloitte or other top tier consultants most days for the past 20 years. I've managed serious spend on these guys (tens of millions a year for top investment banks and commodity companies). As with any industry, there's a huge variety amongst the resource pool from moderately capable in a narrow range to absolute rock stars. It is really difficult to spot the latter just from the CVs but what I find is those good ones are highly versatile, learn new skills incredibly quickly and hugely motivated to deliver.

Let's be clear though that no-one becomes an analytics expert overnight and for sure we need to be clear that machine learning, mathematical modelling or AI skills are very different and rare skills that I agree the Giants don't seem to have in house.

So should they? In the medium term I think so. Absolutely. Was it the most pressing problem Gettleman faced? Nope. He had to overhaul the scouting dept and coaching staff, get on the same page as his coach and fix a uniquely flawed strategy of fielding a statue QB with a terrible offensive line. So I can't fault DG for prioritizing.

In his shoes I would have kept analytics firmly on the back burner and done the basics (physiological data etc) and parked the hardcore stuff hoping that someone actually does a lot of the work for you and brings something resembling a mature, standard package to the market you can build off with some of the early adopter errors ironed out.

So I think for us to close the gap between us let's try and agree on the following.

1. Analytics can absolutely add value, across a range of different areas and we should attempt to catch up vs the rest of the league but it is trickier to apply than say baseball & basketball.

2. Some of those areas are easier and more mature than others. Even teams embracing analytics are doing stupid shit like drafting a non-generational running back #4 overall (looking at you Jacksonville) or managing the clock worse than your average Madden player (cough Andy Reid).

3. There are massive demands on people's time turning this ship around, scouting, investigating human beings, self-scouting, aligning the football strategy.

4. There is finite money

5. A poor analytics implementation is likely to deliver very little value. When it is done it should be done properly and maybe year 2 of DG's reign after the draft is a sensible time to kick this off.

Let me close with what I see as the value in analytics and why we shouldn't obsess with the how or the maths or the machine learning but with the fact that our team is thinking analytically.

I've forgotten some of the details of this story but if I remember it was the 1987 Giants - Redskins game in the playoffs for a superbowl trip. Belichek stays awake watching film for crazy amounts of hours with his staff and one of the quality control guys spots that (I think) Ricky Sanders doesn't put his mouthpiece in when he's not a route option in the playcall. The Giants then know they can jump other routes and amend the football strategy accordingly. We all know the outcome.

That to me is just a good example of the kind of stuff we should be looking to analyse automatically and teach machines to do for us. It does get done today though, quality control guys are obsessive about looking for these give aways and tendencies but wouldn't it make life easier to be able to see percentages etc as soon as the all-22 film is available and have a machine evaluate all of this in a few hours and you can constantly build up the scope.

Belichek may be ahead of the field now, he always has been.
^^^  
arcarsenal : 9:13 am : link
Really good post.
English Alaister  
NoGainDayne : 9:52 am : link
Brevity has never been my strong suit, but Iíll separate your earlier query into two parts, one that explains how Iíd build the system broadly and the expected costs and another that addresses what is a very good point about esoteric concepts (like leadership) that humans asses better than machines, that is until you teach the machine what you know. (This is what a lot of effective Wall St. systems have done)

Building the System Step by Step

1) A Play Type Forecaster Ė timeouts/time management with game theory. Feed in game scores and timestamp every play with amount of time left, quarter, down, distance and then start with something Iíd say as simple as timeout, run offensive play, FB, punt, run defensive play, FG block, punt block, punt return then 2-point conversion as well. Each of these will have a win probability associated with choosing that type in a vacuum.

2) Enhanced Situational Play Type Forecaster Ė 4th down conversions and improved efficacy of step 1 systems through increased sophistication from data on weather, players, match-ups, team stats.

3) Build Autoencoder Ė this would convert game film to machine learning signals, I think you could look at this is a very similar to Zebra data, but this is important for the longitude of training sets as video goes back much further than alternative data

4) Build initial models for complex problems - stats, injury, asset allocation, play suggestions and fan sentiment could all be built and provide some level of value at this point (Iíd use a combination of unstructured and reinforcement learning as well as an experimental framework for conditional ensembling)

5) Lay groundwork for meta models which combine inputs from step 4 like wins and profit

This could all be done in one year, step one a few months max, at the total cost of $.5M to $1M, now I am saying this with proprietary software Iíve built over that past almost decade, Iím not the only one with software like this but there are many pretenders too. I also think the spend that gets to 10ís of millions is essentially paying for highly paid data scientists to tinker with models, hyper-parameters, data structures and time series modifications when software is much better at doing this. Iíd also add that McL who is clearly knowledgeable is talking about building much bigger teams than I think are necessary. I would also keep the team to pure back end until results passed the eye test and software deployment became a much bigger need.

I think the point on how valuable on this? Do you prioritize this? Itís tough to draw clear conclusions. In the case of the Saints game, down 12-7 at home completely blowing the creation of an extra possession for ourselves as we sat on timeouts when they had 1st and goal and more than enough time to score. (This wasnít our only blunder on clock management on the season, but it was our worst) can we really prioritize fixing other problems over something like that? Winning that game could have completely changed our season. Can we say definitively that the way we are approaching ďfixing these problemsĒ are right when the larger focus on traditional methods while de-prioritizing advanced team building analytics has seen us fall to the bottom of the league? And even last year with new management supposedly with skills assessing the trenches have us hand out some bad contracts in FA to the positions they needed to fix the most?

I do think itís hard to find the right tech people but that isnít an excuse not to start spending what is a paltry amount relative to the profitability of the organization on trying. Contract out a search team, tell them they can't interact with Gettleman or his staff for the first year or two if you are that concerned about his time. Resources are finite but I do believe the main thing that needs to be ďfixedĒ is that no matter how good our football people are now other teams have more diverse data to inform their decisions. While this isnít a definitive theory it canít be disregarded that a lot of these things we are trying to fix by largely the same methods could very well be symptom of the same problem which has to be fixed with the same commitment to technology that other teams have made already.
Part 2 predicting esoteric concepts  
NoGainDayne : 9:54 am : link
Any system an intelligent tech leader would build should incorporate existing data that scouts have made as inputs and be assessed with great scrutiny as outputs before you even think of deploying. Letís breakdown the famous IT factor of a QB for a second. You could say you just need to be in the room with them or you could break apart that problem. What are scouts looking at that we can work on quantifying better? This would be my preliminary list but also, Iíd want to work side by side with a great scout after attacking the obvious myself.

Wins (controlled for strength of team, not difficult if you have a way to project every player with an autoencoder)

Comebacks (controlled for strength of team)

Interview teammates and coaches and analyze with natural language processing (NLP)

Ask them about leadership, have them write about leadership (NLP)
Analyze grades, classes

Analyze facial expressions, body language and that of teammates

Wonderlic, existing Q&A etc.

This is the worry for me, something like this is just a jumping off point and based on Ty Siamís LinkedIn there is a very low probability he can build systems that simply predict IT factor leveraging this data let alone nesting this solution within broader systems.

And this is also why the sooner you start the better, maybe you are not videotaping prospect interviews, maybe with players permission you want to start getting EKG or MRI readings while they speak to you. The most important thing is taking your first shot and figuring out what people might be capturing that the computers are not and that is purely iterative.

Whatís crazy about this, is this a random thought exercise based on what we perceive to be something you need humans for when itís possible that all this information is embedded in camera or Zebra data and you donít need to do this at all. There are most likely a wealth of other shortcomings that can be addressed. Thatís why people pay people like me to do what we do, you must know how to start as unstructured as possible and commit to a process of adding structures and data to attempt to improve and solve perceived shortcomings of the human end users. This can take up zero time of existing internal people, one dedicated scout could probably do the trick on this and you could hire them separately.

When it is ready to start rolling this stuff out to higher level people to start comparing to their decisions to the computer live for better reinforcement learning it may seem time consuming but itís the job of a good technology leader that by the time they put it in front of business people with limited time it is already in a place to teach them new ways to look at the problem, so the models are improving as well as the perspective of the decision makers.
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