News and Blog Report: Analytics and their evolution

[Slats432]

'Open people's eyes': How the NHL's evolved in the decade of data

The curly-haired chemist is working away in a San Jose lab. He's wearing a white lab coat, safety goggles, and nitrile gloves. Flasks are stirring on a hot plate with temperature monitors nearby. The lab, run by the electric car battery company QuantumScape, stores various solvents and inorganic...

www.thescore.com

Since this was the first place I ever heard about analytics, I thought this would resonate with some. All those Mc79hockey, Lowetide and igor posts vindicated for their support of analytics on here.

Click to read more...

 

[Jimmi McJenkins]

Great read, thanks. Also, this is wild to me

 

[5 Mins 4 Ftg]

 

[Drivesaitl]

Great read, thanks. Also, this is wild to me

View attachment 835742

Not sure what to make of this. Some of the worst run teams have the biggest analytics depts. The one with the smallest just won the cup.

One could also say the over reliance on analytics results in ineffective teams that look like NJ, Seattle. Or the Leafs who perpetually fail to eternity.

The Oilers have 6 analytics department and are one of the worst drafting clubs in the league.

The Florida Panthers with among the least analytics people is probably the best run team in the league currently. The Jets with 4 might be 2nd best run.


I guess if people just want to count total analytics people employed this is something, but its still something that isn't shown to be immensely better than other assessment methods.

If one did a rank ordinal correlation of place in standings vs amount of analytics staff there wouldn't be strong correlation. Just look at the 6 clubs with the most analytics staff. 5 of those clubs are missing playoffs. The other is lol Toronto that have been wrong on so many players.

 

[DaGap]

If you gamble and play the NHL you will realize how analytics gets you only so far.

 

[belair]

Not sure what to make of this. Some of the worst run teams have the biggest analytics depts. The one with the smallest just won the cup.

One could also say the over reliance on analytics results in ineffective teams that look like NJ, Seattle. Or the Leafs who perpetually fail to eternity.

The Oilers have 6 analytics department and are one of the worst drafting clubs in the league.

The Florida Panthers with among the least analytics people is probably the best run team in the league currently. The Jets with 4 might be 2nd best run.


I guess if people just want to count total analytics people employed this is something, but its still something that isn't shown to be immensely better than other assessment methods.

If one did a rank ordinal correlation of place in standings vs amount of analytics staff there wouldn't be strong correlation. Just look at the 6 clubs with the most analytics staff. 5 of those clubs are missing playoffs. The other is lol Toronto that have been wrong on so many players.

What would analytics have to do with a team's success in drafting? Hard to imagine that the data being tracked in lower leagues provides much in terms of projecting upside at a much higher level of competition.

 

[McDNicks17]

Great stuff.

The media covering analytics has probably been more lacking than the NHL's use of it. I'm glad they're starting to put stuff like this out.

Not sure what to make of this. Some of the worst run teams have the biggest analytics depts. The one with the smallest just won the cup.

One could also say the over reliance on analytics results in ineffective teams that look like NJ, Seattle. Or the Leafs who perpetually fail to eternity.

The Oilers have 6 analytics department and are one of the worst drafting clubs in the league.

The Florida Panthers with among the least analytics people is probably the best run team in the league currently. The Jets with 4 might be 2nd best run.


I guess if people just want to count total analytics people employed this is something, but its still something that isn't shown to be immensely better than other assessment methods.

If one did a rank ordinal correlation of place in standings vs amount of analytics staff there wouldn't be strong correlation. Just look at the 6 clubs with the most analytics staff. 5 of those clubs are missing playoffs. The other is lol Toronto that have been wrong on so many players.

I think the number of people in data-related roles is kind of irrelevant. Like they said in the article, every team has access to the same data. It just depends on how you're finding insight in them and if the rest of the organization is willing to listen to them. Third party firms make it very easy for anyone in an organization to use analytics, so you don't really need guys specifically designated for it.

Like Vegas may only have one person in a data-related role, but you can clearly see Cassidy is very analytically-minded by the article. My guess would be they have managers that share a similar vision since they seem to target players that fit Cassidy's philosophy.

Look at the St. Louis example too. Robert Thomas is doing deep dives with their goaltending coach on goal-scoring trends. He wouldn't show up as a guy in a "data-related role".

 

[McDNicks17]

If you gamble and play the NHL you will realize how analytics gets you only so far.

The publicly available data is like 0.01% of what NHL teams have access to.

Looking at some xG model to gamble isn't remotely similar to what they're doing.

 

[Soundwave]

The Oilers need a shaman or cleric or exorcist to help with their drafting.

Like honestly it's so bad, it's not even explainable. It's not even a Chiarelli/Holland thing exclusively, it's been bad since like 1983.

The Kevin Lowe era was the best drafting era we've had post-1983 when they got Tikkanen in the 3rd or 4th round.

It's like Pocklington made some kind of deal where the 79, 80, and 81 drafts would bring him 5 Cups, but the catch was the team can't draft for another 50 years.

Like I had to literally look this up and really realize "holy crap ... this is even worse than what I remember".

 

[Behind Enemy Lines]

Good article. Weird flex.

Innovation, information and finding efficiencies or inefficiencies has always been part of the game whether coaching, equipment, sports science, enhancing information capture and analysis. Moving beyond the eye test to more structured data collection and analysis took its leap into mainstream last decade.

I think Cassidy's insight summarizes this support function well. Build the strategy, execute with personnel, test and ongoing utilize information through statistics to drill down and assess and evaluate against strategy and process.

"Players determine success, not numbers," Cassidy said. "But it sure can help you coach your players. I think the data itself has come a long way, and the coaches I think who are current will use analytics to their advantage."

Numbers can also be a check on team identity for Cassidy. Vegas famously packs the middle of the ice on defense to limit shots from prime scoring spots, so it's OK if the club ranks high in defensive-zone time. It's not OK, however, if it ranks high in high-danger scoring chances against.
"I can look at certain areas and say, 'Yeah, that number's no good. That's one of the reasons our game has slipped a little bit,'" Cassidy explained. "Other numbers could be there - high or low - and they do not go hand in hand at all with what's going on on the ice because it's not relevant to how we play."

I like the insight about Ron Francis, a deep and knowledgeable hockey lifer 'saw it gooder' type who stepped up to hire a non-traditional, trained data scientist to augment his decision making capability. Bringing far more sophisticated with R & D was a necessity lacking in operating a billion dollar big business. I hope that a guy from the Jim Rutherford, Ron Francis management tree, Jason Botterill, will get strong consideration as the Oilers next GM. Blend the deep hockey experience with a growth mindset open to all innovations to winning including a trained data science team which is now in place.

Read a solid book about the Boston Red Sox focused on their organizational approach to guide their business operations. One critical hire is like a high level translator with credibility as an ex-player but deeply versed in analytics and data science bridging the two worlds. Then implementing consistent management philosophy and team strategy throughout all levels of their farm system.

 

[Slats432]

More on analytics and drafting, I know the owner of Stathletes. We had talked before a draft that they track the prospects for the NHL teams and they will provide reports prior and give information to help make selections.

He told me (And this was early 2010s) that Vancouver and NYR were customers of his. I am sure he wouldn't care 15 years later I divulged this information...haha.

 

[Drivesaitl]

Great stuff.

The media covering analytics has probably been more lacking than the NHL's use of it. I'm glad they're starting to put stuff like this out.



I think the number of people in data-related roles is kind of irrelevant. Like they said in the article, every team has access to the same data. It just depends on how you're finding insight in them and if the rest of the organization is willing to listen to them. Third party firms make it very easy for anyone in an organization to use analytics, so you don't really need guys specifically designated for it.

Like Vegas may only have one person in a data-related role, but you can clearly see Cassidy is very analytically-minded by the article. My guess would be they have managers that share a similar vision since they seem to target players that fit Cassidy's philosophy.

Look at the St. Louis example too. Robert Thomas is doing deep dives with their goaltending coach on goal-scoring trends. He wouldn't show up as a guy in a "data-related role".

Depends on the data in my view. The article is fair in that it speaks of earlier analytics as primitive modeling and metrics. I always was of the opinion they were. For 25yrs I've been crowing about the need for the data to come from sensors in equipment, puck, and rinks rather than observed data. So that the Edge data cited in the article is intriguing. So we're getting better data now and far less subject to interobserver bias and rink to rink skewed data counts. hopefully the equipment functions well and equally in all rinks. I'd think I would have to know more about how standardized the setups are as not even cameras or broadcast booths are close to being standardized.

So overall I'm feeling better about analytics now. Still, some of the conclusions drawn from data are still problematic. The article cites that point shots are out now. Yet its how we were beaten by Winnipeg in playoffs. They generated a lot from the points, we were getting nothing from the point. Plus we've never had more D just elite at bombing from the point or more shot passes from the point. Point is still dangerous and affords different ways to score and setup plays.

The other thing in the article that I kind of laughed at is the conclusion that analytics helped teach that passing across is more dangerous than shoot, shoot? Well gee, we're fans of the Edmonton Oilers, this was a known as long as the Oilers have been in the NHL. Its not like it was something discovered. Unfortunately what continues is that the purveyors of analytics do a really poor job of verbalizing findings and conclusions. This has always been a week area. Better communication of details is needed.

 

[Drivesaitl]

Just as an aside on NHL Edge data the other trouble with more data is what get used, how, and what is evaluated from that. I'll take a case point. Rasmus Kupari is terrible at NHL hockey. He's inept. He makes Connor Brown look like a topten producer. The guy is one of the fastest guys in the league and its really the only reason he's in the league. he can't piss a drop of offense but the knowledge that he's one of the fastest players keeps him in the league. But to me thats where the data can persuade keeping players in the league longer than they should. Kupari is an absolute bust. The guy is 24 tomorrow and makes compatriot Jesse Puljujarvi look like a top scorer. Kupari has one assist. All season.

This is just one example of players that are only in the league due to tracking data. I've watched the guy for years. Nothing is ever going to happen with him. Have him in your lineup and just wasting a roster spot. Should be playing in Europe.

Heres another one from NHL Edge. In the category of +100mph shots some of the most dangerous D shots aren't in that stat because they shoot slightly less speed. But it means nothing to have that specific category. Anything around 90miles and up is a serious bomb and the ability to get shots through consistently and pick spots and use screens more important that shot speed. So that Evan Bouchard probably best point shooter in league right now, and nobody really needs the analytics to determine that. Just watching him does.

Yet a punter like Xhekaj has one of the fastest shots in the world, can win competitions like that on shot speed but it means nothing. He has 8 career goals. he has 3 this season. he's not even dangerous.

These just being examples where data alone doesn't really say much. Trouble is if some of this data is applied to drafts it could lead to bad drafting on specious skillsets.

 

[Fourier]

Depends on the data in my view. The article is fair in that it speaks of earlier analytics as primitive modeling and metrics. I always was of the opinion they were. For 25yrs I've been crowing about the need for the data to come from sensors in equipment, puck, and rinks rather than observed data. So that the Edge data cited in the article is intriguing. So we're getting better data now and far less subject to interobserver bias and rink to rink skewed data counts. hopefully the equipment functions well and equally in all rinks. I'd think I would have to know more about how standardized the setups are as not even cameras or broadcast booths are close to being standardized.

So overall I'm feeling better about analytics now. Still, some of the conclusions drawn from data are still problematic. The article cites that point shots are out now. Yet its how we were beaten by Winnipeg in playoffs. They generated a lot from the points, we were getting nothing from the point. Plus we've never had more D just elite at bombing from the point or more shot passes from the point. Point is still dangerous and affords different ways to score and setup plays.

The other thing in the article that I kind of laughed at is the conclusion that analytics helped teach that passing across is more dangerous than shoot, shoot? Well gee, we're fans of the Edmonton Oilers, this was a known as long as the Oilers have been in the NHL. Its not like it was something discovered. Unfortunately what continues is that the purveyors of analytics do a really poor job of verbalizing findings and conclusions. This has always been a week area. Better communication of details is needed.

The bolded made me think of Dallas Eakins. He might have benefitted for some of this sage advice.

As to the communication part. This is why you hire professionals. One of the big issues I had with the some of the early zealots was that they were not capable of communicating the limitation of their work. For some I suspect that this was because they did not understand, for others it was pure arrogance, assuming that anyone who did not buy what they were saying was to ignorant to understand, and still others were just not all that good at conveying technical information to a lay audience. Understanding something and being able to explain it to others are not the same thing.

I remember watching the expert that the prosecution hired to try and explain the DNA evidence in the OJ Simpson case. The evidence should have been almost impossible to overcome but the explanation was so brutal that it was probably rendered useless. I think anyone with some teaching experience and even a modest background in probability would have been able to do enough to make it clear.

 

[McDNicks17]

Depends on the data in my view. The article is fair in that it speaks of earlier analytics as primitive modeling and metrics. I always was of the opinion they were. For 25yrs I've been crowing about the need for the data to come from sensors in equipment, puck, and rinks rather than observed data. So that the Edge data cited in the article is intriguing. So we're getting better data now and far less subject to interobserver bias and rink to rink skewed data counts. hopefully the equipment functions well and equally in all rinks. I'd think I would have to know more about how standardized the setups are as not even cameras or broadcast booths are close to being standardized.

So overall I'm feeling better about analytics now. Still, some of the conclusions drawn from data are still problematic. The article cites that point shots are out now. Yet its how we were beaten by Winnipeg in playoffs. They generated a lot from the points, we were getting nothing from the point. Plus we've never had more D just elite at bombing from the point or more shot passes from the point. Point is still dangerous and affords different ways to score and setup plays.

The other thing in the article that I kind of laughed at is the conclusion that analytics helped teach that passing across is more dangerous than shoot, shoot? Well gee, we're fans of the Edmonton Oilers, this was a known as long as the Oilers have been in the NHL. Its not like it was something discovered. Unfortunately what continues is that the purveyors of analytics do a really poor job of verbalizing findings and conclusions. This has always been a week area. Better communication of details is needed.

Who knows? Maybe the analytics hinted at the Oilers being susceptible to point shots. They got destroyed by them in the Chicago series too, IIRC.

 

[Drivesaitl]

The bolded made me think of Dallas Eakins. He might have benefitted for some of this sage advice.

As to the communication part. This is why you hire professionals. One of the big issues I had with the some of the early zealots was that they were not capable of communicating the limitation of their work. For some I suspect that this was because they did not understand, for others it was pure arrogance, assuming that anyone who did not buy what they were saying was to ignorant to understand, and still others were just not all that good at conveying technical information to a lay audience. Understanding something and being able to explain it to others are not the same thing.

I remember watching the expert that the prosecution hired to try and explain the DNA evidence in the OJ Simpson case. The evidence should have been almost impossible to overcome but the explanation was so brutal that it was probably rendered useless. I think anyone with some teaching experience and even a modest background in probability would have been able to do enough to make it clear.

Here we agree. But it possibly has to do with people having skillsets in different areas and those that are into certain stats as a pastime are maybe not necessarily good at verbal or written abilities. Some master all but many struggle linguistically. My other concern was the analytics acolytes, the early ones, they were not Statistically trained in the first place. They pretended as if they were. As if methodology didn't even matter.

"Zealots".

I don't disagree. But it was often borne of a want for some of those individuals to talk down to the masses pretending they have full purview on hockey understanding. It was never worse than them talking down to people that coached hockey, that scouted hockey etc.

 

[Fourier]

Here we agree. But it possibly has to do with people having skillsets in different areas and those that are into certain stats as a pastime are maybe not necessarily good at verbal or written abilities. Some master all but many struggle linguistically. My other concern was the analytics acolytes, the early ones, they were not Statistically trained in the first place. They pretended as if they were. As if methodology didn't even matter.

"Zealots".

I don't disagree. But it was often borne of a want for some of those individuals to talk down to the masses pretending they have full purview on hockey understanding. It was never worse than them talking down to people that coached hockey, that scouted hockey etc.

It was not just hockey knowledge. I can absolutely live with someone questioning my hockey knowledge. BUt I don't know how many times I was told that I just did not or would not understand the math,

 

[Sheikyerbouti]

Analytics which uncover trends is gold in hockey, but analytics uncovering unheralded NHL players and prospects is fantasy imo

Baseball is just different, you can use analytics to find things the eye can't see, because the sample sizes are larger, the database (players) is 100X bigger and the amateur draft is 4X longer ....... plus there is global development complex's and international FA.

Teams like Vegas and Florida are definitely using analytics well, but they are smart enough not to throw money at moneyball scouting

Oilers say they are analytics driven when amateur scouting, but Holland's team has consistently drafted tools the entire time, so I don't think it is accurate and they feel analytics promotion will appease fans.

 

[Drivesaitl]

It was not just hockey knowledge. I can absolutely live with someone questioning my hockey knowledge. BUt I don't know how many times I was told that I just did not or would not understand the math,

Yeah I understood what you meant. Been around long enough to have seen it here.

 

[brentashton]

'Open people's eyes': How the NHL's evolved in the decade of data

The curly-haired chemist is working away in a San Jose lab. He's wearing a white lab coat, safety goggles, and nitrile gloves. Flasks are stirring on a hot plate with temperature monitors nearby. The lab, run by the electric car battery company QuantumScape, stores various solvents and inorganic...

www.thescore.com

Since this was the first place I ever heard about analytics, I thought this would resonate with some. All those Mc79hockey, Lowetide and igor posts vindicated for their support of analytics on here.

Interesting where recent SC winners stack up in the list of data crunchers on staff.

 

[McDNicks17]

Analytics which uncover trends is gold in hockey, but analytics uncovering unheralded NHL players and prospects is fantasy imo

Baseball is just different, you can use analytics to find things the eye can't see, because the sample sizes are larger, the database (players) is 100X bigger and the amateur draft is 4X longer ....... plus there is global development complex's and international FA.

Teams like Vegas and Florida are definitely using analytics well, but they are smart enough not to throw money at moneyball scouting

Oilers say they are analytics driven when amateur scouting, but Holland's team has consistently drafted tools the entire time, so I don't think it is accurate and they feel analytics promotion will appease fans.

I think that mainly happens in the form of finding guys that would fit your system better than the one they're playing in.

Like Florida has that unique style where they create a ton of time and space off the rush, so they seem to target the guys that excel with time and space, but who aren't getting that on other teams.

 

[Slats432]

It was not just hockey knowledge. I can absolutely live with someone questioning my hockey knowledge. BUt I don't know how many times I was told that I just did not or would not understand the math,

This was my biggest deterrent to the analytics at the beginning. "If you don't agree with me, you either don't understand or are just stupid." Igor and Tyler did that early but Tyler certainly softened as time went on.

Personally I had to evolve because I just wanted to watch the game an enjoy it and not drill down into Corsi, PDO, zone starts, pts/60, WOWY. But dinosaurs like me have to change and I have come to use the tools to see how I feel about a player. If I am going to say someone is shit, I should at least figure out why I think they are shit. LOL

 

[Fourier]

This was my biggest deterrent to the analytics at the beginning. "If you don't agree with me, you either don't understand or are just stupid." Igor and Tyler did that early but Tyler certainly softened as time went on.

Personally I had to evolve because I just wanted to watch the game an enjoy it and not drill down into Corsi, PDO, zone starts, pts/60, WOWY. But dinosaurs like me have to change and I have come to use the tools to see how I feel about a player. If I am going to say someone is shit, I should at least figure out why I think they are shit. LOL

I am not a technical hockey guy at all. Football and curling are two sports I know much more about as far as the technical stuff is concerned. But I have watched the sport fairly religiously for almost 60 years so I have some idea of what is going on. For me stats allow me to either fortify or dissuade my beliefs. But it is important to understand the limitations of how the numbers are used. Sometimes a statistic can give definitive evidence and other times the same statistic can be completely useless in referencing two seemingly similar assertions. The differences in such situations can be quite subtle. So it is easy to see why people who may not be able to see such subtleties can misuse the numbers. What is less forgivable is when so called experts give specious arguments that show their lack of understanding.

 

[McDNicks17]

I am not a technical hockey guy at all. Football and curling are two sports I know much more about as far as the technical stuff is concerned. But I have watched the sport fairly religiously for almost 60 years so I have some idea of what is going on. For me stats allow me to either fortify or dissuade my beliefs. But it is important to understand the limitations of how the numbers are used. Sometimes a statistic can give definitive evidence and other times the same statistic can be completely useless in referencing two seemingly similar assertions. The differences in such situations can be quite subtle. So it is easy to see why people who may not be able to see such subtleties can misuse the numbers. What is less forgivable is when so called experts give specious arguments that show their lack of understanding.

And that happens a lot unfortunately.

I forgot who it was, but they were listed as The Athletic's analytics writer and they wrote a long drawn-out article that basically boiled to Player A is better than Player B and Player C because his GF% is better. No mention of any context. Simply just GF%.

It blew me away that they were actually paying that person to write about analytics.

 

[Fourier]

And that happens a lot unfortunately.

I forgot who it was, but they were listed as The Athletic's analytics writer and they wrote a long drawn-out article that basically boiled to Player A is better than Player B and Player C because his GF% is better. No mention of any context. Simply just GF%.

It blew me away that they were actually paying that person to write about analytics.

Aside from some rather specific situations, there are very few stats that are definitive without context. And there are very few stats that cannot have value with the proper context. +/- is a great example. Without context it is often nearly meaningless. But in the right situation it can be quite valuable.

As you know GF% is really just a fancy version of +/-.