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In the NHL, you start by being part of the old-boys network, according to this current NHL executive, who wrote a book by talking to every living Stanley Cup Finals GM.
The lifetime these men spend building their networks and interacting with peers in various roles also gives them access to insight that helps guide their decision-making.
“At the core, the GM’s are in the information business,” Farris says. “If they can access information from all over the world ahead of other teams, they can gain an advantage. If they’re bringing a player in, they want to have a good read on the situation that the player is coming from and how he might impact the locker room, in addition to his on-ice abilities.”
And long-time, and successful GM, of the Devils, is my kind of guy when he says:
Controlling the flow of information and using it to drive internal decision-making is critical to success, but no optimal method exists that automatically translates to Stanley Cups.
New Jersey’s Lou Lamoriello, currently the NHL’s longest-tenured GM, takes a very different approach than Bowman. Instead of encouraging cooperation and teamwork amongst his staff, he creates information silos to eliminate the groupthink mentality.
“Lou purposely keeps certain people away from each other on the scouting and hockey operations staff,” Farris says. “He’ll say ‘look, the most important thing for you to do is X, go do it’ and he won’t tell anyone else what that guy might be doing because he wants to protect the integrity of the information.”
And this is what happens when you have a cap system:
Toronto has also built their organization around the power of ‘Big Blue’. As a GM in a constrained salary capped system, it’s important to create capacity for yourself. Maple Leafs ownership has given Burke the green light to outspend almost every team in the NHL when it comes to off-ice luxuries.
“Toronto has the best practice facility, a dedicated goalie coach, a player development staff, a scouting staff of 35 when most teams might have 20,” Farris says. “You’re limited in what you can spend in player salaries, but they’re outspending everyone off the ice to try and create a competitive advantage.”
Phil looks at one component, to show how the relative rate of points scored by the home team is dependent on how “easy” it is to score per possession. The easier it is to score, the less the relative rate of points will be earned by the home team. The harder it is to score (the more things have to compound in order for a goal or point to score), then the larger the relative rate of points earned by the home team.
In basketball, the current rules have it that the home team ends up getting 52% of the points. But, Phil changes the rules so that more compounding actions have to happen in order to get points, and he can change that to 54% of the points goes to the home team. Or, he reduces the number of compounding actions so that the home team gets barely more than 50% of the points.
It’s still part of the overall theme of “confrontations”. For example, Nadal’s clay-court advantage is different if we just look at total points earned, as opposed to matches-won. If you count as a “win” each point earned, maybe Nadal wins 150 points on court, while losing 100 or something. That is, he gets 60% of all points scored. But, if you count as a win each game, then he might win say 70% of all games. If you count as a win each set, he might win say 80% of the sets. And if you count as a win each match, he might win say 90% of all matches.
So, you can change the rules, like Phil is describing, to control the home-site advantage. And the compounding effects of the confrontations is how you do it.
Let’s just say that we’re not surprised by the general tone in these posts (except for the choking part, which is always shocking, regardless of who it is).
Bruce Dowbiggin was the Canadian counterpart to American Russ Conway, who together exposed NHLPA union leader Alan Eagleson’s crimes to the world. Imagine Marvin Miller, but who ends up actually being a really bad guy. That’s what happened. So unbelievable that Eagleson still had support from former players.
Anyway, Dowbiggin is interviewed, and asked for five hockey books to recommend, and gives us a bit of history of hockey in the process. An unusual format, but, great insight.
For each of the selections, I want to cherry-pick the quotes a bit and focus on the negative comments on players I consider a “success” (500+ games in the NHL), as well as the positive comments on those who played less than 500 games. I’ll keep them in the order that [NHL Central Scouting Bureau] placed them.
I still remember watching that 4OT game, Islanders/Capitals. I was exhausted watching it, so I can only imagine what it was like for the players to actually play it.
This event looks exactly like it’s part of the game. At worst a dirty hit, and worthy of a penalty, not sure about a suspension, but it could go either way, but still part of assumed risk. Not a criminal case. Chara/Pax, that’s a much better test case than this one.
In what can only be described as a possible path to the future if you let the inmates run the asylum, NHL playoffs have decended into some brutal plays. If the players can get away from speeding or running a red light, then they will. Is Shanahan to blame? Is it too late for him to send the message? Do we need someone to come in tough and hard and settle everyone down? Maybe we need someone like Paul Kariya or Pat Lafontaine to be in charge of punishment.
Gabe and I wrote this a while ago. I was hoping it to get some broad exposure, but we weren’t able to find any takers. Anyway, it seems to have good timing, especially today.
This is just a crazy thought I had. I haven’t tested it. Maybe someone out there can run the numbers. You get 9 points for a win, and then one bonus point for every run differential up to a maximum of 6 bonus points. So, win by 1, and you get 10 points. Win by 6 (or more), and you get 15 points. So, if you win three games by 1 run, or you win two by 6, and lose the third game, you get 30 points either way.
There are three points to consider when constructing this:
1. How many points for a win, your base level (*)
2. What score differential to cap?
3. Do you give points for losing close games, or do you get zero points whether you lose by 1 or 6?
(*) In my case is 9, which is a pleasant number as far as baseball is concerned. I kind of did a trial and error to see what numbers would seem reasonable, and once I saw that I was coalescing toward 9, I decided that’s a good enough number. My guess is that you can do this for any sport, and set the number as the average number of points per game. In baseball, it’s about 9 runs per game (4.5 for each team). I’d bet you can do the same thing in NHL and use 6 as the base level, and then cap it off at half of that, so that the range in NHL would be 7 to 10 or 11. NFL is probably 42 points as the base, so the range would be say 43 to 63 (maximum differential of 21 points). NBA? I dunno, say have a base of 200 points, with a range of 201 to 220 or something.
So, I’d like to see a bit of work from the Straigh Arrow readers, if you like to play around with stuff like this.
The first time I saw these even-odd correlations was from Keith Woolner about a decade ago. It’s so briliiantly simple, that I took to it right away. All those problems I had with aging being a factor gets washed away. This has the benefit to fantastically increasing your sample size, without needing to adjust for the aging variable.
Anyway, Brian applies it for hockey goals, trying to predict the number of goals scored in one group based on the goals, shots, hits, and faceoffs of the other group. Hence, even-odd correlation.
Brian posts this, which is even more cumbersome than it needs to be:
-1.34 + 0.31*Goals + 0.03*Shots + 0.03*HitsAgainst - 0.03*Hits + 0.04*TotalFaceoffs
First realize that in hockey, there are about one goal scored for every 10 to 11 shots. So, look at the coefficient of shots and goals: it practically maintains that ratio. What does this mean? Well, if you only look at those two components, then this means that goals and shots equally predict goals! That’s great, isn’t it? So, you can take that part and simply recast it as:
0.31 * (Goals + Shots/10)
So, a team that scores 3 goals with 30 shots or 4 goals with 20 shots or 2 goals with 40 shots will converge to the same point.
That 0.31 coefficient means that it regresses two-thirds of the way toward the mean. BUT, that’s based on whatever number of games in each pool. In fact, you CAN’T just use the 0.31. You need to know how many games Brian had in each pool, and use THAT into the equation. So, if Brian had 40 games in each pool for each team, then that 0.31 can be rewritten as:
GP/(GP+89)
If you have 40 games, then the coefficient is 0.31. But, if you only have 1 game, then guess what? You can’t apply the 0.31. And if you had three seasons worth of games, then the coefficient is higher. (Indeed, the goals and shots coefficient may each regress differently, so you wouldn’t necessarily merge the goals and shots as I have.) Of course, you can’t go too far with it at the team level, since teams are not static. It’s not like Montreal2007 and Montreal 2012 would necessarily be part of the same “Montreal” dataset.
The two hits terms can be merged into one, as HitDifferential. But, let’s set aside the Hits and Faceoff components for this talk. For hits, the two will become zero anyway. For the faceoffs, let’s say we replace that with a fixed value of +2.4.
We end up with:
0.31 * (Goals + Shots/10) -1.34 + 2.40
Or with a little fancy footwork:
0.31 * (Goals + Shots/10 - 5.4) + 2.7
What does that mean? Well, Goals - 2.7 is goals above average. Shots/10 - 2.7 is goals above average. You take the two together, multiply by 0.31, and you get goals above average. And add in 2.7, and you get… total goals.
I think recasting in this manner makes it much clearer what is going on. If goals and shots together perfectly predicted goals, that 0.31 coefficient would instead have been 0.50.
This rarely happens. I’ve never seen it happen. Here’s the story.
And here’s the video of today’s game, as well as the last time they played (4-man brawl to open the game). And, the time before that, it was a 2-man to open the game. Devils-Rangers.
The fans really get into it (Canadian or US fans, they all get into it). In Europe though, some brawls get booed. I’ve never seen a brawl booed in North America. It was a boxing match that preceded the game, that’s what it was.
Brodeur though did speak up:
“I don’t like it,” Brodeur said. “I know the fans get into it. We’re here to play. It takes 10 minutes to pick up the gloves and blood.”
I’ll use a hockey example first, and then I’ll switch to baseball.
In hockey, goal scoring follows a Poisson distribution. If we have two distributions, one with a mean of 3.0, and another with a mean of 2.7, we can figure out how often the one with a mean of 3.0 will have a random value higher than the one with the mean of 2.7. Ties are broken down in sudden-death OT fashion. In this case, in a 60-minute game of a 3 goals per game team facing a 2.7 goals per game team, the better team will win 55.3% of the time.
Now, what if a game of hockey was only one period? Setting aside any “change of pace” argument, we can model this as simply a 1.0 goals per game (that is, a game is 20 minutes, or one-third as long as the standard game) team facing a 0.9 goals per game team. In that case, Poisson says that the better team will win 53.5% of the time.
As you can see, changing nothing about the sport other than the number of periods, we can drastically alter the home-site advantage. It’s all based on the number of confrontations. The longer the game, the more the confrontations, then, the more the gap in talent will override the effect of random variation.
If we look at how often teams are tied heading into the third period, which is the same thing as I’m talking about here with the one-period game, I’m sure we’d see this kind of result, that home-site advantage will drop proportionately as I’m showing here.
We can see that with baseball as well. Now, baseball doesn’t follow a Poisson distribution, but we can model it as well. A 9-inning game gives us a .540 win%, while a 1-inning game would give us a .520 win% (which is close to the empirical result).
We can go through this with any sport, and the same thing will happen.
This is most clear in tennis, where the chance of Federer, Nadal, or Djokovic losing a 5-set match to someone other than the other two guys is much smaller than losing a 3-set match. For example, say that the big 3 is up 2 sets to 1 against the #20 seeded player. What is the chance that they would end up winning one of their next two sets? It’s going to be pretty high. Now, suppose the #20 seeded player is up 2 sets to 1 against one of the big 3. What is the chance that this #20 seeded player is going to win one of his next two sets? I don’t know what it is, but it’s DEFINITELY less than when the roles are reversed.
If Tiger in his prime had a 33% chance of winning a four-round tournament, then what’s the odds of him winning a single-round tournament? It’s definitely less than 33%. Probably something like 10%. That is, if you looked at each day’s results, I’d bet that Tiger in his prime won something like 10% of his rounds (if he won 33% of his tournaments). Something like that.
So, when people compare the home-site advantage of various sports, and trying to explain why one sport has a “higher” advantage than another, it’s meaningless. It’s entirely dependent on the number of confrontations.
When Gretzky was 20 years old, and already made his mark in the NHL, there was still some doubt in 1981. Guy Lafleur had come off six sensational years (his Koufax years) through 1980. And in 1981, he was still pretty good. When the reporters asked the Canadiens about Gretzky when the two teams were in the playoffs, the players said “Guy will put him in his back pocket”. The young Gretzky did not answer. Instead, he had a great series, and all he did when he skated past the Canadiens bench was tap his butt with his glove ("*I* am the one who’s got Guy in my back pocket, is what he showed without saying it.)
And that’s how you brag. You don’t say it before you do it, and you don’t go out of your way to say it. You make your point quick and at the appropriate time, and then you move on.
And even when asked throughout his career about his own talent, Gretzky would just go as high as to say “I’m a pretty good hockey player.” And, he’s always acknowledged his teammates. Even at his retirement press conference, he went out of his way to talk about Darren Langdon. Langdon you should know was a young “nobody” goon with the Rangers, but to Gretzky he was someone special. How many superstars on their retirement conference point out a guy like that?
(I’ve said it before, but I love saying this part too. At that same conference, after it was over, TSN, which is the Canadian ESPN, then had their two gasbags talking about Gretzky. Gretzky in the background starts walking through all the empty chairs, and eventually sidles up next to the two gasbags, slaps them on the back and says, “Ok, let’s talk to Canada.” It was great. One of the two gasbags by the way was a reporter who was hugely critical of Gretzky back in 1993, when the Kings were playing the Leafs in the semi-finals, and he said that Gretzky was playing like he had a piano on his back. Gretzky promptly went out and had one of the best games of his career. And that’s as close as the Leafs would come to make the Stanley Cup.)
Back in 1982, the Devils moved to NJ, and as the late owner’s son describes it:
It was pretty complicated to move the team here because of the indemnification. They had to indemnify the Rangers, Islanders and Flyers. As I understand, the NHL had a finance committee that arrived at that payment schedule ($12.5 million) to the three teams because we came into their media territory
I didn’t realize that the Flyers were part of that deal.
Another interesting one was when the NHL expanded in the south in 1992. The standard exapansion fee at the time was 50MM$. That’s what the Lightning paid. Anaheim also paid the 50MM$, but half of that went to the Kings. So, Anaheim technically paid just 25MM$ in expansion fees, and another 25MM$ for the territorial fees. Basically, the NHL wanted to get it done, and they wanted to pave the way for Disney to get into the league, and they wanted to make sure the Gretzky-fueled hysteria was capitalized down south. Anaheim paid 0 in territorial fees, and the rest of the league decided to indemnify the Kings instead, just to have a happy family.
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