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MIT Sloan Sport Analytics Conference has a bunch of video at this link. I haven't watch them but the topics seem extremely interesting.


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The Moneypuck revolution

JAMES MIRTLE, Globe and Mail, Sep. 23, 2011

It's a revolution that has, in many ways, already taken place in North America's other top professional sports.

In baseball, Bill James, Billy Beane and Moneyball – the film version of which was released in theatres this weekend and stars Brad Pitt as Beane – helped bring in-depth statistical analysis out into the open to the point that it's now simply part of doing business for most teams.

In the NBA, the Houston Rockets turned to former MIT analytics professor Daryl Morey to be their general manager, one of more and more hires in that vein in the basketball world.

And in the NFL, teams such as the New England Patriots have long used advanced statistics to dig up the best players for the lowest price, giving them an advantage under the salary cap.

Hockey, however, has always been behind the curve.

Which is where people like Gabriel Desjardins are coming in.

With a day job as an engineer with a semiconductor firm in Silicon Valley, Desjardins's background is unlike anyone's in hockey. But with teams looking for a unique edge, he's being called upon regularly when NHL teams have a decision to make.

While his name isn't listed on any team's directory, the 34-year-old, originally from Winnipeg, is now on the payroll of three teams as part of a new push for more statistical analysis in the league.

More than 30 years after James made a name for himself as baseball's leading numbers guru, Desjardins has built a reputation that will likely see him catch with a team full time – just as James did as a senior adviser with the Boston Red Sox in 2003.

It seems only fitting that Desjardins grew up reading James's work and began applying it to the NHL about a decade ago.

“He's somebody who changed my thinking about baseball,” Desjardins said. “And ultimately he made me change my thinking about hockey, even though he doesn't know anything about hockey.”

In some cases, that meant borrowing directly from James, such as when Desjardins used his “minor league equivalencies” concept to project how goals and assists in junior or minor pro leagues translate to the NHL.

In others, Desjardins developed completely new statistics specifically for hockey, including ratings for the quality of players' teammates and opponents when they're on the ice.

Other metrics, such as Corsi – which was originally used by Buffalo Sabres goaltending coach Jim Corsi to measure the workload netminders were facing – gauge how often players are in possession of the puck by counting every shot directed at either net (including those that miss the net or are blocked) while they're on the ice.

In contrast to traditional statistics such as goals and assists, advanced statisticians believe these new numbers offer greater insight into which players are performing well in important areas of the game, including defensive play, puck possession and ability to play against other team's top lines.

This knowledge, in theory, allows teams to better determine what players should be paid – that is, their true value under the salary cap – and find players who may be overlooked or underrated by their own organizations.

Desjardins's work at behindthenet.ca has gained a large following in the past several years, but NHL teams have only recently begun to reach out to him for help. At a cost of up to $200 an hour, he now dedicates roughly eight hours a week during the season to the endeavour.

Which teams he works for and what, precisely, he does for them, however, remains behind closed doors, as he's sworn to confidentiality as teams try to keep quiet any work they do in what is very new territory for the league.

What Desjardins can say is that some of his recommendations led directly to teams pulling the trigger on major deals last season.

“I've seen people use Corsi to make trades,” he said. “I'll put it that way.”

The secrecy surrounding analytics in the NHL extends well beyond Desjardins.

Of all the teams contacted on the subject, only the Pittsburgh Penguins were willing to talk openly about their increasing use of advanced statistics, which began in earnest last year through a partnership with a group called The Sports Analytics Institute.

“This was the first year, this past season, that I felt we were really onto something,” said Penguins director of player personnel Dan MacKinnon, who has become the team's point man in the area. “We're getting some powerful insight into things that you just can't track with the naked eye or traditional statistics.”

MacKinnon estimates that only five or six NHL teams are doing considerable work with analytics, with another half dozen beginning to “kick tires” and investigate some of the concepts involved.

The rest of the league, he said, isn't going this route because “they feel hockey doesn't lend itself to analytics.”

MacKinnon pointed to the Sabres' recent creation of a small analytics department as a sign of where things are going, adding that he wouldn't be surprised if more and more people like Desjardins are brought into the fold to offer a different perspective.

SAI's model has introduced the Penguins to in-depth shot location analysis and goal scoring probabilities – using a statistic called predicted goals scored – that they make available after every NHL game.

What was initially a tough sell (and remains one to many teams) has become a tool some on Pittsburgh's staff use on a daily basis.

“Instead of explaining it to people, we put it right in front of them,” said Kevin Mongeon, an economics professor who developed SAI's metrics with analytics specialist Mike Boyle. “And said, ‘Here it is.' They looked at it, and there's a little bit of variation game over game, but after 10 games, they went, ‘Holy crap, I can't believe I've been doing my job without this.'

“The coach in Pittsburgh, we went down after a game one time, and he said ‘Did we out PGS them?' They used it as a verb after a while. But it took a while to get there.”

Desjardins met that resistance firsthand when he began meeting with teams, recalling one recent sit-down with an NHL general manager who wrote off his work as merely “doing arithmetic.”

He believes most teams still have a long way to go in terms of embracing what advanced statistics can do for their organizations.

“You can see that there are a lot of decisions made every year – Philadelphia getting [Ilya] Bryzgalov, for one – that pretty much any analytics department would, 100 per cent, advise you against,” Desjardins said, referencing the Flyers netminder's $51-million contract as an example of inefficient spending.

“As high as player salaries are, if you hired a very skilled analytical consultant from industry, paid them $150,000 to $200,000 a year, and he sits there and works on things all year and comes up with recommendations, what are the odds that he's not going to be able to find you a player that you can sign for $200,000 less his value or less than you otherwise would have paid?

“It's pretty obvious that there's some value in there.”

MacKinnon agrees and sees that as the way things will be done in the future as the NHL finally follows in the footsteps of other major pro leagues.

He hopes that by shedding light on what the Penguins are doing more teams will get on board and the data available will improve.

“There's no doubt in my mind,” MacKinnon said. “Ten years from now, every team will be using something like this.

“For me to make the best recommendation possible to [Penguins general manager Ray Shero], I'm using this as a powerful tool and he's asking what it's told me.”

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Hockey’s new numbers

James Mirtle, Globe and Mail, Sep. 23, 2011

Here are four statistics Gabriel Desjardins says are changing hockey and a fifth created by the Sports Analytics Institute that the Pittsburgh Penguins are using on a regular basis:


What is it?

Corsi is shots directed on the net minus shots directed on your own net. It includes all goals, shots on goal, missed shots and blocked shots.

What does it tell you?

In simple terms, who has the puck and who is spending most of their time in the offensive zone. Vancouver Canucks linemates Ryan Kesler and Mason Raymond had two of the highest even-strength Corsi ratings in the NHL last season.


What is it?

A measurement of the quality of opponents players face in a game. It is a complex calculation that evaluates every player on the ice using an advanced version of plus-minus or Corsi.

What does it tell you?

Who coaches are using against other team’s top lines. Detroit Red Wings captain Nick Lidstrom and New York Rangers forward Ryan Callahan were among the leaders in the statistic last season.

3. PDO

What is it?

The combination of shooting percentage and save percentage when a player is on the ice.

What does it tell you?

This stat is often regarded as measuring the “luck” factor, as some players benefit from extremely high shooting or save percentages not created by their own play that dramatically affect plus-minus. A player with a very high or low PDO is considered unlikely to be able to sustain that level of success or failure over time.

Little-known Boston Bruins defenceman Adam McQuaid led the NHL in PDO this season and was plus-30, a performance an advanced statistician would deem extremely difficult to duplicate next season.


What is it?

The percentage of faceoffs players are on the ice for in the offensive zone. Neutral zone faceoffs are not counted.

What does it tell you?

How coaches use their different line combinations. Vancouver’s Sedin twins led the NHL in zone start last season, as they were on the ice for almost three times as many offensive zone draws as defensive zone ones.

Teammate Manny Malhotra, meanwhile, was in the opposite role, taking mostly defensive draws, which has a negative effect on plus-minus.


What is it?

According to SAI’s definition, “PGS is the probability that a shot will result in a goal assuming an average quality shooter took the shot on an average quality goaltender.” (Unlike metrics used by Desjardins and others online, the methodology involved in PGS is proprietary and not made publicly available.)

What does it tell you?

Pittsburgh Penguins director of player personnel Dan MacKinnon lists shot quality, shot location, shot characteristics and who is on the ice when those shots are taken as the key information it provides.

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Why haven’t advanced stats caught on in the NHL?

James Mirtle, Globe and Mail, September 23, 2011

There are plenty of theories out there as to why hockey has been so slow to embrace advanced analytics the way other sports have in recent years.

The Globe and Mail asked four statistically minded people working in the NHL, either as employees or independent analysts, for their opinion as to why it’s taken so long for the trend to emerge in front offices around the league.


One of the more common theories is that NHL teams are very traditional organizations, with teams often run by large groups of former players and in much the same way they’ve been for decades.

“They’ve all grown up without these types of numbers and have to relearn the way they think about statistics,” said one staffer on a Western Conference team that is beginning to dabble in advanced statistics.

“I think what’s standing in the way of things fundamentally changing in the NHL is the backgrounds of guys who are general managers,” statistician Gabriel Desjardins added. “I think something like 20 of them played in the NHL. Just by its very nature, that’s not going to bring a lot of new ideas into the process.”


Others point to the complexity of the sport, with so many shift changes, different numbers of players on the ice in different situations and even randomness (or luck) factoring into every game.

“Hockey’s very complex,” acknowledged Kevin Mongeon, an economics professor at the University of New Haven who founded the Sports Analytics Institute with data analyst Mike Boyle. “In order to extract information that is usable on a regular basis and teams can actually make actions on it, it takes a very high, sophisticated level of analysis to be done on it.

“It’s not as simple as baseball, therefore it takes more of an investment of effort and time for the teams. That has held it back.”


Mongeon also believes there’s also a lot of confusion among teams as to where to go for analysis.

Combined with an unwillingness to invest resources into what’s a relatively new field, that helps explain why so many teams have ignored the area entirely.

“Some teams want to use analytics, but they don’t know specifically what that means,” he said. “There’s a problem in the market with what is a good analytics service to buy.

“Teams aren’t for all intents and purposes investing in major statistical groups to build that intellectual capital [the way they have in other sports] ... They don’t have that intermediate person inside the organization. And they’re not really willing to pay for it. But they’re becoming more willing to pay for it.”

Also, statistics that are perceived to be the most useful can rapidly change, something that causes confusion as to which analytics are the best for teams to turn to.

“The signal-to-noise also hurts with adoption of the newer numbers in that the perspectives can be overwhelming,” the Western Conference staffer said. “And it creates an uncertain landscape.

“A few years ago we had [statistician] Alan Ryder’s work, then everyone jumped on the Corsi bandwagon and the online community keeps chipping away at that. You don’t want to invest in a system if it won’t be the standard two years from now.”


Some of those working for NHL teams, however, argue that the quality of analysis is only now getting to the point to be really useful.

“It’s not that everyone’s been blind to this stuff forever,” said Pittsburgh Penguins director of player development Dan MacKinnon, who used SAI’s metrics extensively last season and was one of the members on the first hockey panel at MIT’s Sports Analytics Conference this year. “It’s more that, it hasn’t been available until fairly recently. The NHL didn’t even track this kind of [advanced data] until 2006 or 2007.”

Other than the Penguins, MacKinnon points to the Boston Bruins, Buffalo Sabres, Calgary Flames and Tampa Bay Lightning as teams that have begun to invest in this type of analysis.

Many of those in front offices looking at analytics are also from a younger generation, one that grew up reading about Bill James, Moneyball and some of the advanced analysis being done in other sports.

“Honestly, probably the greatest obstacle in sport is that it’s hard to strip away all the emotion and make completely rational decisions,” MacKinnon said. “That’s exactly what analytics is trying to do.

“The reason why we don’t mind being a little open about [what we’re doing] is we’re hoping to take this to the next level where we can get this data from the other leagues [like the AHL]. It’s going to take a larger community than just the Penguins to do it. If we get more teams asking for it, I think we can get that.”

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Dean, a lot of your articles can only be read when the coach logs in. The copy and paste function seems to only work then. Maybe if you edit a little then it will show when not logged in.

I am kicking myself for not watching Portland practice last spring. They had a talent id camp 5 minutes from my house. I went and talked with Mike Johnston for a bit but didn't watch them practice. I would love to have seen the music being used etc.

Bob Murdoch used stats when he was with Winnipeg and Chicago and the main one he used was based on decisions every time a player touched the puck. There is a video on this site where he is a guest speaker at my college hockey coaching class. He talks about this stat and the team covenant.

A 5% swing in decisions changes the entire game. Stewart Behie, who has a Doctorate in Engineering took the idea and created a computer program that monitored decisions. We used it at the U of C and it told everything about how effective each player was, how involved in the game and the kind of decisions they made. He took it to HC and showed them but they decided to go with the testing on how fast players skate around pylons and how accurately they shoot while standing still in front of a net.

I remember we were in the Western Finals and Willie Desjardins saw how oftern our top scorer was touching the puck and the decisions that line was making. He met with them between periods with hard data and showed the players. It made a big difference in their performance. It also influenced how we practiced.

Maybe the time has come for this kind of analysis.

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Hi Tom,

I edit each one of the articles I post. I don't just cut and paste. I don't understand why they don't always show up - unless one log's in. If that is the case, hopefully it encourages more people to sign up!!!

I want to write more personal entries but with my two kids and busy schedule, I must admit it is easier to post articles... I will try to contribute more of my own stuff - at least, that is my intent!

I coached with Mike on the National Team. I have spoken with him about players the last couple of years and look forward to our conversations. He is a good coach. I am hoping I can show Mike our 'Game Intelligence' methodology next time he comes through town.

I will review the Murdock Video - I remember him talking about the covenants, but perhaps I didn't watch long enough to hear about his statistics. Approximately how far in is it - do you remember?

I too was thinking about Stewart when I read these articles. I liked what he did for the Dinos. I believe you said he was in Saudi Arabia or somewhere? I would like to talk with him to gain a firm understanding of what he did. Perhaps you could email me his contact info (to my Shaw email account)? This might be (yet another) good excuse for you and I and John to get together over a pop...!

Doesn't surprise me that HC didn't carry on Stewart's work and instead pulled out the pylons. It is easier to supply and use pylons then teach people about the game. "Teach a man to fish..."? Sadly, we don't do enough to properly train and mentor our coaches; thus our kids develop by accident. I am becoming more and more of the impression that although well-intentioned, the longer time that administrators are removed from the daily challenges of the coaching world, they forget what the 'real world' is like; and as a result, their policy-making decisions are often out of touch with what 'we' working coaches need. I have heard rumours though, that the coach certification process within Hockey Canada will require ongoing attendance at PD clinics to maintain one's certification - so that is good news... if it is true!

John and I ran a successful dryland session for two hours Friday night, using our Game Intelligence model. We had 25 kids and about 40 parents; plus 10 soccer and hockey coaches. We received very positive feedback. I will try to post more under the 'Game Intelligence' tab when I get time...

Keeping with the analysis theme... check out this crazy discovery... if true, how would this influence our use of analytics?

Physicists urge caution over apparent speed of light violation
Scientists react with disbelief and call for repeat experiments after results suggest particles can travel faster than light

Alok Jha and Ian Sample, guardian.co.uk, Friday 23 September 2011

Scientists around the world reacted with shock yesterday to results from an Italian laboratory that seemed to show certain subatomic particles can travel faster than light. If true, the finding breaks one of the most fundamental laws of physics and raises bizarre possibilities including time travel and shortcuts via hidden extra dimensions.

Scientists at the Opera (Oscillation Project with Emulsion-tRacking Apparatus) experiment in Gran Sasso, Italy, found that neutrinos sent through the Earth to its detectors from Cern, 450 miles (730km) away in Geneva, arrived earlier than they should have. The journey would take a beam of light around 2.4 milliseconds to complete, but after running the Opera experiment for three years and timing the arrival of 15,000 neutrinos, the scientists have calculated the particles arrived at Gran Sasso 60 billionths of a second earlier, with an error margin of plus or minus 10 billionths of a second. The speed of light in a vacuum is 299,792,458 metres per second, so the neutrinos were apparently travelling at 299,798,454 metres per second.

A cornerstone of modern physics is the idea that nothing can travel faster than light does in a vacuum. At the turn of the 20th century Albert Einstein encapsulated this idea in his theory of special relativity, which proposes that the laws of physics are the same for all observers and led to the famous equation E=mc2, indicating that mass and energy are equivalent.

Brian Cox, a professor of particle physics at the University of Manchester, urged caution. "If you've got something travelling faster than light, then it's the most profound discovery of the last 100 years or more in physics. It's a very, very big deal," he said on BBC 6 Music on Friday. "It requires a complete rewriting of our understanding of the universe."

Professor Jim Al-Khalili at the University of Surrey said it was most likely that something was skewing the results. "If the neutrinos have broken the speed of light, it would overturn a keystone theory from the last century of physics. That's possible, but it's far more likely that there is an error in the data. So let me put my money where my mouth is: if the Cern experiment proves to be correct and neutrinos have broken the speed of light, I will eat my boxer shorts on live TV."

Opera co-ordinator Antonio Ereditato said his team was "recovering from the shock" of the discovery and would leave the physics community to explain the result. "We made a measurement and we believe our measurement is sound," he said. "Now it is up to the community to scrutinise it. We are not in a hurry. We are saying, tell us what we did wrong, redo the measurement if you can." He added: "There will be all sorts of science fiction writers who will give their own opinions on what this means, but we don't want to enter that game."

If the measurements are shown to be correct, physicists will have to modify their understanding of special relativity. There are several theories that could help explain the results.

Heinrich Paes at Dortmund University and colleagues believe it might be possible for neutrinos to move through hidden extra dimensions of space and effectively take shortcuts through space-time.

"The extra dimension is warped in a way that particles moving through it can travel faster than particles that go through the known three dimensions of space. It's like a shortcut through this extra dimension. So it looks like particles are going faster than light, but actually they don't."

Another potential explanation for the observation was given by Alan Kostelecky at Indiana University. He proposed in 1985 that an energy field that lies unseen in the vacuum could allow neutrinos to move faster through space than photons, the particles that make up light.

"This is a field that sits in the vacuum and as a result, things travelling in the vacuum will have unconventional properties," he said. "It may very well be that neutrinos travel faster than light does in that medium. It is not at all unreasonable that that would be the case."

Professor Dave Wark, leader of the UK group on the T2K neutrino experiment in Japan, cautioned that scientists would "require a very high standard of proof and confirmation from other neutrino experiments around the world".

Susan Cartwright, senior lecturer in particle astrophysics at Sheffield University, said there were many potential sources of error in the Opera experiment. "The sort of thing you might worry about is have they correctly accounted for the time delay of actually reading out the signals? Whatever you are using as a timing signal, that has to travel down the cables to your computer and when you are talking about nanoseconds, you have to know exactly how quickly the current travels, and it is not instantaneous."

Cartwright works on T2K, which sends neutrinos over a 295km distance. "We could certainly check this, but MINOS [the neutrino experiment at Fermilab in the US] are in a better position because we are still doing repairs after the earthquake that struck Japan."

Professor Jenny Thomas of University College London, a spokesperson for the MINOS neutrino experiment, said if the discovery was proved correct, it "would overturn everything we thought we understood about relativity and the speed of light".

Ereditato said the Opera team was going through a mix of feelings. "There is excitement, adrenaline, because you feel you have hit something hot. Another feeling is exhaustion. A third feeling is let's look again and again and think of other checks we have not yet done."

What has been discovered?

A fundamental subatomic particle, the neutrino, seems to be capable of travelling faster than the speed of light.

Where on the scale of amazing/ surprising is this finding?

If the Gran Sasso results are correct, scientists would have reason to believe that Einstein's of special relativity is wrong. This is troubling, as the theory has been tested countless times in experiments and never disproved.

The trip would take a beam of light around 2.4 milliseconds to complete, but after running the experiment for three years and timing the arrival of 15,000 neutrinos, the scientists discovered that the particles arrived at Gran Sasso 60 billionths of a second earlier, with an error margin of plus or minus 10 billionths of a second.

Since the speed of light in a vaccum is 299,792,458 metres per second, the neutrinos were apparently travelling at 299,798,454 metres per second.

What are neutrinos?

Neutrinos are electrically neutral particles that have a tiny (but non-zero) mass. They interact very weakly with normal matter, making them almost impossible to detect. Tens of billions of neutrinos pass through your fingertip every second. They are created in certain types of radioactive decay, during collisions between atoms and cosmic rays and during nuclear reactions such as those that occur at the heart of the Sun.

Are there any theories that might explain the result?

If the result is proved correct – and that is still a big if – you have to go into some relatively uncharted areas of theoretical physics to start explaining it. One idea is that the neutrinos are able to access some new, hidden dimension of space, which means they can take shortcuts. Joe Lykken of Fermilab told the New York Times: "Special relativity only holds in flat space, so if there is a warped fifth dimension, it is possible that on other slices of it, the speed of light is different."

Alan Kostelecky, an expert in the possibility of faster-than-light processes at Indiana University, put forward an idea in 1985 predicting that neutrinos could travel faster than the speed of light by interacting with an unknown field that lurks in the vacuum. "With this kind of background, it is not necessarily the case that the limiting speed in nature is the speed of light," he told the Guardian. "It might actually be the speed of neutrinos, and light goes more slowly."

Does this mean that time travel is possible?

Don't hold your breath – we won't be routinely jumping into the past in DeLoreans any time soon. If particles could travel faster than light, special relativity suggests travelling backwards through time is a possibility, but how anyone harnesses that to do anything useful is beyond the reach of any technology or material we have today.

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Long time reader (posted a few times at the hold board) and always following the conversations.

Love how a lot of people here are leaning towards the mental side of the game. A lot of great conversations. Really look forward to reading about your off-ice session and Game Intelligence training

I have been following a soccer coach from Belgium, Michel Bruyninckx, and his methods. His youtube practices definitley make his players think

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Search "Horst Wein" - he started in field hockey, then switched to soccer and even hockey! A master coach, he has helped contribute to FC Barcelona's success the past several years.


Tom (or someone) has posted a link to a horst Wein video previously - http://vimeo.com/27345178

I watched your posted link... thanks for contributing! Look forward to hearing more from you!

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Football Copernicus content if his revolution doesn't catch on

David Whitley, AOL FanHouse Columnist, Sporting News, Sept 30 2011


It never stood a chance.

The coordinator took it back to his head coach and was told why.

“Look, this is my job,” he said. “If you do something non-traditional, even if it’s the right thing to do, you’ve lost your job.”

The right thing would be going for it on fourth down and trying onside kicks almost every time.

You’re brilliant if they work, an unemployed dunce if they don’t. Most coaches would rather not take that chance.

Kelley isn’t most coaches. He runs the madcap football laboratory known as Pulaski Academy in Little Rock, Ark.

The Bruins got a lot of attention a couple of weeks ago when they took a 29-0 lead. The other team hadn’t even snapped the ball thanks to four successful onside kicks. It was X-and-O insanity. Only it wasn’t.

“The perception of craziness,” is how Kelley puts it.

There’s a scientific method to his madness, yet people view him as a football Copernicus. The father of astronomy dared to say the earth revolved around the sun. All the medieval geniuses around him just knew the sun revolved around the earth. Copernicus caught more grief than Wade Phillips. The pope declared his ideas heretical and suspended him for four centuries.

Kelley hasn’t been persecuted to that extent, but his discoveries have been largely shunned. They are slaves to tradition, which says the football universe revolves around punting, kicking and playing it safe.

Kelley went along with that until he ran across a study written by Cal-Berkeley economics professor David Romer. It was an analysis of business decisions based on NFL fourth-down situations.

It concluded that coaches punted or went for field goals far too often. I’ll spare you the arcane stuff, but the numbers didn’t lie. Kelley was inspired enough to do his own research, set up computerized tracking and challenge tradition.

At first, people thought he’d lost him mind.

“Idiot!” they’d yell when he went for it on fourth-and-8 from his own 20-yard line. But the results justified the football heresy. Pulaski, which has only 350 students, has won two state championships. The current team is unbeaten and ranked No. 1 in Arkansas’ Class 4A and No. 80 in the nation by Rivals.

Nobody’s calling Kelley an idiot now.

“I used to be called stupid,” he said. “Now they accuse me of trying to run up the score.”

He doesn’t try. It just appears that way when a team doesn’t even have a punter. Kelley got serious with the approach in 2007. Since then, you could literally count the number of punts on one hand.

The Bruins go for it even if it’s fourth down inside their own 10-yard line. If they fail, the stats say the opponent will score 92 percent of the time.

If they punt, stats say the opponent will get the ball near the 40. From there it scores 77 percent of the time.

Since it’s only a 15 percent tradeoff, Kelley will take his chances.

Never punting changes the entire offensive dynamic. Third-and-2 feels like second-and-2. It’s a nightmare for defensive coordinators and players who’ve been raised on accepted football doctrine.

Success on fourth down has an emotional punch. Since 2007, the Bruins have scored 79 percent on drives that had a fourth-down conversion. Then comes the kickoff madness.

Pulaski has 12 different onside-kick schemes, from the one-hopper to the “helicopter” to varied formations that swarm the receiving team. The only time the Bruins kick deep is when opponents put 10 players up. Even then they’ll try to bloop it to an open area and storm the spot.

Again, the math justifies the risk. Kelley said a typical kickoff is returned to the 33-yard line. If an onside kick fails, the opponent usually gets it at the 47.

He’ll risk the 14 yards to get the ball right back.

It worked to perfection against Cabot High two weeks ago. Imagine being down 29-0 before even touching the ball.

Imagine that happening in college or the NFL.

What fun, right?

Now come back to reality.

For one thing, it would be harder to exploit professional defenders than 16-year-old Arkansas kids. Even with that factored in, stats say it’s worth a try.

The football zeitgeist (pardon the academic phrase) says it’s not. As the Big 12 coach said, the numbers justify the risk, but the job risk is too great.

It’s too easy to second-guess fourth-down calls and onside kicks. If they don’t work, Fourth-and-Dumb headlines are sure to follow. The medieval mindset conditions us to reject daring new things.

There had never been an onside kick in 44 Super Bowls (other than desperation time) until two years ago. The Saints tried one to start the second half. They recovered, drove down for a touchdown, went ahead for the first time and were on their way to a 31-17 win.

Sean Payton was declared a gambling god. But if it hadn’t worked, nobody would have wanted to hear him extrapolate on statistical analysis and how the numbers justified the risk.

“The irony is it’s about winning,” Kelley said. “Even though they think this will help them win, they won’t do it.”

He’s happy doing it at Pulaski, but admits he’d be interested in trying it at a higher level. It would take a school that’s way down, wants to sell tickets and is willing to take a risk on the “perception of craziness.”

Sadly, I don’t think Kelley’s phone will be ringing anytime soon. Though he sees the bright side in that.

“I don’t want this to catch on,” Kelley said, “because we have an advantage.”

Despite all the numbers, all the success and all the fun, this beam of innovation will only shine at Pulaski Academy.

Everywhere else in the football world, alas, the sun will always revolve around the earth.

M.Ed (Coaching)
Ch.P.C. (Chartered Professional Coach)
Game Intelligence Training

"Great education depends on great teaching."

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NHL's new mathematics of winning: A fresh way of looking at NHL stats can track dominance and predict winners

Luke Fox, Sportsnet.ca, December 22, 2011

Terry Appleby is a retired Canadian board-game developer, an economist, and 20-year member of baseball's ultimate nerd group, the Society of American Baseball Research (SABR). Since a child he has been fascinated with the statistics of sports, and a lifelong basement researcher, crunching numbers and thinking about the games we watch in unique and wickedly smart ways.

When hockey writer Mark Spector, now at Sportsnet, filed a lighthearted newspaper column in October 1998 on how the Oilers' new lineup should yield eight more victories come season's end, little did he know that he would trigger Terry's beautiful mind.

"If the purpose of an NHL hockey player is to help the team win, why aren't we measuring him that way?" Terry asked himself. It was as if a Zamboni had cleaned an ice rink rutted with traditional statistics. Terry began to make fresh strides in the way he gathered and compressed goals and assists, creating new formulas and developing composite "super stats" focused on finding winners.

His fantastic findings, however, were known only to Terry and his hard drive. And his son.

For Christmas 2008, Terry's son, Marc Appleby -- an entrepreneur who impressed Canadian audiences and high-rolling investors by successfully pitching EcoTraction on Dragon's Den in 2009 -- bought his father a website to showcase all of his number-crunching. Once the father and son worked out the bugs, they brought the PowerScout system here to Sportsnet. After 13 years of scribbled notes and a gazillion hours of one passionate hobbyist's data entry, a revolutionary way of evaluating hockey players and teams (moneypuck?) is now upon us.

"I'm PowerScout's biggest superfan because I watched my dad develop it year after year, and I saw the results. I thought it was incredible: you're really telling the story behind what people think they're seeing. And it reinforces a lot of the clichés of hockey," Marc explains. "They talk about defence wins championships and you want strength down the middle. These things come out in the research. So now we've built a system that has done all the research, and we just track the numbers for people and let the numbers speak for themselves."

We caught up with Marc to better understand the NHL's new math and what it means to fans.

How is PowerScout's approach to hockey comparable to Moneyball's approach to baseball?

The statistics that come out of it and the research that we've done is based on one fundamental principle, and that's winning. And Moneyball had the same principle, basically looking at, OK, if you do this in these situations, you'll be more successful. That our research is based on winning, it helps teams make better decisions, (and) it helps fans understand what's going on with their team or their players. It gives a third category for people to follow. There's the scoring race, based on goals and assists; there's fantasy, which is everyone's pools where power-play goals and penalty minutes are worth something; and we're more reality-based. It's an honest look at what's on the ice, why teams are winning and losing. It's founded on research that says, OK, if you do these things, you have a higher chance of winning games, winning championships.

What first inspired this research?

When Mark Spector's piece in 1998 came out and said, hey, everybody's looking at goals here, but everyone cares about winning. They don't care about goals; they want to win, they don't care how it happens. So he says, "Why aren't we measuring players this way?" And that was three years before Bill James came out with his baseball Moneyball. His research predated what James was doing, but of course, (my father has) been in his basement for 13 years. My dad's been part of the Society of American Baseball Research for 20 years. He's a member of SABR, which is the baseball nerd group, of which Bill James is a member, and my dad sits on the Business of Baseball committee and the analysis committees. He's a massive baseball fan, so he knew a lot of the research that was being done in Moneyball. He was more inspired by Mark Spector and his article in the Edmonton Journal taking a look at the Oilers in the upcoming season and saying, I think they're going to be eight wins better, based on all the players coming in or going out. That was the light bulb. (Terry) said, "Wait a minute. This is the way we need to evaluate players." So he went back and said, How do we do this statistically? And once the real-time statistics came out and you could get ice time per player, that allowed him to say, OK, for the amount of time this guy was on the ice, this is how much he contributed.

PowerScout's current MVP rating has defencemen in the top three spots, led by Brain Campbell. In your opinion, then, should Campbell be voted MVP of the league?

Well, I think you have to be on a playoff team to be MVP. How the MVP rating is calculated is: How much better is he, based on his ice time, than if he were to be replaced by someone on the minors? Brian Campbell has a certain performance, but if I replace him with some no-name, that guy will also make some contribution. So it's the percentage better he his than a guy who could replace him. Right now, everyone's wondering why Florida's so successful, and part of it is Campbell's stability on the back end, creating offence. For Florida, he is their MVP.

A lot of offensive defencemen will lead their team in MVP because they're contributing to wins. It's all about contribution to the team, and defencemen play a lot more time than wingers. A winger might play 15 minutes; a defenceman's on the ice for 20-25 minutes. He's on the ice for half the game. Plus, each forward plays a third of the ice [surface]; a defenceman plays half the ice, and they're the last line of defence. So defencemen, and particularly offensive defencemen, are rated higher.

Which NHL statistic do fans and media overvalue?

The most overrated statistic is penalty minutes. And for most people in fantasy leagues, penalty minutes are great. You want your guy to get fights and take penalties. In reality, who wants to take penalties? This is a negative. You look at Campbell, he's disciplined. Where if you look at (Dustin) Byfuglien, some people thought he should've been MVP last year, but he was taking almost a penalty-and-a-half per game.

In our research, we've found that penalty killing is almost four times more important than power play. That was a massive finding. You're not going to lose a game if you have a bad power play, but you will if you have a bad penalty kill. Why are the Leafs struggling? It's their penalty kill.

And in the playoffs, we found that one of the most important stats is goaltending performance against only the top 10 teams in the league, so we look at that and penalty killing: the two major drivers of playoff success.

Power-play goals and penalty minutes are dismissed. Everyone likes goals, so they talk about how the power play is doing. Penalty kill is not as sexy, but it's almost four times more important.

There's a misconception that toughness equals penalties, but in reality it's about discipline. Toughness comes from hits. When we look at players, we look at 12 skills. It's very much like the quarterback rating in football. Each quarterback is rated between 75 and 150 based on all these stats, and no one really knows how it's calculated, although it's on Wikipedia, but based on all these metrics, it gives you a sense of performance. We know 150 is an incredible game, and 100 is about average.

Is the eventual goal to have stats like your MVP rating appear in a player's stat line when they're on TV?

Absolutely. If there's one stat that I think can revolutionize hockey, that would be Game Dominance. It's the ultimate context to NHL scores. We're an analytical company, so there's a niche market there. But every fan needs to get their score; everyone wants to know, hey, what happened in the game last night. PowerScout allows you to see that score but then also see which team outplayed the other in percentage terms. It's not a new stat that people need to learn; it's percentages. You can see that a team won 2-1 but was outplayed 70% to 30%. You get the context for the game. That's what I want to get to for out-of-town scoreboards: "Oh, 2-1 but they're getting outplayed." That little bit of extra context that allows media guys to present a better story at a glance. That's one statistic I think could become part of the box score.

Why should Sportsnet.ca users care about these Game Tracker and Game Dominance graphs?

It's the single best way to scoreboard-watch, to get the feel of the game at a glance. If you're a Leafs fan and you're at a restaurant or in a movie theatre, pull up your phone and you can watch the game in real time and see how it's playing out. It's the ultimate platform for fans to get and the score and the context in one second. People want scores. Where do they go for scores? A website. And it's interesting to go back in the archives. For the rest of hockey history, every game now will be archived in one little picture, never to be forgotten. I find that really powerful.

Explain the Momentum Meter in simple terms.

The momentum meter tracks how fast shots happen in real time to measure team effort. We're trying to create a visual fingerprint-and I like the word "fingerprint" because every game is unique-of every game's momentum swings for each team. Every 30 seconds, we look at how many shots that team had. If they had a lot of shots, their momentum goes up; if not, it goes down. What you're able to do is capture how hard teams are trying. Shots are an estimator; it's the most basic stat you could use to drive something like this, which everybody understands. If you take a shot, you're in the opposition's zone. It's a proxy for zone-time. And it shows how teams react to power plays and fights and goals.

One of our readers wrote that using shots on goal can be misleading. One team could be taking a weak shot every 30 seconds and not generating quality scoring opportunities, whereas the other team could be taking a shot every five minutes but giving itself great chances to score. How do you respond to that?

Absolutely. We're always looking to refine it. Certainly quality of shots is important. But how do you rate the quality of every scoring chance unless you're watching every game? Or unless you're getting location data-where the shot was taken-which the league does not allow us to get. NHL.com is the only site that can access where the shots are taken from and if it's a wrist shot or a slap shot; they retain that for their Game Center Live. You could get scoring chance data, but shots are the fundamental building block. If we went to scoring chances, you'd be missing part of (the picture). There's the odd shot from the other end of the ice, sure; usually when you get a shot, you're in the other team's zone. You get a sense of who's attacking and who's playing defensive by looking at shots. And if you watch a game while you have the graphs going on, it almost mimics the sense of the crowd. It tells you that much about the game; that's why I find them so powerful. If you missed any part of any game, you go back to that graph, and in three seconds you know exactly how it played out as if you were there.

What's the biggest flaw of the PowerScout system?

I haven't heard negative feedback yet. Some people think we shouldn't use giveaways and takeaways. We've been asked why we're not using plus-minus or game-winning goals or power-play goals.

Why aren't you using plus-minus?

We're trying to look at player skills. When looking at an individual player's statistics, plus-minus is a team statistic that's applied to a player. We know that the trouble with plus-minus is that he could be just coming onto the ice or just going of the ice or not involved in the (goal-scoring) play. Players on really bad teams have low plus-minus because they lose a lot, not because they're a bad player. It's not an individual skill. Much like power-play goals. Goal scoring is the skill. Power-play (and game-winning and shorthanded) goals are just when they happen. But a goal is a goal is a goal in our system. We don't care if it's power-play or shorthanded. It's a skills-based approach. Takeaways and giveaways are a small part of the model, and we're the first people to incorporate all the individual statistics the NHL uses into one single stat, which is like the quarterback rating.

Why don't you factor in faceoffs?

Everyone says, "Well, for centres, how come you're not using faceoff winning percentage?" There's some faceoffs that are important, but for the most part, they're not. Blue lines? Centre ice? The best faceoff guy is 60% or 55%; the worst guy is 40%. That's a difference of one faceoff for every 10. Some faceoffs are important, but say you win the centre-ice faceoff. What do you do? You go and dump it in the zone and give the other team the puck right back. There are so many moments after a faceoff when possession changes hands, it's obscene to think that faceoffs are a measure of possession. But we measure it because it's the only set piece that happens in hockey. It's easy to measure. But in terms of its impact on winning, we feel it's overvalued.

Why bring this system to Sportsnet? Why not bring it to a small-market team and try to build a winning team for cheap?

From a business perspective, it's costly to go after fans individually. Trying to do Google ads and trying to attract fans one by one, it's time-consuming. I knew I had awesome content that could help a Sportsnet take their stuff to the next level. On a whim, I said, I want to talk to the networks. Ultimately we want these graphs on TV. What better way to do out-of-town scoreboard? This is cutting-edge, revolutionary stuff, totally designed for TV. We talked to other networks as well. Sportsnet felt like the best fit because they're the leader in NHL broadcasts in Canada; they show the most games. They're regionally based, and they're in a position for growth. I felt good rapport with the Sportsnet team.

I'm an Oilers fan, I'm from Edmonton originally, live in Ottawa now, and I get a lot of Sportsnet games. I liked where the branding was going. We are still going to the teams, and there's a challenge around that because we have out information on the web and possibly on TV. The teams might say, "Why do I want you guys? You're giving away all your stuff for free?" Ultimately, there's so much that can be done. A small portion sits on Sportsnet, stuff for the fans to understand. If we look at the Trade Maker, Sportsnet will have five variables to post; the teams will get 12. There's enough content there for everybody.

I'm trying to give a legacy for my dad. He's a superfan who's done so much for so long. A brilliant economist and sports fan, and he sees the game in a way that needs to be shared. I want to help you guys be the leading sports broadcast starting with trade deadline day. It was kind of a no-brainer.

M.Ed (Coaching)
Ch.P.C. (Chartered Professional Coach)
Game Intelligence Training

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Gregg Drinnan, Taking Note, Jan 17 2012

If you are interested in a statistical analysis of the WHL and its teams, visit http://www.masseyratings.com/

This website rates the WHL’s 22 teams, taking into account such things as estimated team strength, offence, defence, home-ice advantage and strength of schedule.

The Blazers went into last night’s game ranked No. 2, behind the Americans. Kamloops is ranked highly in all categories except home-ice advantage (11th) and strength of schedule (20th).

The Blazers are 17-6-0 at home. And, as mentioned earlier, they have played some of the poorer teams of late, which has resulted in the strength of schedule ranking.

Interestingly, the Americans are ranked 21st in strength of schedule, with the Portland Winterhawks, who are third overall in the Massey Ratings, at No. 19.

M.Ed (Coaching)
Ch.P.C. (Chartered Professional Coach)
Game Intelligence Training

"Great education depends on great teaching."

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Goalie Analytics

Ritch Winter (agent), Agent of Change, February 8, 2012

(Check this site - it is pretty interesting... http://www.theagentsofchange.com/ )

@HockeyAgentDad tweeted: Why is Devan Dubnyk (not a client) statistically the best starting goalie in Alberta? He may be the real meal deal.

In response:

@JayBrookman49 Tweeted – Enlighten us, unless Feaster just moved Kipper I object…

@YuriThomas99 Tweeted – what advanced goaltending stats do you like to evaluate with?

In preparing for free agency every year, I have started to employ mathematical analytics more and more to advise clients on things like target teams. Employing various statistics to more accurately project future team performance.

Initially, my foray into statistical and economic analytics began shortly after Marian Hossa approached me about representing him three years ago before he was traded to Pittsburgh. After meeting him in Atlanta, it became clear he was going to be much more interested in playing for an “elite” organization than in money alone.

After we met in Atlanta, I began devising a formulaic approach to measuring and projecting “elite” performance to assist with advising him. In the end, we determined that Marian would only consider teams that we determined had a high statistical probability of recording 100 points consistently over the five years after he became a free agent. We considered projections beyond the 5 years to be less accurate and not worthy of inclusion into our analysis even though the deal Marian would sign would extend beyond 5 years. We took this approach due to the fact contract terms for each team’s existing players were most often 5 years or less and who could project who would stay. So we focused on the 5 year period following the July 1 date on which Marian would become a free agent following the Cup run he had with Detroit.

The analytics proved to be amazingly accurate. Marian was the only player in NHL history to play in the Stanley Cup finals three years in a row with three different teams. So we made two very good choices. The results, as Marian shared all this with others, became a huge competitive advantage as an agent. No other company had taken the time to accurately measure the prospects for their unrestricted free agents. We had successfully placed a player on two Stanley Cup finalists and one winner in three years. Bookies would have trouble competing with that.

In preparing for free agency last year for Ilya Bryzgalov, we began looking at goaltending analytics more specifically. It was the first time a goalie with the statistics Bryz had would hit the open market at his age. In tandem with Michael Schuckers, a professor at St. Lawrence University, we built models designed to determine goaltender performance by team for Ilya. Some interesting information grew out of that.

For example, as Michael focused on Ilya’s save percentage in various situations and looked at adjusting a goaltender’s save percentage to the types of shots generally faced by goaltenders, some interesting bits of information began to surface to assist with the analysis we were preparing for Ilya as well as in general. The specifics as they relate to Ilya are confidential, but some of the more general insights we uncovered have widespread application and are, for the most part, just very interesting. Now I do not think that Michael Schuckers research is determinative, but it does suggest that a further course of study is required in all cases before picking up a new goalie or signing one of your existing roster players. Current NHL statistics do not provide the whole picture. Relying on them alone is risky.

Instead of comparing goaltenders by save percentage, Schuckers has developed a methodology that measures goaltenders by a more accurate measure, in my opinion. He calls it the “Defense Independent Goalie Rating” or DIGR. It is designed to create an adjusted save percentage number that more accurately measures goalie performance. Not a perfect measure, but more accurate than save percentage is on its own.

For example, we all know that a goalie who played in a game where he faced 10 breakaways and 30 shots as compared to an opposing goalie in the same game who faced 30 shots, but no breakaways and 20 shots on goal from outside the blue line, most likely had a better game - assuming each let in one goal and otherwise faced very similar shots. In this case, save percentage alone doesn’t tell us very much. Both had an identical save percentage, but very likely just one of them was named a star of the game.

The point is that some teams have such a strong defense that it results in their goaltenders facing a much smaller number of quality scoring chances than others do. In these cases, a higher save percentage on lower quality scoring chances that end up in shots on goal, would be less meaningful.

So how does one address this statistically?

Schuckers has come up with a great approach. His DIGR ratings begin with him first analyzing all of the shots on goal in the NHL in a given season. Then he determines, based on all of the shots taken in all of the regular season games, what types of shots goalies face on average per game - five from the left slot, two shoot-ins, etc.

After doing this, he determines each goalie in the league’s save percentage on each type of shot that the average goalie would face. So, what would each goalie save if he faced the shots each goalie in the league faced, on average? This gets you a goalie’s DIGR – his save percentage on the shots taken on average during an average NHL regular season game. It creates a much more level playing field for comparative purposes than raw save percentage.

This methodology provides us with an adjusted save percentage accounting for the quality and distribution of shots faced after taking out empty net goals, penalty shots and shootout shots. To calculate the DIGR for all NHL goalies, Schuckers has to build a model of each goalies performance during the applicable season and then mapped every shot taken by the entire league to the individual goalie map before applying each goalies save percentage on each type of shot to the average shots per game. The DIGR allows for a direct comparison of goalie performance since it is based upon the exact same types of shots, not just the shots that an individual goalie faced.

A few interesting points taken out of the league-wide analysis include:

Not surprisingly last year, Tim Thomas was the top goalie, followed by Cory Schneider and Roberto Luongo. While it is not a surprise that Thomas is at the top given his phenomenal year, the difference between Thomas and the second best goalie shrinks by about 0.5% after accounting for the difficulty of the shots he faced. Thomas had a great year but was helped by a strong defense.

Jonathon Quick had the easiest shots in the NHL and Cory Schneider faced the hardest set of shots.

Among goalies facing 1000 shots or more, Jaroslav Halak had to face the most difficult shots, on average. You have to think that will change this year under Ken Hitchcock.

Jonas Hiller and Bryzgalov are the only two goalies to appear in the top 10 of the DIGR for both the 2009-10 and 2010-11 seasons.

It doesn’t take a genius to figure out that the Calgary Flames had a more accomplished defense last year with the likes of Mark Giordano (my client), Jay Bouwmeester (not a client) and Robyn Regehr (not a client) as compared to the Edmonton Oilers. So, you would think that Miikka Kiprusoff faced much easier shots to stop on average than the goalies in Edmonton. It turns out that this was indeed the case and it dramatically affects the way the two teams should have evaluated their goaltender’s performances last year.

Is Kipper a worse goalie than Devan Dubnyk?

As the chart below displays Devan Dubnyk was among the top 10 goaltenders in the NHL in adjusted save percentage or DIGR and Mikka Kiprusoff was among the worst. If Dubnyk faced the shots that goalies on average see each game, he would have recorded a .922 save percentage (or DIGR), 8th in the NHL. Had Kiprussoff faced those same shots, his save percentage would have been .902, 45th in the league.

Take a look at the chart below:

Rank Name DIGR RawSV% Shots Faced Avg Goalie Salary10-11
1 TimThomas 0.9312 0.9386 1808 0.9184 6
2 CorySchneider 0.9285 0.9253 669 0.9009 0.9
3 RobertoLuongo 0.9269 0.9275 1752 0.9104 10
4 JonasHiller 0.9269 0.9249 1452 0.9067 4.5
5 IlyaBryzgalov 0.9234 0.9211 2103 0.9121 4.5
6 CamWard 0.9232 0.9221 2336 0.9123 5
7 Marc-AndreFleury 0.9227 0.9189 1738 0.9134 6
8 DevanDubnyk 0.9224 0.9164 1101 0.9067 0.8
9 CoreyCrawford 0.9219 0.92 1538 0.9109 0.85
10 CareyPrice 0.9218 0.922 2142 0.9132 2.5
11 BrentJohnson 0.9214 0.9236 602 0.9144 0.6
12 PekkaRinne 0.9204 0.9293 1881 0.916 2.8
13 HenrikLundqvist 0.918 0.9204 1961 0.9159 7.75
14 JaroslavHalak 0.9178 0.9117 1483 0.9055 2.75
15 TomasVokoun 0.9177 0.9208 1705 0.9152 6.3
16 OndrejPavelec 0.9177 0.9153 1700 0.9101 1
17 TuukkaRask 0.9176 0.9183 857 0.9143 1
18 SergeiBobrovsky 0.9173 0.9167 1500 0.9103 0.9
19 SemyonVarlamov 0.917 0.9223 759 0.9165 0.77
20 MichalNeuvirth 0.9164 0.9156 1280 0.9143 0.77
21 RyanMiller 0.916 0.9157 1958 0.9148 6.25
22 BrianBoucher 0.9159 0.9156 900 0.9187 0.93
23 JamesReimer 0.9141 0.9222 1131 0.9184 0.56
24 JoseTheodore 0.914 0.9178 961 0.9158 1.1
25 JonathanBernier 0.9139 0.9098 654 0.9176 0.77
26 AnttiNiemi 0.9138 0.9175 1745 0.9158 2
27 CurtisMcElhinney 0.9137 0.8997 708 0.9056 0.57
28 DwayneRoloson 0.9136 0.9138 1519 0.9196 3
29 MathieuGaron 0.9132 0.9027 884 0.9099 1.2
30 KariLehtonen 0.9125 0.9152 2029 0.9183 2.7
31 JohanHedberg 0.9122 0.9104 748 0.9134 1
32 CraigAnderson 0.9121 0.9157 1519 0.9182 2.13
33 NiklasBackstrom 0.912 0.9184 1531 0.9205 6
34 ScottClemmensen 0.9112 0.9102 835 0.9186 1.1
35 AnteroNiittymaki 0.9101 0.9018 611 0.9105 2
36 MartyTurco 0.9095 0.8974 799 0.9129 1.3
37 JonathanQuick 0.9091 0.9162 1634 0.9208 1.9
38 MartinBrodeur 0.9087 0.9057 1305 0.9177 5.2
39 JonasGustavsson 0.9071 0.8914 617 0.9121 1.3
40 JimmyHoward 0.9067 0.91 1801 0.9137 0.8
41 ChrisMason 0.9066 0.8921 853 0.9068 1.6
42 SteveMason 0.9064 0.9002 1503 0.9123 0.77
43 Jean-SebastienGiguere 0.9051 0.9029 762 0.9191 7
44 DanEllis 0.9043 0.9003 1083 0.9143 1.5
45 MiikkaKiprusoff 0.902 0.9058 1910 0.9198 7
46 PeterBudaj 0.9019 0.8961 1232 0.9119 1.25
47 BrianElliott 0.9 0.8947 1520 0.9126 0.9
48 NikolaiKhabibulin 0.8999 0.8917 1385 0.9068 3.75
49 RickDiPietro 0.8925 0.8847 772 0.9077 4.5

What does all this mean? It suggests that Devan Dubnyk, had he played on the average NHL team, would have been a top 10 NHL goalie based on his performance last year and Miikka Kiprusoff would not have cracked the top 40. It’s interesting, but not determinative. Just because shots came from the similar location in the DIGR analysis does not mean they were of the same quality of shots.

What is clear though is that this suggests further research, perhaps via in-depth video review, is required to test if the DIGR analysis is accurate in each case. That relying on save percentage alone just doesn’t provide a full and clear picture of goalie performance.

DIGR clearly makes the case for the Oilers giving Dubnyk the reins and seeing, with an improving defense over the next few years, if Dubnyk (not my client) is the guy. The stats seem to suggest he is. Time will tell. It’s much more difficult to be a top go-to guy than a back-up given the additional pressure, but Dubnyk appears, based on 35 games last year to be ready.

In looking for additional support for the performance of the starting goaltenders in Alberta last year, we looked at three star selections. Now, these are subjective of course, but they do at least suggest that in the opinion of at least one hockey expert who was “actually” at the game that the goaltender was among the best players on the ice. Looking at last year’s three star selections, Devan Dubnyk was named a game star 13 times (37% of the time) and Kiprusoff just 17 times in 71 games (24% of the time).

What it all suggests is that Devan Dubnyk may be the best starting goaltender in the province last year, and may soon establish himself as the best going forward..

In the end, who really was the best starting goalie in Alberta last year (I recognize that starter usually means majority of the games, but in Dubnyk’s case he was the starter at year end last year so we went with that)? I don’t know. What is clear however is that Devan Dubnyk with a regular save percentage of .916, a DIGR of .922 in the games he played outperformed Miikka Kiprusoff and gave the Oilers a chance to win most nights when there play really didn’t dictate that.

This season to date, Kipper boasts a .920 save percentage as compared to Dubnyk’s .908. With no DIGR to rely on yet, the jury is still out, but it looks like Kipper is winning this year’s goaltending Battle of Alberta with a solid bounce back season behind a defense that missed Mark Giordano for much of the year and lost Robyn Regehr to trade.

All we can say for sure is that all this brings to light a unique look at the goalie position that suggests current statistics, like was determined in baseball – only tell half the story. By way of example, can you tell me what the second assist actually measures? What value can it have expect in the case of goals like the one Brandon Prust set up in the Rangers win against the Flyers on Super Bowl Sunday. Check it out:


Now if Kipper leads the Flames to the playoffs this year – and he could -- one will have to take a closer look at why. But, if nothing else, Oiler fans have to like the fact that the young goalie tending pipes for them now, might just be the real deal.

As you look at hockey games, look deeper. Think harder and ask yourself the tougher questions.

Is our goalie that good? How close are we to elite status? Looking deeper, going further and analyzing all this more effectively is what great teams do. Some intuitively, some with an increasing reliance on statistics and analytics and some with management teams that have vastly superior educations than their competitors.

Take the Stanley Cup finalists last year. The Bruins were run my three Harvard graduates. The other, Vancouver, was led by a group of well educated lawyers and businessmen. That is what wins nowadays.

M.Ed (Coaching)
Ch.P.C. (Chartered Professional Coach)
Game Intelligence Training

"Great education depends on great teaching."

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Lost in translation: MIT Sloan Sports Analytics Conference
Former NBA coach Jeff Van Gundy, Bruins general manager Peter Chiarelli and Indians president Mark Shapiro were all featured on panels in Boston.

Kevin Nielsen | March 7, 2012, Twitter @Kevin_H_Nielsen

BOSTON -- As I detailed yesterday, I was down in Boston over the weekend at the MIT Sloan Sports Analytics Conference. And as promised, here are some of the more interesting stories or things I learned when I was down in Beantown.

Excluding baseball, most of the major sports panels can be boiled down into a couple of major thoughts.

One of the first panels I attended featured Toronto Maple Leafs general manager Brian Burke, Peter Chiarelli of the Boston Bruins, and Michael Shuckers, who is the Associate Professor of Statistics at St. Lawrence University.

As always, Burke was cantankerous (although part of that may have been due to the fact that he would fire his head coach later in the day). And while he may have been cantankerous, he was also enlightening at times.

At one point he said,

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Burke: in hockey stats are like lampposts to a drunk. Useful for support but not really for illumination.
2 Mar 12

I doubt that most analysts would argue with him there.

Later in the day, during the baseball session, Indians president Mark Shapiro said, "No machine ever spits out an answer. They do spit out a lot of great ideas."

Back to the hockey panel.

At one point Shuckers told the panel that he believed faceoffs were overrated. Only one in 100 ever result in a scoring chance. The panel immediately direided him and dismissed him after that, and he seemed rattled from that point forth.

It's not that what he was saying was necessarily wrong, but it was how he presented the idea to the rest of the panel that was wrong.

This was really a running theme throughout the conference.

How do the analysts get their ideas across without offending the higher-ups or confusing upper management, players or coaches? Analysts aren't claiming to be superior, but that the languages the two sides speak are very different.

One way that the soccer analysts do so is by cutting out some of the numerical data in their reports, replacing some of the math with video.

"Making it relevant for the players is one of the real challenges for us," said Steve Houston, head of technical scouting for Hamburg F.C.

Steve Brown, an analyst at Everton Football Club, took it a step further when he explained, "The data and numbers are one thing, but if you don't have the video to go with it, it will be a tough sell to players."

Houston said he is amazed at how far the use of stat analysis has jumped over the last year, but Scott McLachlan, the head of international scouts for Chelsea, said there was still a ways to go: "I still think there's a glass ceiling as far as team's seeing value in analytics."

While there were many ideas and guests at the conference over the weekend, one of the major flaws of the invited speakers was that they were unwilling to share ideas.

It is understandable as many of the speakers had opponents luring nearby, but it was frustrating nonetheless.

Fanalytics: One of the more interesting panels over the weekend was entitled Fanalytics and it featured Tim Brosnan (Major League Baseball), Drew Carey (Seattle Sounders), Nathan Hubbard (Ticketmaster), Jonathan Kraft (Patriots), and John Walsh of ESPN.

They discussed three major subjects which should be of interest to readers.

The first was ticket pricing, leftover tickets and the secondary market.

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Hubbard: secondary ticket market is successful because we suck at pricing.
3 Mar 12

He said that 25 per cent of tickets for sporting events go unsold and that teams should be using dynamic pricing. Dynamic pricing would be comparable to how airlines price tickets. The cost of the tickets should go up or down depending on demand.

Hubbard's example was the Jeremy Lin effect. Teams need to be prepared to boost prices for games that suddenly attract special interest and high demand, which makes sense, but there are a couple of flaws with the idea.

Kraft believes that "dynamic pricing devalues the brand for baseball."

Teams are also afraid of upsetting season ticketholders who will have paid a set rate for their tickets and might suddenly feel cheated if the person next to them had spent significantly less for their seats.

Clearly another danger for fans would be that teams occasionally push prices up to sell seats but never cut prices (think: the cost of gasoline for your automobile).

Brosnan said, "Proper pricing is going to take care of the secondary market."

Maybe, but it hasn't worked thus far.

Another issue that the panel looked at was the effect of social media at the games and for teams and leagues.

During last year's home run derby, Major League Baseball had players tweet live during the games. And when certain players sent messages, the TV ratings spiked, according to Brosnan.

He was not worried about the effect of social media on ratings, explaining, "I think we are going to be able to use social space to drive people to television."

Hubbard said:

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In game twitter activity up seven times year over year.
3 Mar 12

He brought up another interesting point about Twitter's value.

"On average, every time someone tweets their seats, it is worth $20 to Ticketmaster."

When asked the value of tweets versus Facebook posts, he said the posts were only worth about $6.

The last issue that teams are facing with regard to social media is having enough bandwith to deal with the growing use of electronic devices at sporting events.

Kraft said the Patriots have beefed up the bandwith at Gillette Stadium but that it would cost tens of millions of dollars in order to effectively allow every customer to have total access to everything, like video on demand.

There is one silver lining to that note, however, as he said, "Analytics will allow teams to see what their fans are trying to do."

The plus side to that is, teams will be able to better service the fans, but the minus side is that fans' privacy will become an issue.

NOTES AND QUOTES: Houston: "About 99 per cent of scouting is who you don't sign."

Rockets general manager Darryl Morey on coaches being fired at a higher rate than GMs: "I think GMs should be fired more often."

Saints owner/executive vice-president Rita Benson LeBlanc's Super Bowl ring was almost the size of her hand. Even from the back of the room it looked massive.

More Morey. This time on the star player's influence: "Power flows to the top 20 players in the (NBA). They have a bigger win impact than in other sports."

More Houston: "There are 10,000 (soccer) players around the world. How do we effectively evaluate all of them with a staff of 10?"

Bruins general manager Peter Chiarelli: "A little more (cost) uncertainty this year, and that's probably why there wasn't as much movement at trade deadline."

Chiarelli said when he was in Ottawa that the team did some research into drafting, and one of the conclusions was that "weight is much more important than height when scouting players."

Former Rockets coach Jeff Van Gundy on the Charlotte Bobcats : "They're trying to be bad, and the league rewards it."

Kevin Nielsen @Kevin_H_Nielsen

Quit calling it a tv. Quit calling it a laptop. It's just a screen. - John Skipper, ESPN president
2 Mar 12

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Video of the 2012 Hockey Analytic panel


Interesting.... Burke is really a character. Although he comes across as stubborn to me.

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For now, speed of game outpaces analytic angle

Fluto Shinzawa, Boston Globe, March 25 2012

On March 13, with his team down, 2-0, to Philadelphia with five minutes remaining in regulation, Devils coach Peter DeBoer did something that would have startled most of his counterparts. During four-on-four play, he yanked goaltender Martin Brodeur and replaced him with forward David Clarkson, leaving the net empty.

The brassy move caught the attention of Michael Schuckers, associate professor of mathematics at St. Lawrence University. Schuckers doubles as the cofounder of Statistical Sports Consulting. In that position, he consults with NHL teams, using data to promote less-considered approaches.
For example, signing a mid-tier goalie and a forward instead of focusing all resources toward an elite puck-stopper. Or that winning faceoffs isn’t as important as coaches believe it to be. Or pulling the goalie earlier.

Schuckers bases the latter proposal on a paper by David Beaudoin and Tim Swartz, based on data from the 2007-08 NHL season. The researchers concluded that in such a scenario as New Jersey’s (trailing by two goals with six minutes left), the losing club should pull its goalie far sooner than with 1:30 remaining, the traditional mark when coaches consider the maneuver.

“If you’re in a situation where you’re pulling your goalie, you’re obviously already in a spot where you’re likely to lose,’’ Schuckers said. “You’re down a goal or two goals. You’re likely to lose and get no points.

“The strategy, admittedly, is a risky one. But it’s one which can pay off. If you pull your goalie with 4-5 minutes left, yes, you’re probably still going to lose. But the chance you get some points out of the game improves drastically.’’

With 4:49 left in regulation of that Flyers-Devils game, Danny Briere scored an empty-net goal. Philadelphia won, 3-0. But Schuckers still believes the Devils made the right move.

“By giving yourself an extra attacker, you’re increasing the probability you’re going to score a goal,’’ Schuckers said. “Over the course of repeating that strategy in an 82-game season, it eventually pays off.’’

That scenario and its outcome illustrate the challenge Schuckers and his colleagues face when pitching their theories to hockey’s gatekeepers. Earlier this month, Schuckers participated in a panel at the MIT Sloan Sports Analytics Conference. Also on the panel were Bruins general manager Peter Chiarelli, Toronto GM Brian Burke, NBC analyst Mike Milbury, and former NHLer Tony Amonte.

Burke dominated the discussion, downplaying the significance of the oft-cited but irrelevant plus/minus statistic, which largely reflects whether a player is on a good team or a bad team. (See Jeff Schultz’s plus-50 in 2009-10 or Tim Gleason’s minus-11 in 2010-11.)

But Burke also emphasized that he prefers the traditional methods of scouting. He noted that he watched just one of Ryan Kesler’s shifts at Ohio State to decide that he would draft the center in the first round of 2003. Burke also acknowledged scouting Wayne Simmonds as a junior multiple times and not seeing anything to command his attention.

Like most in the game, Burke endorses the use of experienced bird dogs in pro and amateur rinks to evaluate players and determine who stands above the rest.

As for the statistics gathered and applied by Schuckers and others in analytics, Burke used the metaphor of a lamppost for a drunk: useful for support, but not for illumination. You could say there is resistance.

“You still have a culture of hockey that is very old-school,’’ said Schuckers. “There’s plenty of skepticism in hockey for the role that hockey analytics and statistics can play.’’

Schuckers acknowledges the hurdles analytics must overcome in hockey. The practice has become standard in baseball, where the sport’s rhythm makes it perfect for statistical analysis.

Hockey, however, is a chain reaction of events that unfold rapidly. Take, for example, Chris Kelly’s goal in the Bruins’ 8-0 thrashing of the Maple Leafs last Monday.

That Kelly scored on Toronto goalie James Reimer is a static piece of information, of little use.

But by breaking down the series of events that led to the goal, the Bruins could accrue some valuable data. The goal took place in the first period. The scoring chance, which started off a Luke Schenn turnover, started against the left-side boards. It happened on a one-man forecheck. The Leafs had just played D-to-D, with Jake Gardiner passing to Schenn. Kelly scored on his backhand.

By examining each component, the Bruins could, for example, roll out a specific forecheck for a certain stage of the game against certain opponents.

However, to break down a 60-minute game into hundreds of events requires more video tracking and analysts to follow each sequence. Neither the NHL nor its teams currently use enough resources to gather the raw data.

“We can go through the play-by-play file and the files of NHL records of events in a game,’’ explained Schuckers, referring to the real-time data, supplied by off-ice officials, that the league currently tracks. “Take the beginning of a game. There’s a faceoff to start the game. About 40 seconds later, we have a shot, a shot by the team that won the faceoff.

“We know they won the faceoff. We know, 40 seconds later, they took a shot. What we don’t know is all those things that happened in between. Did they win the faceoff, go back into their zone, and organize the attack? Or did they immediately go into the offensive zone and pass it around for 30 seconds?

“Not knowing those pieces of information makes some of the in-game stuff hard to do.’’

It will take several years for analytics to gain relevancy in hockey. The NHL would have to install additional cameras in every rink to capture each event more thoroughly. Hockey-savvy statisticians would have to track every sequence.

Even if enough data is collected and analyzed to uncover trends, coaches must embrace the information, then convince their charges to carry out certain tasks on the ice. In its current state of infancy, analytics projects to be more helpful for management in player evaluation than for coaches, because of the sport’s speed.

“You might have six things that analytics tells you,’’ said Schuckers, repeating an anecdote he heard from Celtics assistant GM Mike Zarren. “Four of them, you’re confident enough to take to the coach. The coach is confident enough to tell two of them to the player. If you’re lucky, the player will execute one of them.’’

One hand or two?

Under former coach Ron Wilson, Toronto defensemen were encouraged to keep both hands on the stick. That way, they could be stronger on pucks and more forceful at swatting away opponents’ sticks. The Bruins coaches teach their defensemen to lead with their sticks with one hand and aim for the puck. With their other hand, they can lean on the puck carrier. For example, if a forward is trying to swing wide, the defensemen are taught to reach with their sticks with one hand, which gives them better reach. If the forward then tries to pass, the defensemen has a hand free to attempt to swat the puck away. In tight, the one-hand approach also works. “You use one hand with stick on puck, then push the puck,’’ Johnny Boychuk explained. “Then you can push him at the same time with your other hand.’’

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Like to a four part series that is to long to copy and paste here. More hockey stats....

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Excellent detective work Eric! Can't believe I missed this, but I haven't been scouring the web as much these days... my bad!

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Power plays, not goal scoring, down in NHL

Rory Boylen, The Hockey News, 2012-03-27

The phrase “Dead Puck Era” has a lot of negative connotations to it. When you hear it uttered, you picture slow-moving board play, hooking, holding, a lack of scoring chances and just a dreadful overall entertainment experience. The NHL spent a year trying to move away from this style and the hockey we were left with when the 2005-06 season began was fittingly dubbed ‘The New NHL’ and provided a fresh take on the age-old league.

Coming out of the lockout, goals were soaring. The 6.05 goals per game being scored in 2005-06 was the highest average since 1995-96 and this was viewed as a victory for all.

Ever since then, the entertainment value has been held up to this number, which was derived from what was essentially a tryout season for the new rules. As goals per game dropped from 5.70 in 2008-09 to 5.53 then 5.45 in the following seasons and now this year’s 5.29, the idea that the Dead Puck Era was on its way back began to percolate and, once latched onto by the knee-jerk world of social media, caught fire and became a major talking point.

But this thought is flawed. It only takes into consideration numbers on the surface when, in fact, the issue goes much deeper. Goals per game is down from 2005-06, but one passing glance at today’s game and one hard look at the numbers shows the Dead Puck Era is not on the verge of returning.

See link for stats: http://www.thehockeynews.com/articles/45904-Boylen-Power-plays-not-goal-scoring-down-in-NHL.html

Editor’s note: There were, on average, five extra minutes of power play time per game being played in 2005-06 over 2011-12. When five is multiplied by the total number of games played in 2005-06 you get 12,300. Divide 12,300 by 60 minutes per game means there were an extra 205 games at even strength in 2005-06. Multiply 205 by the 1.63 5on5 GPG average in 2005-06 and there should be 343 goals added on to the 2005-06 total. In dividing the new total (4,361) by the 2,460 games actually played in 2005-06, you get an even strength GPG average of 1.77, still lower than this season.

Let’s get one thing straight: The low goal totals of the Dead Puck Era can be attributed to the overwhelming obstruction that was allowed. Therefore, the era should be defined more by the slow pace at which it ran, rather than strictly by the amount of goals being scored. There was so much obstruction it hurt the league’s speed and entertainment value immensely, but there is no one on this planet who, in their right mind, can compare the game we have now to the one we had eight years ago.

Is goal scoring down from what it was after the lockout? Absolutely – the numbers show that clear as day. But the numbers also suggest this development is in direct correlation to the fewer numbers of power plays being handed out. And just because there are fewer penalties called does not mean obstruction is at the level it was in 2003-04.

The one common ground where we can compare these three years is at even strength, where there are actually more goals being scored now than there were in 2005-06. In fact, only 108 more goals were scored at even strength in 2005-06 than in 2003-04. This year’s even strength markers have already surpassed the first post-lockout season by 144, with a few games to play.

Is obstruction creeping back into the game? When you compare it to how obstruction was handled fresh off the lockout, yes. But, again, when you watch a game and look at the numbers, the NHL is not in danger of reverting to what it was in the dark ages. Too many penalties for inconsequential plays were being called in 2005-06 (i.e. minor, unobtrusive stick taps) and there’s now a happy medium between that and the overwhelming pre-lockout levels of obstruction. What we have now is a good balance of goals, difficulty level and, in turn, entertainment value.

Power play opportunities per game jumped by 1.7 in 2005-06, but are currently being handed out less frequently than they were in the last year of the Dead Puck Era. But this has not had an adverse impact on the game’s goal totals at even strength, so how can one argue the clutching and grabbing is impeding with the entertainment level of a game to the degree it was before the lockout - or even that it’s headed in that direction?

If fewer penalties meant the Dead Puck Era was creeping back, wouldn’t that mean 5-on-5 goals would suffer rather than swell?

Entertainment value depends on your opinion. If all that keeps you interested in games are goal totals, then constant passing around the perimeter with the man-advantage is right up your alley. I like to call this “Harlem Globetrotters” hockey.

But if every other facet of hockey is something you enjoy as well, then this version of the NHL is still in a good spot. If you like battles for the puck, battling through checks, earning every inch of ice and every goal scored, the current incarnation of the NHL is for you. I like to call this “old-time” hockey.

I’m not here to argue the game is called perfectly - the level of officiating always has to be monitored. By having human beings manage a sport that runs at this pace, there will be calls missed from time to time. Suck it up and push through.

But let’s cut out this idea the Dead Puck Era is back. If you have a problem with the fact fewer power plays are being awarded and, in turn, fewer overall goals are being scored, please call it something else.

Because by watching the games and looking at the numbers, today’s NHL and the Dead Puck NHL are nothing at all alike.

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