Hockey Abstract Presents... Stat Shot

Description

Advanced stats give hockey s powerbrokers an edge, and now fans can get in on the action. Stat Shot is a fun and informative guide hockey fans can use to understand and enjoy what analytics says about team building, a player s junior numbers, measuring faceoff success, recording save percentage, the most one-sided trades in history, and everything you ever wanted to know about shot-based metrics. Acting as an invaluable supplement to traditional analysis, Stat Shot can be used to test the validity of conventional wisdom, and to gain insight into what teams are doing behind the scenes - or maybe what they should be doing. Whether looking for a reference for leading-edge research and hard-to-find statistical data, or for passionate and engaging storytelling, Stat Shot belongs on every serious hockey fan s bookshelf.

Sujets

• Sciences et techniques
• Béisbol
• Hockey sobre hielo
• Ice hockey
• Baseball

Informations

• Publié par: Ecw Press
• Date de parution: 13 septembre 2016
• Nombre de lectures: 0
• EAN13: 9781770909236
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

Hockey Abstract Presents
STAT SHOT
by ROB VOLLMAN
with Tom Awad and Iain Fyffe
The Ultimate Guide to
HOCKEY ANALYTICS

CONTENTS FOREWORD INTRODUCTION WHAT’S THE BEST WAY TO BUILD A TEAM? WHAT DO A PLAYER’S JUNIOR NUMBERS TELL US? WHO IS THE BEST FACEOFF SPECIALIST? WHO IS THE BEST SHOT-BLOCKER? WHO IS THE BEST HITTER? WHO IS THE BEST PUCK STOPPER? EVERYTHING YOU EVER WANTED TO KNOW ABOUT SHOT-BASED METRICS (BUT WERE AFRAID TO ASK) WHAT WAS THE MOST ONE-SIDED TRADE OF ALL TIME? QUESTIONS AND ANSWERS CONCLUSION GLOSSARY ABOUT THE AUTHORS COPYRIGHT

FOREWORD
by SEAN McINDOE
Author of The Best of Down Goes Brown
Former columnist at Grantland
I can still remember the excitement that came with the realization that hockey was on the verge of entering the analytics era. I’d watched as the Bill James–led sabermetrics movement swept through major league baseball fandom before eventually going mainstream around the turn of the century. As a diehard Maple Leafs fan going back over 30 years, I was eager to see the same scenario finally play out in my favourite sport. After all, the promise of analytics—more stats, better information, and ultimately a better understanding of the sport we love—is nearly irresistible to any true fan.
And sure enough, maybe five or six years ago, the first wave of hockey analytics started to show up on my radar. There were only two problems.
The first was that, back in those early days, good content could be hard to find. Oh, there was lots of it and the small community of fans who were doing most of the work knew where to find it, but to an average fan like me, it could be confusing to wade through random blogs, forums, and comments sections to figure out what was worth paying attention to.
The second and far more pressing problem: math is hard, and I’m not all that bright.
That first problem has largely disappeared, thanks to the work of many smart and dedicated fans, including the authors of the book you’re now holding. You can now find engaging analytics work on virtually all of the major news and sports media sites, and the topic often comes up in broadcasts and highlight shows. More advanced work is being done on blogs and websites around the hockey world, supplemented by discussion and debate on social media. And, of course, NHL teams themselves have leapt enthusiastically onto the bandwagon, hiring up many of the brightest minds to inform their front office decision-making. In fact, just about the only place you couldn’t find analytics was on your bookshelf, and now we’ve solved that issue too. These days, smart hockey talk is everywhere.
The second problem is a bit trickier. If you’re a math lover who already gets the tougher concepts then you’re all set. But if you’re like me, and just calculating the tip on a $20 restaurant bill feels like a homework assignment, it can sometimes feel like you’re slamming your head against a wall. I’ve found myself reading through 2,000-word posts about some particular newly developed stat, getting to the bottom where they lay out the results for certain key players, and then thinking “Wait, is a high number supposed to be good or bad?”
Some of that is by design—not every analytics article is meant for a general audience. A lot of the pieces are intended for fellow experts who’ll engage in a form of peer review to make sure the work is solid. That’s a good thing, and it’s the sort of approach that will keep the movement headed in the right direction. But there’s a certain skill needed to do good work that’s also accessible to a wide audience.
That’s where Rob Vollman comes in. I’ve been reading Rob’s work for years, and there may be no better writer in the field when it comes to straddling that line between producing smart, important content while still making sure the average fan can get their head around it. There’s nothing quite like getting to the end of a complex piece and realizing “Hey, I get this. It makes sense. I can actually use this.”
That’s the beauty of Rob’s work in general, and of this book in particular. If you’re just dipping a toe into the analytics waters for the first time, you’ll be surprised at just how much of these “advanced” stats will end up making intuitive sense to you. If you’re a novice, you’ll encounter a mix of familiar concepts and brand-new ones that take the basic concepts further, or sometimes in surprising new directions. And if you’re already an expert, well, you’re probably not reading this foreword. You dove straight in, eager to see what sorts of new discoveries you’ll find inside.
In any case, you’ll come out the other side a smarter hockey fan. You’ll learn which stats to follow and which to largely ignore. You’ll be better able to predict what’s most likely to happen in the future. And, maybe most important of all, you’ll end up with a much more finely tuned BS-detector, one that will keep you from getting suckered in by common fallacies and sloppy thinking. You won’t necessarily like all the lessons you learn—I’m still not quite over the ugly truth analytics taught me about first-line centre Tyler Bozak—but you’ll be wiser for them.
The work of Rob and folks like him has undoubtedly made me a better hockey fan and, I hope, a much better hockey writer. Spend some time with this book, and they can do the same for you.
(You’ll still be on your own for those restaurant bills though.)

INTRODUCTION
It was called the summer of analytics. The growing wave of interest in the field reached a tipping point early in 2014, with the successful, high-profile prediction of Toronto’s late-season disaster followed by the triumph of Justin Williams and the Los Angeles Kings in the Stanley Cup Final, all of which prompted a flurry of interest in hockey analytics from NHL front offices and mainstream media.
After years of toiling away in anonymity, our hockey analytics community had a busy and exciting time that off-season. Of those analysts who had their work referenced in Hockey Abstract 2014 , these eight were subsequently hired by NHL teams:
NHL FRONT OFFICE HIRING OF HOCKEY ANALYTICS OUTSIDERS, 2014
DATE HIRED
TEAM
ANALYST
July 14
CAR
Eric Tulsky
August 5
EDM
Tyler Dellow
August 10
FLA
Brian Macdonald
August 19
TOR
Darryl Metcalf
August 19
TOR
Rob Pettapiece
September 29
undisclosed
Corey Sznajder
October 11
WSH
Timothy Barnes
October 20
SJS
Matt Pfeffer
In addition, Toronto hired Cam Charron on August 19th, an undisclosed club hired Dimitri Filipovic on September 29th, and New Jersey, perhaps kicking off the entire party, had hired Sunny Mehta as its director of hockey analytics on June 12th.
Of course, hockey statisticians had been hired in the past, but what made this special was the fact that teams were choosing outsiders for those roles. Not exclusively, of course, given the equally prominent hiring of analysts like Ian Anderson in Philadelphia and Kyle Dubas in Toronto, but bloggers and amateur pundits were certainly being pursued to a far greater extent than ever before, and teams were being far less secretive about it.
Picking up on the fact that this sport was getting ready to join baseball and football in publicly acknowledging and tentatively embracing these new views, mainstream media quickly followed suit, hiring many of the remaining analysts for various websites, newspapers, magazines, and radio shows. Most importantly, the NHL itself launched a multi-phase project in the 2014–15 season, introducing a flurry of statistics to its website that were innovated exclusively by outsiders and bloggers.
Even in my personal experience, the growing popularity of this field has been obvious. Not only did I get this very book deal after years of self-publishing, but I was regularly contacted with questions by about a dozen NHL organizations and several mainstream media organizations. My work was even featured in non-sports magazines like Rolling Stone and Forbes . 1 After over a decade of silence, interest in hockey analysts’ work was growing rapidly.
Since it’s never too early to illustrate a point with a chart (and because it’s only fair that I should be the first individual subjected to the same type of analysis that will soon be unleashed on all the NHL’s players), the following chart shows the interest in my own brand of statistical analysis on radio and television, growing from about 10 appearances per year historically to about 50 in 2014 and 100 in 2015.

This same trend is typical of my fellow statistical analysts and across other forms of media, including frequent quotes and non-traditional statistics appearing in mainstream websites, newspapers, and magazines. Like it or not—and you’d presumably be holding this book only if you like it—statistical analysis has finally arrived to our sport to stay.
A Mixed Blessing
The surging popularity of hockey analytics comes with the good, the bad, and the ugly.
On one hand, it finally provides a platform for the growing number of brilliant analysts to share their work and to build