As we head into May, which starts Friday, the uncertain completion of the NHL regular season and playoffs continues to be explored at the league level and debated by media and fans. Everyone agrees: Any resumption of the chase for Stanley Cup will adhere to all safety measures for players, coaches and relevant staff while honoring the public health edicts of local authorities in potential NHL rinks and practice for play.
It's all highly tentative with a tremendous amount of work and due diligence required. While we hockey fans await May and possible clarity, here's a "Hockey Analytics Starter Kit," for any fans who want to know more about how advanced statistics or "metrics" are influencing how NHL front offices build a team. Now might be as good a time as any to learn more:
Watch: NHL's Twitter livestream Thursday at 4:00 p.m.
Alexandra Mandrycky, NHL Seattle's director of strategy and research, is the franchise's analytics chief. She was hired by CEO Tod Leiweke even before GM Ron Francis joined the team last July. In fact, at Leiweke's request, Mandrycky built out analyses of potential GM candidates, including one showing roughly 80 percent of the goals scored by Carolina in a deep playoff run last spring were notched by players Francis drafted or acquired while Hurricanes GM. What's more, 80 percent of the goals scored by players for the Charlotte Checkers, the team's top affiliate that won the league's 2019 American Hockey League championship, were Ron Francis-developed players.
Mandrycky will be talking NHL analytics, taking fan questions and more. The Hockey Happy Hour will take place this Thursday at 4pm PT on Mandrycky's Twitter Account.
Read: Rob Vollman's 'Stat Shot' books
Rob Vollman, who joined the Los Angeles Kings in 2018 as senior statistical analyst, has authored a number of books about hockey analytics. His 2016 book, "Hockey Abstract Presents... Stat Shot: The Ultimate Guide to Hockey Analytics," is a productive place to start on your analytics foray. Before this book, Vollman self-published annual volumes of his "Hockey Abstract"-inspired by Bill James and his "Baseball Abstract" sentinel work re-shaping how MLB players are evaluated to this day. A second book, "Stat Shot: A Fan's Guide to Hockey Analytics" (2018) is a good choice if you feel you know a bit more than the average fan.
But as someone who read Vollman's 2018 book first, I still benefitted from ordering the 2016 "Stat Shot"-hey, "Star Wars" fans like prequels too, right?-and would recommend it for any of us who want to understand how top-flight NHL front offices are leveraging advanced metrics. Vollman opens with how and why he gravitated to hockey analytics, then dives right into defining the NHL salary cap (not nearly as dry a topic as some think). He builds a good part of the book on the best way to build a contending team by "projecting a player's expected value over the life of his contract relative to expected cost in cap space."
Stick with Vollman, which is not hard with his gift for explaining advanced stats in a clear and simple manner. You will understand just what "expected value" and "expected cost" mean and how people like Vollman and Mandrycky arrive at their calculations. Other terms you will learn and appreciate as we all follow how GM Francis and his front office drafts and manages the NHL's 32nd franchise: Cap relief, replacement value, shot-based metrics, what juniors hockey statistics represent, what it takes for a player to be a superior faceoff man and how you can determine the most efficient shot blockers.
The second "Stat Shot" book (2018) is a bit more relevant to today's players and updates the dynamic field of hockey analytics. Highlights include Vollman's data-filled statements in the "who is the best goalie" in chapter. Another section of the book teaches readers about the various levels of hockey (juniors, NCAA hockey, AHL, European pro, NHL) and whether it is plausible to compare player statistics across leagues and levels. College hockey fans will no doubt enjoy and debate Vollman's rankings of relative strength of each major NCAA conference for predicting NHL success. Both books have cartoons, which is always welcome as complex material is consumed.
Read or watch or both: Moneyball
As mentioned, Bill James (now working for the Boston Red Sox) started this whole sports analytics movement with his own self-published Baseball Abstracts that were literally pamphlets in the earliest days. Most sports fans know that Billy Beane as GM of the Oakland A's (still running baseball operations) used analytics to beat the system of "big salaries make the playoffs" by turning an century-plus sport upside down by seeking hitters who get on base (hits, walks, hit by pitch to build "on-base percentage") rather than hit for average (hits only divided by official at-bats, which ignores walks and additionally puts no value on wearing out starting pitchers by running up their pitch counts).
The superb business author Michael Lewis was intrigued by Beane's unorthodox success, writing the No. 1 bestseller, "Moneyball: The Art of Winning an Unfair Game," in 2003. If you have streamed yourself, this book will fill a void. It is a baseball book, yes, and happily so. But it is clearly a case study and deep dive into how Beane and Harvard economics major-turned-instant assistant GM used data analysis to transform baseball and, European soccer next, then the U.S. pro leagues. The book was optioned for a movie, which starred Brad Pitt as Beane, taking nearly a decade to get to the screen. It's not the book in terms of depth, but an entertaining and enlightening two hours and 13 minutes.
OK, time for a field trip. If you have followed one or more of the "Hockey Analytics Starter Kits so far-or you're the type who dives into the deep end of a pool first-then the next step is visiting a hockey analytics website. While there are many excellent sites to pull down data and serve as inspiration for would-be coders and STEM (science-technology-engineering-math) students and lifelong learners, a good starting point is Hockey-Graphs.com (don't forget the hyphen). The site is designed for exploration with articles available on the home page in a feed format that allows users to scroll for interest.
The articles are accessible, often with helpful links to better understand concepts like the newer term "power kill" introduced by Mike Pfeil at the 2019 Seattle Hockey Analytics Conference to explore how some teams might skew toward being more aggressive offensively when at a man-down disadvantage.
Recommendations: Review the "About Us" section for an instructive cross-section of personal histories of site authors, making it clear hockey analytics is open to all bright minds with hockey passion. Next, try out your now deeper analytics know-how by reading "Introducing Offensive Sequences and The Hockey Decision Tree" by Thibaud Chitel. It covers some terms you will read or hear in your hockey-fan travels: Zone exit, zone entry, high-danger shot, high-danger pass, expected goals. The story begins with the author identifying two questions most frequently asked of NHL front offices to their data analysts colleagues: One, how can analytics help us work better and faster? Two, what is the real contribution of each player? The answers reveal support for why NHL GMs, players and fans alike are paying more attention to advanced metrics to enioy the sport even more.