NHL Analytic Teams’ State of the Union

Pure-mathematics-formulæ-blackboard

Fandom means a lot of different things to different people. But one thing unites us all: we hope our favorite team will win, and spend a great deal of time thinking how they can.

For those of us who dig a little deeper on the “how” side and use analytics, we hope that our work will eventually make its way to a front office. In some ways, it already has: numerous “hockey bloggers” hirings have been made recently.

But how many and for which teams?

With some research, I’ve culled a working document on all analytics hires for NHL teams and how they may be using analytics. The following descriptions comes from a variety of sources including Craig Custance’s Great Analytics Rankings [Paywall], fellow bloggers from across the internet, media reports, word of mouth and anonymous insiders.

It should be noted that just because a team has made an “analytics hiring”, it doesn’t necessarily mean that they value their input or use the analysis provided properly. In fact, hires can be made simply for PR reasons, and some teams may even give analytics tasks as secondary duties to staff members who do not posses any formal background in the subject. Teams may also have hired private firms providing proprietary data, which in reality may not provide any tangible, verifiable value than what is free and readily available online.

Continue reading

Will the 2015-16 Calgary Flames follow the 2014-2015 Colorado Avalanche?

Odds are, a team that performs like the 2014-2015 Calgary Flames in shots, possession, and chances will miss the playoffs. The odds also indicate if they do make it they are more likely going to be eliminated in the first round. Calgary beat the odds, though, and pushed into the second round until their eventual elimination at the hands of the Anaheim Ducks.

Odds are not destiny; out-shot teams make the playoffs all the time.

Just last season the 2013-2014 Colorado Avalanche finished the season with 112 points and were favorites to falter in the 2014-2015 season by the analytical community. This has led to comparisons between the 2014-15 Flames and the 2013-14 Avalanche.

How similar are the two teams? Let’s take a look.

Continue reading

Why The Los Angeles Kings Missed the Playoffs: An Open Email

I’ve been asked by a couple of people how a team with a normal PDO and strong metrics could have missed the playoffs entirely. It’s an important question to address, particularly because the playoffs are so much more important than worrying about whether you’re lucky enough to win the Stanley Cup. I composed an email response, and felt good enough about it to open it up. While this doesn’t comprise the whole of the explanation (certainly, there’s some “blame” that goes to Calgary & Winnipeg), they’re points that I’m not seeing made elsewhere.

Hi XXXXX,

A couple of things really hurt the Kings. One is a cruel fact of a low-scoring league: if more games are going to be decided by one or two goals, it increases the likelihood that a fluky goal can impact a team in the standings. The Kings had the most overtime losses in the Western Conference; last year they were tied for the second least in the West. The second thing is the tank battle…the West had two teams with historically bad records – add in games against Buffalo, and we have three teams that will end the season with point totals that were typically reserved for the sole worst team in the league in other seasons. On the flip side, that creates a rising tide for all the other ships in the league, and raises the bar for getting into the playoffs. I mean, needing to get nearly 100 points to get in? Last year, the bottom team in the West, Dallas, had 91 points. A nearly identical record to this year got Los Angeles into the playoffs in the 8th seed in 2011-12.

Maybe the closest comparable circumstance was 2010-11, when the West again had two sad-sack teams (Colorado, Edmonton), and the East was noticeably weaker than the West. It took Chicago 97 points to get in. Also, look at 2006-07…Colorado didn’t make it with 95 points, having gone 44-31-7 during the season. If the West is considerably stronger than the East, as it was back then, you could also end up with a tougher path to making the playoffs. In ’06-07, every team in the Western Conference, save the 8th seed (Calgary, with 96 points), had 104 points or more!

Anyway, this year’s league created a scenario where a good team, by any measure, might not get in. The Kings went 39-27-15, outscored their opponents by 12 goals (in fact, they tied for 2nd in the league in goal differential at even strength), and could get 95 points and not make the playoffs. In the loser point era, there were only two seasons that was even possible, and both occurred in the stronger Western Conference. It’s a successful season by anything except the fluid marker of the playoffs, which unfortunately for them is all-important to reach.

Hope this helps,

Best,

Ben

Note: One critique I’d like to address – yes, all teams in the league are theoretically dealing with the tank battle, but tanking doesn’t occur across the entire season, which means that teams that have already played most or all of their games against tanking teams earlier in the year won’t have the benefit. Additionally, those same teams might have the resulting, added pressure of a more-difficult set of opponents through the latter portion of the season. If the difference between making the playoffs versus not is a matter of a few points, the difference in scheduling can become all the difference in the world.

2014-15 Preview: The Central Divison

Image from Matt Boulton via Wikimedia Commons

If you’re a fan of a Central Division team that doesn’t employ Ondrej Pavelec, you’re probably feeling optimistic as we approach the upcoming season. And you should: this is clearly the best division in the NHL, and all six of its non-Manitoban clubs have legitimate playoff hopes.

Of course, not all six will reach that milestone; at least one will join Winnipeg on the outside looking in. At this time, however, few can agree on how the standings will shake out. The Stars have been projected anywhere from second to fifth; the Avalanche have been slotted everywhere but last. Some are high on the Blues, others are sick of them constantly disappointing.

This uncertainty should make for an exciting year in “Conference III.” Below is a team-by-team breakdown of the league’s toughest division:

Continue reading

Is it time to appoint a new jester?

Toronto -with its high profile in the media combined with some questionable management- has consistently been the brunt of jokes over blogs, message boards and twitter from other fanbases.

Recently the Toronto Maple Leafs has made a bunch of savvy, low-risk, high-potential steps both in management and player personnel to improve their team. While they are still a distance away from being a contending team, the steps taken are not those that the online hockey community has grown to love about Toronto.

With this knowledge and the offseason nearly in our rearview mirror, it is time for Hockey-Graphs to ask its analytically inclined following:

All teams in poll came from an unofficial nomination survey I conducted on twitter.

Revisiting the NHL Regression Predictions from January 1st

Photo by “User:Zucc63” via Wikimedia Commons, modified by author

If you’ll remember, one of the inaugural posts here was a regression prediction piece, using a combination of PDO and Fenwick Close to see who might improve or decline over the latter half of the season. I decided to put together a table of the teams I predicted would negatively or positively regress, just using the aforementioned data:

If you’ll remember, I pegged Anaheim, Colorado, Montreal, Phoenix, Toronto, and Washington for negative regression, and Florida and New Jersey for positive regression. So, even with really rudimentary predictors, this season I was able to be fairly successful building predictions from a half-season sample for the remaining season. In previous years, the fancy stats folks usually picked the much more obvious targets (Toronto being the big one this year), but it’s very possible to go further if you wanted.

NHL Defensemen and Shooting Contributions back to 1967-68

File:Defenseman Ray Bourque 1979.jpg

Photo by Dave Stanley via Wikimedia Commons

I have kicked around this data in the past, most prominently in my theoretical post on offensive systems, but I really wanted to get further into the intricacies of defensemen and their historical place in team shooting (among other offensive contributions). By looking at how much a defenseman contributes to a team’s shot generation (expressed as a percentage of team shots in the games a player played, or %TSh), we can draw some interesting comparisons across NHL eras, but I haven’t yet explored how the role of the defenseman has (or hasn’t) evolved from the Expansion Era to the present, nor have I taken a look at some of the more exceptional defense shooting teams. Let me correct that now.

Continue reading

NHL Career Charting: The Pre-BTN Era and What We Can Still Do With Historical Data

File:BrendanShanahan.jpg

Photo by “IrisKawling”, via Wikimedia Commons

Hockey statistics have always been fairly historically limited; most of the so-called “fancy stats” have only been tracked (and easily track-able league-wide) back through the 2007-08 season. The prior years have a veil of fog over them, though there is fairly decent shot data going all the way back to the 1952-53 season (thanks to the Hockey Summary Project; I’ve been able to bring the data together), good game-by-game individual player data going back to 1987-88 (thanks to Hockey Reference via Dan Diamond & Associates), and gradually-improving TOI data going back to 1997-98 (thanks to NHL.com and Hockey Reference). Unfortunately, this has lead to a relative dearth of research into the years of the “Pre-BTN” Era, so-called because 2007-08 was the first year we received in-depth, league-wide data from Gabe Desjardins’ Behind the Net stats site and Vic Ferrari’s timeonice.com.

Having a background in history, and also having grown up as a fan of the league in this grey statistical era, I have spent the last couple years trying to compile and present statistics from the Pre-BTN Era in ways that can help provide a window into those years (and possibly inform our understanding of the present-day game). I’m somewhat indebted to Iain Fyffe, a guy who’s been doing similar yeoman’s work much longer than myself at Hockey Prospectus, though more recently he’s been sharing his work at his own site, Hockey Historysis.

The fact of the matter is that there is actually an enormous amount of information out there, and more importantly with graph work we can really do some interesting things. First case in-point is what I call “career charting;” essentially, charting a player’s shots in a game relative to their team’s shots in those same games. Using the metric %TSh, or percentage of team shots, this provides an interesting glimpse into player contributions, workload, and development in the Pre-BTN Era. Adding some artistic (and informational flourish), I present to you Pierre Turgeon:

Continue reading

Crystal Blue Regression: Leafs, Avalanche, Ducks, Among the Most Likely to Regress in 2014

Image

Picture taken by Sarah Connors, posted to Flickr – via Wikimedia Commons

With the Winter Classic coming up, or should I say the Winter Classics since the NHL handles marketing success like the kid who found the cookie jar, we also ring in the rough middle of the season. It’s a time for reflection, maybe a chance to re-assess your decisions, lifestyles; and if you’re analyzing the NHL, it’s the perfect time to recognize trends that may or may not continue. Also known as “regression,” here I’m dealing with a concept everyone understands to a degree; you invoke it when you see a friend sink a half-court shot in basketball and say, “Yeah, bet you can’t do that again.” The trend, supported by a history of not making half-court shots, suggests that it is unlikely for your friend to sink the half-court shot, even if they recently made one. In the NHL, possession stats like Corsi are considered better predictors of future success than stats that can be influenced more greatly by luck, like goals (and, consequently, wins), shooting percentage, or save percentage. Much like your friend and their half-court shot, there are teams that are defying their odds (established by possession measures) to succeed, which can easily happen with less than a half-year of performance.

Continue reading