The Shift: Breaking Down The L.A. Kings’ Secrets To Success

k8

By virtue of their 5vs5 shot differential, the Los Angeles Kings are the best team in hockey. As of Saturday night, the Kings are rolling along at 56.1% Corsi – #1 in the NHL by a long shot. In fact, the 3% gap between the Kings and the No. 2 Anaheim Ducks is the same as the one between the Ducks and the No. 15 Philadelphia Flyers.

So why are the King so good?

The simple answer is that they have good players executing a sound game plan developed by a good coaching staff. But how exactly does this manifest itself?

On March 26th, the Kings were beating up on the Edmonton Oilers in the middle of the second period when, in the span of 45 seconds, they put together – in my mind – a perfect, representative shift of everything that makes them a superior hockey team.

Continue reading

Hockey Talk: Why the Kings were good at hitting a lot and also just good

Dustin Brown and the Stanley Cup.jpg
Dustin Brown and the Stanley Cup” by JulieAndSteveFlickr: Dustin Brown and the Stanley Cup!. Licensed under CC BY 2.0 via Commons.

Hockey Talk is a (not quite) weekly series where you will get to view the dialogue amongst a few of the Hockey-Graphs’ contributors on a particular subject, with some fun tangents.

This week we look at dump and chase systems and hitting:

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.

The Hockey Graphs Podcast (EP 3): Hot Dogs = Sandwiches

unnamed

Welcome to the third episode of the Hockey Graphs podcast, where Rhys Jessop (of Canucks Army and That’s Offside) and Garret Hohl continue talking about hockey while learning how to podcast. Join us as we lament the death of Corsi. We also talk about Mike Richards hitting the waiver wire, All-Star game, and (as always) some prospects and draft theory. Continue reading

2014-15 NHL Season Preview: The Pacific Division

Photo by "Kaz Andrew", via Wikimedia Commons

Photo by Kaz Andrew, via Wikimedia Commons

Whenever I put together something as broad as a division preview, especially since the divisions have expanded, I usually try to slap something together that helps me get a quick impression of the teams as compared to one another. This time around, I put a little work into generating a 5v5 simulation of this coming season, specifically among the projected top 6 forwards, top 4 defensemen, and goaltenders. As 5v5 play comprises a little over 80% of all NHL gameplay, and these players tend to more consistently drive results (as players of around 3/5 to 2/3 of gameplay), focusing on their 5v5 performances from last year bring us to use a bit more stable indicators of future team performance. The quick-and-dirty approach here benefits from the fact that most of the Pacific lineups are quite similar from last year, and the top 6 and top 4 players tend to be deployed in the same roles from year to year. So, I took the average 5v5 Corsi-For% of the entire of the top 6 and top 4 for each team, the average 5v5 shooting percentage of the same group (for Johnny Gaudreau, I assumed a forward league-average 9%), and the career 5v5 save percentage of the projected goaltenders (for Fredrik Andersen I assumed a goaltender league-average 92.1%), and ended up with a projected 5v5 season that looked like this:
Continue reading

Gordie Howe vs. Bobby Orr vs. Wayne Gretzky vs. Sidney Crosby: Not Your Typical WOWY

Photo by "Djcz", via Wikimedia Commons

Photo by “Djcz”, via Wikimedia Commons

With or Without You analysis, often referred to as WOWY, frequently involves either comparing the performance of a team or particular players when a single player is and isn’t playing. While the approach is a risky one (sample size is a pretty big issue), it can actually be quite telling when you collect enough data.

The value of modern WOWY is that you can definitely get data from precisely the seconds a player played apart from the seconds they weren’t on the ice. Historical WOWY, on the other hand, cannot do much better than taking data from games a player played versus games they didn’t. To this end, then, I wanted to see if historical WOWY can tell us much of anything, and the best way to do that is to focus on players that are undisputed in their value. In this case, I went for WOWYs of the big guns, four of the best players across the eras of NHL history: Gordie Howe, Bobby Orr, Wayne Gretzky, Sidney Crosby.
Continue reading

Friday Quick Graph: Possessing the Puck in 1969, 1981, and 2013

Hextall OnIce.jpg

Photo by Jim Tyron, via Wikimedia Commons

Just finished tracking possession times in a November 15th, 1969 game between the Flyers and the Leafs. This game, when compared to the games from this post, fits virtually in-between them, which is interesting because, unlike with the other two games, the Flyers and Leafs were two teams on the lower end of the spectrum in the league (8th and 9th in 2pS% in a 12-team NHL). Maybe that also contributes to their average possession time of 6.08 sec (n=349) compared to the 1981 game’s 6.15 (n=364) and 2013 game’s 6.17 (n=360). Another observation among these games: the standard deviation for the 1969 and 1981 games is right around 4 seconds, where it’s right at 5 seconds for the 2013 game. I’ll save any deeper ruminations until I have a larger sample, but it’s food for thought.

Not too long ago, I decided I wanted to try out tracking time of possession in historical games, with the hope of eventually having enough data to look into things. I realized it’s going to be a little difficult to get large enough samples of singular teams, but I also realized that we could potentially compare the game as a whole in different eras. I’ve always been of the mind that the game has evolved somewhat, but at its core there are a number of best practices that have kept it pretty much the same game from around the time that the red line was introduced in 1943. I wanted to test that as far back as I could go, though, so with this possession tracking I actually tracked each individual possession rather than just a total time of possession. For this chart, I displayed all those individual possessions as a distribution, longest possessions to the shortest. These three games, the Philadelphia Flyers vs. Toronto Maple Leafs in 1969 (Toronto won 4-2), Edmonton Oilers vs. Philadelphia Flyers in 1981 (Edmonton won 7-5), and Los Angeles Kings vs. St. Louis Blues (St. Louis won 4-2), had some surprising results when compared. As you can see above, the distribution is actually quite close, with the 1981 game seeming to have shorter possessions but then moving above the others in the middle of the line. The 1969 game actually seems like a trendline of the 2013 and 1981 games. The average possession time? 1969: 6.08 seconds, 1981: 6.15 seconds, and 2013: 6.17 seconds. Obviously, I need (and want) more data, but it is a really intriguing start.

The “possession battle” results?

All Situations Possession

  • PHI (47.1%) vs. TOR (52.9%), 1969
  • EDM (53.4%) vs. PHI (46.6%), 1981
  • LAK (51.7%) vs. STL (48.3%), 2013

Possession, Score Close

  • PHI (41.3%) vs. TOR (58.7%)
  • EDM (48.7%) vs. PHI (51.3%)
  • LAK (51.2%) vs. STL (48.8%)

A Tale of Two Riverboat Gamblers: Analytically Comparing Jack Johnson and Dustin Byfuglien

Source: Harry How/Getty Images North America

There are probably enough fan bias tendencies in sports to fuel psychology graduate theses for years to come. Sometimes these biases even creep into the minds of hockey’s brain-trusts, including GMs, coaches, and national team selection committees.

One such bias is the propensity against players who are strong offensively but can be a risk defensively. Whether these offensive players are a net-positive to the team depends on whether their offensive output outweighs their defensive lapses. Period. You win the game by out-scoring, not by just increasing your own scoring or limiting your opponents. However, if you were to survey most fanbases, you would probably find very few defensive risk-type defenders that are considered a net-positive.

When it comes to the traditional plus/minus statistic, there are great intentions of evaluating a player’s net contribution, but the statistic ultimately fails at achieving this. There are a few issues with plus/minus, one of them being sample size; another fault to the statistic is its low repeatability, which is its ultimate failure. This unreliability in plus/minus relative to most other statistics can be seen here:

Using analytics, we can demonstrate how numbers help differentiate two gambling defensemen who have been the butt-end of scrutiny from their fanbase.

Continue reading