Should teams play with 4 forwards when they’re down late?

Tl;dr

  • There is some evidence to suggest that teams should play with 4 forwards when trailing late in a game.
  • The timing of when to switch to 4 forwards is dependent on how large an impact the switch has on goal scoring rates, however even with a low impact on goal scoring, using 4 forwards still makes sense.

One of the weird things about sports that I find fascinating is how often coaches and players seem to go out of their way to avoid having a negative impact on the game, even at the expense of potential positive impacts. People often seem to prefer to “not lose” rather than to win, which can result in sub-optimal decision making, even in the presence of evidence to show that the correct decision is not being made.

There are many examples of this across sports, but the biggest two in hockey are pulling the goalie and playing with 3 forwards on the power play. Analysts have been arguing for many years now about why teams should pull their goalies earlier, but it’s only been in recent seasons that teams have become more aggressive in getting their netminders out earlier.

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A Defense of WAR from a WAR-Skeptic

Note: This was originally intended to be a tweet-thread which grew far too long and unmanageable, so you’re getting a poorly-written post instead. Apologies in advance.

Recently, David Johnson, owner of the awesome puckalytics.com has been on a bit of a warpath (pun intended) against the use of WAR/GAR. Most of David’s arguments can be found here and here, but there are some other comments in this thread.

I consider myself a bit of a WAR skeptic. I think Dawson’s work is great, but I think there are limitations/issues with it. A good summary of some of my concerns can be found in another ill-advised and long tweet thread.

With that being said though, I still think it’s extremely useful as a first pass to start discussion. WAR can be broken down into 5 useful components to see where a players impact derives from.

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Second Units and Zone Entries: Why teams should go all-in on the 4 forward power play

Using 4 forwards on the power play is generally a good strategy. Four forward units take more shots, score more often on those shots, and post a better goal differential than 3 forward groups do.

It’s also a strategy that has become more popular over the last few years. 4 forward units have accounted for roughly 56% of the 5-on-4 ice-time this season, up 4% from last year and more than 15% from 5 years ago.[1]

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Measuring the Importance of Structure on the Power Play

tl;dr

  • We can measure a team’s power play structure using shot location data, creating a Power Play Structure Index that quantifies their ability to establish and shoot from a structured formation.
  • A Team’s Power Play Structure Index is a stronger predictor of future goal scoring than past goals, but weaker than shot attempt generation.
  • When examined together with shot attempt generation, power play structure is a significant predictor of future goals, although slightly less important than shot attempt generation.
  • A team’s structure index can provide valuable additional insight into why certain power plays succeed or fail.

Edit 2017-02-15: An earlier version of this piece had a small error in the regression coefficient for PP Structure Index. While the article previously indicated the coefficient was -0.19, it should in fact be -0.30. The text both above and below has now been corrected.

Introduction

The importance of structure in a team’s power play is something that’s really easy to see. We’ve all watched a power play executing at the top of its game: the puck flies from player to player, leaving defenders pivoting in place to try to keep up. Each shot looks exactly like it was diagramed by the coach, with attackers working to set up a specific shot from a specific player in a specific location.

A solid structure doesn’t just look good; it actually produces better results. Arik Parnass has written extensively on the importance of structure to power play success, showing that teams who get set up in a dangerous formation score more goals than those who don’t.

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Quick Post: Do Past Sv% Variables Predict Future Sv% Variables?

The usefulness of on-ice save percentage (and derivative metrics such as Sv% Rel and Sv% RelTM) has been the source of many, many heated debates in the analytics blogosphere. While many analysts point to the lack of year-over-year repeatability that these metrics tend to show (past performance doesn’t predict future performance very well) as evidence of their limitations, others (primarily David Johnson of HockeyAnalysis.com) have argued that there are structural factors that haven’t been accounted for in past analyses that artificially deflate the year-to-year correlations that we see.

David’s point is a fair one – a lot can change about how a player is used between two samples, it’s not unreasonable to think that those changes could impact the results a player records. But we don’t just have to speculate about the impact those factors have – we can test the impact, by building a model that includes measures of how these factors have changed and seeing how it changes our predictions.

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Does aggressive play on the penalty kill pay off?

Late last week, Arik Parnass pointed out a particular peculiarity about the Ottawa Senators’ penalty killing so far this year.

While the Sens may be an extreme example, their numbers tell the story of a constant struggle that teams are faced with when killing a penalty: do you focus solely on your own end and do whatever it takes to prevent a goal, or do you allow your forwards to take the play to your opponents, trying for a shorthanded goal and forcing them to defend in a situation where they may not be expecting it.

This risk-reward question is one that’s central to the value of hockey analytics. It’s very easy to make decisions based on personal experience which is so often dominated by memories of things that are out of the ordinary – a coach will likely remember watching his winger get caught deep trying for a shorthanded goal, while forgetting the 2-on-1 opportunity he generated earlier in the game. It’s just as easy, however, for a fan to complain that his favourite team won’t put out their best forwards to aim for a go-ahead shorthanded goal without any data to back up their argument. The challenge for analysts then is to dig through the available data to figure out what past experience has taught us about the overall net impact of playing for a goal on the penalty kill, so that we can make an informed judgement as to what the potential costs and benefits are.

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Probable, ‘Cause: Brodeur’s Record, Karlsson’s Top 5 Chase and Canadian Panic Index

Probable, ‘Cause is a new feature where the Hockey Graphs staff give their predictions about the big unknowns in the hockey universe today. We’ll offer a question and give the reasons why it will and won’t happen, and then our estimate of the probability that the answer will wind up being yes. At the end of each question you’ll have the chance to submit your predictions as well, and we’ll review the group’s answers in the next edition of Probable, ‘Cause. This week, we’ll look at Braden Holtby’s odds of entering the NHL record books, whether Erik Karlsson can keep up his hot hand, and how nervous broadcasters should be at the prospect of an all-American playoffs this year.

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2015-16 Hockey Graphs Midseason Awards

With the league returning from the completely predictable All-Star festivities (I didn’t see the game but can only presume that John Scott screwed the whole thing up, since that’s what Gary Bettman implied would happen), there’s no time like the present to look back at the first 50 games and take stock of the NHL season that’s been so far. And since the only thing better than arbitrary lists or rankings is many arbitrary lists or rankings, we here at Hockey Graphs have put together our picks for each of the end of season major awards.

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Predicting Which Players Will Succeed on the Powerplay

Alexander Semin did not have a good season last year. After producing decent numbers in his first two seasons in Carolina, with 35 goals and 51 assists in 109 games, Semin struggled in 2014-2015, putting up only 19 points over 57 games and seeing his shooting percentage drop below 10% for only the second time in his 10 year career. With three years remaining on a contract paying $7MM per season, the Hurricanes decided to cut their losses, buying out the Russian winger prior to the start of the UFA period in July.

While at first glance Semin’s release seems like a reasonable response for a former top scorer who appeared to have lost the magic touch, if we look at little closer at Semin’s numbers a different story beings to emerge. Semin logged only 1.5 minutes of powerplay time per game in 2014-2015, down more than 2 minutes from his 2013-2014 total, and well below the 4+ minutes he would see at the start of his career in Washington. While other factors certainly played a role in his fall from grace (a 97.5 PDO at 5-on-5 doesn’t help), there’s no denying that the coaching staff’s decision to keep Semin off the ice when the ‘Canes were up a man cost him (and likely the team) points.

Although Semin is an extreme case, the general story of a player losing points as his powerplay time decreases is not uncommon amongst NHLers, and illustrates that opportunity often matters just as much as ability when it comes to a player’s results. Each team’s powerplay minutes are limited, and valuable to both the team and player, given the higher scoring environment that exists when a team is up a skater. Overall, teams scored roughly 25% of their goals on the powerplay last year, despite the fact that less than 20% of total ice time was played with a team on the man-advantage.

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Sbisa, the Sens, and the Scramble: Evaluating Defensive Play Following a Shot Attempt

Luca Sbisa may be one of the players who best epitomizes the divide between the old-school, eye test view on hockey and the statistics-focussed analysts offering their opinions from their mother’s basements on fan curated sites across the internet. While GM Jim Benning clearly thinks Sbisa is a useful defender, rewarding him with a 3-year, 10.8MM deal, and consistently praising his defensive zone smarts, Canucks fans have been less bullish on the talents of the 25-year-old Swiss pointman. Correctly noting his less than stellar possession numbers, J.D. Burke commented that his first season with Vancouver featured few “extended stretches in which any pairing with Sbisa on it looked passable”. These aren’t just the criticisms of a bitter fan wishful for better years, Burke backed up his arguments with a detailed numerical breakdown of Sbisa’s many failings, and video evidence of some of his less than professional defending from 2014-2015. Burke, and the Canucks’ fanbase in general, seemed to paint a picture of Sbisa that stands in stark contrast to what Vancouver management observed. Where the fans saw a player who frequently found himself out of position at critical junctures when defending his own end, Vancouver’s brain trust viewed Sbisa as the ideal player to disrupt a cycle down low. How could two groups of people who watched the same games with such intense devotion come to such different conclusions?

One of the biggest difficulties with evaluating Sbisa, and defencemen in general, is that what the eye test says is important is often wildly out of sync with what statistics can currently measure. While stats-based analyses focus on a defender’s ability to prevent shot attempts (in other words, their Corsi Against per 60), most of the praise for defensively-minded defencemen tends to focus on hockey IQ, being in the right position, and winning battles in the corner. While ideally these less “quantifiable” skills should lead to favourable statistical results, issues with differences in player deployment and the teammate-dependent nature of defending often mean that what gets praised in post-game interviews isn’t what shows up on the scoresheets, leaving a divide between management’s view and the story told by pure shot attempt numbers.

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