Tag Archives: Bruins

ShiftChart101: Visualizing matchups

This is the third post in a series on using ShiftChart.com to gain insight into hockey games.  It is not necessary to read the previous posts to make sense of this one, though it may be helpful.

One of most fascinating aspects of the NHL playoffs is the repeated matchups showcased between elite players in a Best-of-7 format.  A “matchup” is a strategy by which a coach designates certain players from his team to be used against opposing star forwards with the intent of keeping them off the score sheet.  Because each team has four sets of forward lines and three pairs of defensemen in constant rotation, executing specific matchups mid-game requires vigilance from the coaching staff and players.

ShiftChart provides a visual way to identify a coach’s matchup strategy.  I’ll illustrate its use by focusing on the most conspicuous shutdown player in the league, Zdeno Chara of the Boston Bruins.  At 6’9″, Chara receives special dispensation from the NHL to use a longer stick than allowed in the rulebook.  Had the Slovak been born in a different era, I picture him a warlord wielding a mace topped with the Hart Memorial Trophy, easily besting Wilt Chamberlain’s Bombaata in 1-on-1 combat.

In addition to Chara, Boston is further blessed with perennial Selke Trophy (for best defensive forward) finalist, Patrice Bergeron.  Armed with these elite shut down pieces, Bruins coach Claude Julien liberally employs matchups to stymie opposing teams’ stars.

Detroit Red Wings vs. Boston Bruins Game 1 – 4/18/14

The Detroit-Boston first round series is an ideal setting for visualizing matchups.  With Red Wings’ star Henrik Zetterberg out of the lineup due to injury (until Game 4), Detroit would have to lean heavily on player-magician Pavel Datsyuk.

Below is a ShiftChart screenshot from Game 1.  The shift rectangles form near-perfect Jenga columns; even without highlighting the aforementioned players, it’s clear a matchup is being employed.

Red Wings vs. Bruins, Game 1.

Red Wings vs. Bruins, Game 1.

For a more thorough evaluation, it’ll be easier if we arrange the players of interest side-by-side.  Click on Datsyuk, Chara, Bergeron (in that order.  I’ll explain).  Then from the Compare menu, select Shifts:

Compare -> Shifts

This will slide the selected players next to one another in the order they were clicked.  If you did not select the players in that order, you’ll need to de-select and re-select them (an improved drag-and-drop approach is in the works!).

Comparison of Datsyuk, Chara, and Bergeron's shifts in Game 1.

Comparison of Datsyuk, Chara, and Bergeron’s shifts in Game 1.

Arranged this way, although it’s clear that Chara and Bergeron are on the ice against Datsyuk frequently, you can also see the occasional missed matchup.  In the 2nd period around the 24 minute mark of the game, Datsyuk gets a shift away from Chara but not Bergeron.  Also, there are instances where even though the matchup is executed, there is “slop”: Datsyuk is free of Chara and/or Bergeron at the beginning or end of a shift.

[Aside: I can’t imagine how tiring this must get—Datsyuk basically sees the same 5 guys against him all game, all series… Half the Bruins roster is irrelevant to him!]

Two lesser-known aspects of the NHL game that affect matchup execution:

  • The home team coach has an embedded advantage in this chess match via the “last change” rule: after a whistle (other than for icing), the away team players must be sent on to the ice first.  The home team coach is then allowed to deploy the players he wants.
  • The second period is the period of the “long change” where, due to goalies switching ends, teams’ benches are further away, making on-the-fly substitutions more difficult to execute.

ShiftChart captures face offs as well.  Clicking on this option from the Layers gearbox menu will overlay every face off, colored by which zone it took place in: solid black for Boston, dotted red for Detroit, fuchsia for neutral zone (hey, we needed a color that was clearly different than every team color!).

faceoffs layer

Hovering over a face off line brings up the zone in which the face off took place and which player won:

Detroit Boston gm 1 faceoffs

With this additional information and keeping in mind the “last change” rule, coach Julien’s intentions are unambiguously revealed.  We can also see that the instance in which Datsyuk escaped the Chara matchup was not during a stoppage of play in the second period.

So if you’re Boston coach Julien, all good, right?  Until this happens with 3 minutes left in the game:

Unreal.  Phenomenal.  If you have a young child learning to play hockey, show this video to him/her to watch and study.  TV time is over, but you may watch this.  This is hockey greatness.

How about some numbers?

So you’re convinced there is a matchup and you want to see some numbers, because saying “from the chart, it looked like…” is not compelling enough.  Instead, you want to say, “Chara was on the ice for 90% of Datsyuk’s even strength shifts.”  The video below shows the behavior when you click Compare —> Total TOI.

The resulting visuals are divided into two sections: a top section, which uses the area of the shift chart, and a bottom section, which brings up completely new graphics.

Top section: total time on ice (TOI) comparison

Note the animation.  The shifts are first stacked, as if to calculate and display total time on ice (TOI).  But upon completing a total TOI bar for each player, the bars for Chara and Bergeron are sliced and slid out to produce the following formation:

Red Wings vs. Bruins, Game 1. Comparison of Chara and Bergeron to Datsyuk.

Red Wings vs. Bruins, Game 1. Comparison of Chara and Bergeron to Datsyuk.

The information is best understood by eyeing the chart vertically, noting “columns” of where the bars overlap and where they do not.

    • Datsyuk’s bar is the usual total TOI.  Nothing new.
    • Chara’s 22:05 total TOI is split into two segments:
      1. a 13:24 piece which overlaps with Datsyuk.
      2. a 8:41 piece that does not (no Datysuk).
    • Bergeron’s is more complicated, because his 17:45 ice time is compared to both Datsyuk and Chara. There are four pieces:
      1. a 10:03 piece for which all three players are on the ice.
      2. a 2:33 piece where Bergeron is on with Datsyuk only (no Chara).
      3. a 2:05 piece with Chara only (no Datsyuk).
      4. a 3:04 piece for which neither of the other two players are on the ice.

Selecting players in a different order would preserve the total time on ice for each player but change where the bars are sliced and shifted.  This is why selection order matters.  Two final comments on this top section:

      1. The animation to create the sliced bars attempts to adhere to our principle of “Make the data believable”, discussed in our second post.  By first creating the total TOI bar, we believe it’s easier for the user to accept the final segmented formation because he can see that they were all assembled from the original shift rectangles.
      2. Despite lacking the ooh-aah form factor of the charts in the bottom section, this visualization actually captures every possible two-way and three-way comparison of selected players (and more-way, if more players selected).  From the result, one can do calculations like: Datsyuk was away from both Chara and Bergeron for: 19:32 – (13:24 + 2:33) = 3:35, something not easily calculated otherwise.

Bottom section: detailed breakout by period and strength

The bottom section is itself split into two parts, the top for comparing overlapping shifts, the bottom for comparing time on ice.

Comparison of shifts and ice time, Datsyuk vs. Chara and Bergeron.

Comparison of even strength shifts and ice time, Datsyuk vs. Chara and Bergeron.

In fact, these two sections are calculated independently, for reasons I will get into shortly. Both are structurally the same: a bar chart shows how much of Datsyuk’s shifts/TOI the other skaters are on the ice for, and two filter doughnuts to allow the user to specify period and strength.  Clicking on any of the slices will filter the bar charts accordingly.  Note that the doughnuts reflect Datsyuk’s shift/TOI allocation and not the other players’.

Typically, an analyst is interested in even strength shifts, since special teams have dynamics entirely their own.  In the screenshot above, I’ve filtered by “EV” for both sets of charts.  From this, I can finally declare, “Chara was on the ice for 90% of Datsyuk’s 20 even strength shifts and 78% of his 16:51 even strength TOI.”  (I get the 20 shifts/16:51 by hovering over Datsyuk’s shift/TOI bars).  It’s always interesting to see how this changes in the period of the “long change”: these numbers fall to 83% and 67%, respectively.  While it’s not unusual to see 90% in overlapping EV shift counts, it’s difficult to get 80% in overlapping EV time on ice.

The “Mixed” category in the strength doughnut warrants further explanation: hovering over this slice of the doughnut shows three such shifts for Datsyuk.  These are in fact power play shifts, but the shifts had portions of even strength as well, resulting in this “Mixed” label.  If a shift was fully contained in the power play, it would have been designated “PP”.  By contrast, the TOI charts do not need a “Mixed” category since every second of Datsyuk’s ice time can be categorized as “EV” or “PP”.

So which is more useful, overlapping shifts or time on ice?

It depends on the question.  The reason the overlapping TOI charts show lower percentages is because of the “slop” alluded to earlier: if Datsyuk gets on the ice and  Julien wants to respond by sending out Chara but isn’t able to do so (perhaps the puck is in the Boston zone), how should this be treated from a matchup-scoring perspective?  Eventually the matchup is made, so that should be noted.  At the same time, if Chara is not able to get on the ice for 20 seconds, that isn’t a well-executed matchup.

At the risk of oversimplifying, I will say the charts for overlapping shifts better measures the “intended matchup” and the overlapping time on ice charts measure the “realized matchup”.  When trying to identify a coach’s shutdown strategy, the overlapping shifts is likely more relevant.  But if trying to assess a home team coach’s ability to get his star forward away from the opponent’s shutdown players, the overlapping ice time might be more relevant.  Neil Greenberg of the Washington Post wrote about an instance of the latter case involving Ryan Getzlaf in the Anaheim-LA series.

Here are are some recent uses of ShiftChart for matchup analysis from these playoffs:

      • Kings’ Anze Kopitar has matched up well with just about everyone in Stanley Cup playoffs —Greenberg, Washington Post (link)
      • Examining Toews-Kopitar playoff matchup —Craig Custance, ESPN Insider (link)
      • Blackhawks-Kings could turn on battle of top lines —Brian Hedger, NHL.com (link)

Welcome to the fascinating world of in-game hockey strategy!




ShiftChart101 (Part 2): Visualizing team depth

This is the second post in a series on using ShiftChart.com to gain insight into hockey games.  It is not necessary to read the previous post to make sense of this one, though it may be helpful.

In my first entry, one use of ShiftChart that I highlighted was to get a sense of team depth.  I used the example of the Rangers-Penguins Game 7 from last month (for those living under a rock, SPOILER: the Rangers won), and included the screenshot below.  Context: down by a goal with 10 minutes left in the game, and, hence the season, Penguins’ coach Dan Bylsma reduced his active roster to his top two sets of forwards and defensemen, forcing them to play shift after shift with minimal recovery period.

Penguins' Coach Bylsma shortens bench in failed comeback effort against Rangers.

Rangers vs. Penguins Game 7. Penguins’ Coach Bylsma shortened his bench in a failed comeback effort.

The chart is still one of my favorites because it captures a coaching strategy change with clarity: no arguments around “the numbers don’t tell the whole the story…” (In fact, there are no numbers here!  A theme I hope to return throughout this series).

Total time on ice (TOI) charts

A quicker but less detailed way to get a sense of team depth is by looking at total time on ice (TOI) per player.  Click on the Total TOI button in the scoreboard bar and then Sort players by “Total ice time by team”:

Screen Shot 2014-06-06 at 11.30.46 PM

The resulting bar chart shows that while Penguins players like Paul Martin (defenseman) and Evgeni Malkin (forward) skated for 28:10 and 23:04, respectively, there were players like Craig Adams and Tanner Glass who logged less than 7 minutes.

Total time on ice, Rangers vs. Penguins Game 7.  Red lines added for emphasis.

Total time on ice, Rangers vs. Penguins Game 7. Red lines added for emphasis.

The difference in player deployment between the two teams is visually apparent: the Penguins’ distribution of ice times is highly skewed, while the distribution for the Rangers is only moderately so.  The Rangers have been a surprise playoff success, led by stellar goaltending in Henrik Lundqvist and depth—four forward lines that coach Alain Vigneault feels comfortable using for almost the entirety of games.

These charts are, of course, for a single game, and better capture how a coach views his players rather than the players’ “true” abilities (former Rangers’ coach John Tortorella benched Brad Richards last playoffs, for example).  One could make the reasonable argument that we should really look at deployment over a season to get a truer sense of depth. I don’t disagree. However, I do believe that playoff games, particularly elimination games, are especially revealing on how a coach views his team and deserves special attention in any discussion about team depth.  For the purpose of the remainder of this post, I’ll continue to use the term from the perspective of “a coach’s willingness to use his full roster of players”, which I understand some may find unsatisfactory.

Aside: animation in ShiftChart

Below is a 30-second video of how to create the above chart:

The video may seem overkill (it is) but it serves another purpose in illustrating one of our guiding principles in designing the visualizations for ShiftChart: make the data believable. That is, don’t make the consumer wonder, and, even worse, doubt, how the numbers got there.  If one can accept that our shift chart has accurately transcribed official NHL shift data into those colored bricks, then seeing those bricks stacked up should require minimal leap of faith.

Depth of other playoff teams

Let’s take a look at the total TOI charts from a few other game 7s this playoffs to see what we might learn about those teams’ depth.  By April of this year, it had become cliche to say the Boston Bruins were “built for the playoffs”; Scott Burnside of ESPN even described them as a “playoff fortress“.  And yet, one month later, the Bruins found themselves trailing the Montreal Canadiens by one goal in the 3rd period of a game 7 and ultimately failed to get a puck by gold medalist Carey Price.  The finger pointing in Boston has been measured compared to the outcry in Pittsburgh, but a glance at total TOI reveals a 4th line that coach Claude Julien simply could not use for offensive upside and will likely remain the focus for tweaks in the off season.

Canadiens-Bruins Game 7 TOI

Total time on ice, Canadiens vs. Bruins Game 7.

The Chicago Blackhawks fell to the LA Kings in a game 7 overtime.  Like the Bruins, the Blackhawks will try to keep their major pieces, but the scrutiny is deserved for the bottom three forwards, two of whom played less than 4 minutes each!  Duncan Keith’s 32+ minutes for a game that ended five minutes into overtime may raise an eyebrow, but I believe Nick Leddy (12:37 TOI) has demonstrated continuous improvement this season and will only log more minutes next season—Leddy played less than 4 minutes in last year’s Cup winning game 6.

Kings-Blackhawks Game 7 TOI

Total time on ice, Kings vs. Blackhawks Game 7.

Rangers-Kings, Game 1

The two teams that demonstrated depth most consistently have earned their ways into the Stanley Cup finals.  The TOI charts for each team from Game 1 look remarkably similar.  One noteworthy difference is the 31:12 played by Rangers’ star defenseman, Ryan McDonagh, while their 6th defenseman, Raphael Diaz, skated only 10:15.  By comparison, Kings’ lowest TOI defenseman, Matt Greene, logged 16:48, indicating the Kings may have an edge on the blue line (beyond the phenom that is Drew Doughty).

Rangers-Kings Game 1 TOI

Total time on ice, Rangers vs. Kings Game 1.

A look at the shift chart below reveals that Rangers’ coach Vigneault used Diaz only twice in the 3rd period, both times within the first six minutes before keeping him out of sight in the crucial stretch of the period.  John Moore, finished with his two-game suspension, is expected to play in Game 2 in place of Diaz.

Rangers vs. Kings Game 1. Rangers' Raphael Diaz only had two shifts in the 3rd period of a tied game.

Rangers vs. Kings Game 1. Rangers’ Raphael Diaz only had two shifts in the 3rd period of a tied game.

One last note about McDonagh in these playoffs and the shortcoming of charts alone: he covers a tremendous amount of ice, sometimes battling in the offensive zone corners only to then have to sprint back on the backcheck.  This style is in contrast to Ryan Suter of the Minnesota Wild, another heavy-minute defenseman who plays a more efficient game and thereby avoids the foot race scenarios.  The data to quantify the intensity of shifts is not available (yet), but it is something to be mindful of when looking at these charts.

UPDATE — 6/9/14 (after Game 2, before Game 3):

The Kings won another overtime thriller, this time in 2OT.

John Moore returned as expected to the Rangers lineup for Game 2 as the #5 defenseman, with partner Kevin Klein sliding down to #6 (Klein was not used as frequently in special teams, especially in 3rd & OT).  This limited McDonagh’s minutes to 37:48(!), a number I wilt just thinking about, and yet was still behind Doughty’s 41:41.

Total time on ice Rangers vs. Kings Game 2.

Total time on ice, Rangers vs. Kings Game 2.  Doughty led the Kings with 41:41, McDonagh the Rangers with 37:48.

The TOI chart reveals remarkable balance in usage of both rosters, with the Rangers ice time more evenly spread.  This is expected since the Rangers led for most of the game (two 2-goal leads blown) and the Kings were in catchup (aka “Seabiscuit”) mode, leaning on their top players more heavily.  If anything, it is remarkable that the Kings’ chart is not more skewed; it is a testament to coach Sutter’s confidence in his players that he uses them all, even when trailing in the 3rd period.

As I study the shift charts and TOI charts, I often end up with more questions than answers.  What metrics can we construct to measure depth?  How might it depend on score in the game?  How can we better visually compare depth of the two teams?  Across a season? To me, this is one of the most important aspects of visualizing data: seeds for new questions emerge that one had not previously considered.