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An Advanced Look: The Patrick Kane Effect

By Melissa Peterson
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Patrick Kane is an elite player.

*Crickets, because no one is really ever disputing that fact*

If you follow the wider hockey world, we’ve heard talk of Sidney Crosby of the Pittsburgh Penguins slumping this season. Same for Patrice Bergeron of the Boston Bruins. Whether or not you agree with these analyses (I don’t), they’ve been said. But what of Patrick Kane?

Silence.

No one’s really said anything but positive things about the 25 year old since he really came on the scene in 2007 when the Blackhawks selected him with the first overall pick in the draft. In his first season, he racked up 72 points and won the Calder Memorial Trophy, which is awarded to the best rookie player (For some perspective, the points leader for that season was Alex Ovechkin with 112 overall points; Kane came in 32nd with 51 assists and 21 goals as a rookie).

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Since his point scoring first season, the Blackhawks have made the playoffs every year. For Kane personally, he’s scored the game-winning goal during Game 6 of the 2010 Stanley Cup Finals, represented the USA in two Olympics, represented the NHL in four All-Star games, been the 2013 Stanley Cup champion as well as became the fourth American-born player to win the Conn Smythe Trophy and the first American-born forward to do so. Prior to getting injured, Patrick Kane was the leading points scorer in the league for this season. In terms of the points race, right now only two players are in front of him in terms of Points-per-game, of which Kane has 1.049: Sidney Crosby (1.11 Points per game) and Evgeni Malkin (1.07 points-per-game). Tyler Seguin trails him in fourth by 0.004 (1.045). For some perspective, Jonathan Toews is the next highest point scorer on the Blackhawks, and he is at 0.83 points per game*. Christ, if you need more convincing, please just watch any of these stick-handling videos.

I’ve talked a little about what some of us have taken to calling “The Patrick Kane effect” before. But let’s take a look at exactly what that is, without even focusing on that giant list I made above.

If you’re not familiar with some of these abbreviations or terms, the entirety is listed at the bottom under “Resources” with brief explanations for your convenience. All charts can be clicked on to enlarge. 

Chart courtesy war-on-ice

But, hey, let’s put those numbers into some perspective as to what they mean for the Blackhawks:

SCORING GOALS

Chart compiled by Melissa Peterson | GF refers to CHI Total Goals, PK GF refers to Patrick Kane’s Goal Tally, %GF is the percentage of CHI’s total goals that Kane is responsible for, and %GP is the percentage of the season’s games Patrick Kane played.

Patrick Kane accounts for an average of 11.26% of Chicago’s total scoring playing in 93.75% of the games. For some perspective, if each of the 20 skaters were tasked with accounting for a percentage of goals, Kane would easily cover his and another skater’s contributions.

To focus on this season alone, Kane’s contribution of 13.24% of the goals scored in less than 82% of the games played is a bit daunting. Prior to his injury, Chicago was looking at a CF% of 54.8% (1st in league), a goal differential of +29 and overall shooting percentage of 8.2% over 61 games. Post-Kane’s injury, Chicago has a CF% of 51.2% (13th in league), a goal differential of +3 and an overall shooting percentage of 7.3% over 14 games.

It’s worth noting here that the fact that the overall percentage of total shots has gone down is troubling enough, but the fact that we don’t also see an increase in shooting percentage suggests that the success rate has also gone down remarkably. For some explanation here, the more shots you take overall, the more likely to gain success, but also the more it skews overall shooting percentage until a success is met, since shooting percentage is simply Goals divided by shots and multiplied by 100. When you are taking less shots but still scoring, your shooting percentage spikes. For a mini-lab example: during the 8.2% time, Chicago scored 172 goals. This suggests there were 2,098 shots on goal.

In contrast, during the post-injury 7.3%, there were 32 goals which suggests 438 shots on goal. At that rate, it would have taken them nearly an extra 258 shots on goal to achieve the same 172 GF. The only reason the goal differential hasn’t been hit more, to be frank, is that the goaltender save percentage has risen from 92.1% to 93.5%.

GENERATING PLAY

Kane is not only responsible for scoring goals. We can also look at how he is able to generate play, which as you can tell from his assists portion of his points, he does quite well.

Chart compiled by Melissa Peterson

Here’s a little look at the amount of time Kane has spent on the ice with his teammates. We can take a look at how Kane fairs with each of the other Chicago players by looking at WOWYs (With-or-Without-You’s):

Data courtesy Puckalytics, Charts compiled by Melissa Peterson

If you don’t really know what they are or what they’re used for, WOWYs are meant to examine if a player’s stats are enhanced by being on a line with another player, or if they might not be the best fit for the line they are on. Note: There are things that can skew this spike: A change in usage or deployment (zone starts; more offensive zone time versus more defensive zone time), low TOI together (decreased sample size), score effects (CHI takes less shots when they are leading then when they are behind) are all examples of these factors.

Ideally, a player will see the dark purple bar spike above what a player is producing outside of that pairing. Brad Richards, Kris Versteeg, Jonathan Toews, Brandon Saad, Marcus Kruger and Marian Hossa all see this spike in the first category.

But let’s take a look at his effect overall:

Corsi For per 60 | Charts individually courtesy of war-on-ice, layered by Melissa Peterson

Note: For the CF graph, it is better to be around or above the red line

What these charts shows is a per-60 rate for CHI total (All players including Kane), Without PK, which refers to the CF events for players not on the ice with Kane, and Kane’s rates per 60, which means these are not the actual event rates, but what event rates would look like if he were on the ice all 60 minutes of a game at even-strength 5-on-5 play based on the time he did have on the ice’s rate of play at that strength.

What is most telling, perhaps, on this chart is the amount that CHI’s even strength CF/60 rates tend to correspond with Kane’s even-strength highs and lows rates. What this suggests is that Kane is very good at driving play overall even though he only spends about 15 minutes per game on the ice for even strength play.

Based on the effects felt by the Chicago Blackhawks during his absence, it sort of calls into question just why Kane isn’t considered for a Hart Memorial Trophy nomination.


Resources

  • Corsi: For those that are unsure of what Corsi even is, it is measured as Corsi For and Corsi Against (CA). Corsi is the total number of on-ice shot attempts (on goal, missed, or blocked) taken during a game/series/season. Corsi For is the amount of the total Corsi taken by one team or player on said team. Corsi Against is the amount of the total Corsi taken against one team or player on said team.
  • CA% : Corsi Against Percentage (of total) What this means is they’ve totaled up the Corsi Events that took place for both teams, and divided the individual team’s total by that number and multiplied it by 100 to get a percentage.
  • CP60 : Corsi Per 60. What this means is they’ve totaled up the Corsi events that took place for both teams and divided it by 60 to get an average Corsi Events per 60 minutes.
  • G+/- : Goal Differential. The total number of Goals For (GF) minus the total number of Goals Against (GA). If it is a positive number, the team is outscoring their opponents.
  • FO%: The percentage of Face-offs won.
  • OFOn%: On-Ice Unblocked Shot Attempts on Goal
  • OSh%: On-Ice Shooting percentage
  • OSv%: On-Ice Save percentage
  • PDO: On-Ice Save percentage + On-Ice Shooting percentage
  • ZSO%: The amount of Offensive Zone starts. The larger the number, the more often a team starts (with a Face-off) in their Offensive Zone

*These stats current as of 12:01PM CTL on 30 March 2015

Sources

Stats and charts courtesy of war-on-ice.com and puckalytics.com

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