Using Shooting Percentage to Guide Your Fantasy Hockey Decisions

Heading into tonight’s game, there have been 827 goals scored on 8,784 shots on goal in 152 NHL games. The shot totals for NHL teams, on average, are just under 300. According to this article by JaredL of Driving Play, shooting statistics are still strongly dominated by luck at this point in the season.

This time last season (measured in shots, not dates), we analyzed the shooting statistics of players who had taken at least 25 SOG. The end result was that we compiled a list of players from whom we expected a decrease in scoring. One month later, we re-examined this same list of players to find that 90% of those players experienced significant drops in scoring.

We will now look at all NHL players who have taken at least 25 SOG this season. We have compared their 2012-2013 SH% to their career SH%. We will use a simple metric which we’ll call the Overage which is basically a % difference between the two numbers: 100*(NOW_SH% – Career_SH%)/(Career_SH%). Any player with at least 25 SOG and an Overage greater than 50 will make the list. What are we expecting from the players on this list going forward? In general, as a player takes more SOG, his SH% should approach his career SH%. Players with high Overage values on our list are likely to experience a decrease in scoring as the season moves on. As a fantasy hockey manager (depending on your scoring settings), you can loosely interpret this Overage as a measure of a player’s current trade value.

On Wednesday, we’ll reach the 1/4 mark of the fantasy hockey season. If you’re looking to make a deal in your league, why not consider moving some of the players below while their value is still high?

Players Most Likely to See a Decrease in Scoring
Player Team GP G SOG SH% Career SH% Overage
Patrick Kane CHI 11 8 30 26.7 11.1 140.5
Alex Edler VAN 10 3 26 11.5 5.6 105.4
Kris Letang PIT 10 3 28 10.7 5.3 101.9
Joe Pavelski SJS 10 5 26 19.2 10.0 92.0
Logan Couture SJS 10 6 25 24.0 13.1 83.2
Tomas Plekanec MTL 10 6 31 19.4 11.1 74.8
David Clarkson NJD 10 7 41 17.1 10.0 71.0
Eric Staal CAR 9 7 37 18.9 11.2 68.9
Dustin Byfuglien WPG 6 3 26 12.0 7.3 64.4
Patrick Marleau SJS 10 9 39 23.1 14.3 61.5
Thomas Vanek BUF 10 10 42 23.8 15.4 54.5
James van Riemsdyk TOR 11 6 37 16.2 10.5 54.3
Jason Pominville BUF 11 6 34 17.6 11.7 50.4

Comments (4)

  1. Interesting. Can the same analysis be applied to players who are underperforming and might be due for an increase in goals? I have to think players like Phil Kessel or Corey Perry are due. Thanks for the insight.

    • Mike

      @Marius – I’m a bit more hesitant about using this logic in reverse. While I believe there are players who are ‘underperforming’ due to luck (e.g. Kessel, Malkin), there may be unknown factors driving down their SH%.

      Last year, Patrick Kane was on the underperforming side of this list, but he was playing through a wrist injury that many fantasy hockey managers didn’t know about. Scott Hartnell would have made that same list in 2009-2010, but he was having personal issues with a messy divorce.

      You also have to consider the natural tendency of a player’s SH% decreasing with age (typically beyond the age of 28).

      In short, yes, I think the logic should work in reverse. But, a certain asymmetry exists: players with higher than normal SH% are succeeding mostly due to luck, while players with lower than normal SH% may be failing due to one of many reasons (and one of those reasons might be luck).

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