I thought this debate had been fully hashed out already but apparently some people still don’t believe that the game score has an impact on shooting percentage (and shot quality).  The following table shows the shooting percentages by game score over the past 3 seasons (2007-08 to 2009-10) during even strength situations where neither goalie is pulled for any reason (including delayed penalty situations).

 Situation Shots Goals SH% Prob<= Prob> Down2+ 23650 1852 7.83 0.3794 0.6206 Down1 30447 2356 7.74 0.1696 0.8304 Tied 60753 4427 7.29 0.0000 1.0000 Up1 26842 2288 8.52 0.9999 0.0001 Up2+ 19351 1779 9.19 1.0000 0.0000 Overall 161043 12702 7.89 0.5024 0.4976

The Situation, Shots, Goals, and SH% columns are self explanatory.  As you can see, shooting percentage is at its lowest in game tied situations, increases slightly for teams that are trailing and increases significantly for teams that are leading.

The second last column titled Prob<= show the probability (according to a binomial distribution) that that number of goals or fewer would be scored on that number of shots if the expected shooting percentage was 7.89%, the same as the overall 5v5 shooting percentage.  The last column titled Prob> is simply 1-Prob<= and shows the probability of getting more than that number of goals on that number of shots.  So, in down 2+ goal situations, there is a 37.94% chance of their being 1852 or fewer goals scored on 23650 shots which indicates that the down2+ shooting percentage isn’t different from the 5v5 mean at any reasonable confidence level.  The same conclusion can be drawn about down1 situations.  But, the shooting percentages in game tied, up1 and up2+ situations are statistically different at an extremely high confidence level.  Essentially there is zero chance that game tied, up1, or up2+ situations have the same natural shooting percentages as game overall 5v5 situations.  In no way can luck be the sole reason for these differences.

So, does this conclusively tell us that shot quality exists and varies according to game score?  It probably does, but I can’t say it is conclusive as it could mean that teams that trail a lot have bad goaltending (the reason they are trailing) and this results in the team leading having an inflated shooting percentage.  So, what if we looked at shots against a particular team.  Let’s say, for example, against the NY Rangers.  Here is what that looks like.

 Situation Shots Goals SH% Prob<= Prob> Overall 5159 386 7.48 0.5135 0.4865 Up1 843 73 8.66 0.9116 0.0884 Up2+ 485 46 9.48 0.9571 0.0429 Leading 1328 119 8.96 0.9800 0.0200 Tied 2004 138 6.89 0.1658 0.8342

I chose the Rangers because they use predominantly one goalie and that goalie is generally speaking a quality goalie.  As you can see, the confidence levels aren’t quite as strong as league wide mostly because of the smaller sample size but if we combine the up1 and up2+ categories we can say that shot quality against the Rangers when the opposing team is leading is statistically different than shooting percentage against the Rangers overall.

If you are interested in seeing what happens with a team that has had chronically bad goaltending, here is the same table for the Maple Leafs.  We see the same sort of things.

 Situation Shots Goals SH% Prob<= Prob> Overall 5309 491 9.25 0.5120 0.4880 Up1 938 94 10.02 0.8098 0.1902 Up2+ 906 100 11.04 0.9698 0.0302 Leading 1844 194 10.52 0.9712 0.0288 Tied 1985 149 7.51 0.0034 0.9966

So what have we learned.

1. Shooting percentages vary according to game score.
2. Those shooting percentage differences can’t be attributed to luck.
3. Those shooting percentage differences can’t be attributed to goaltending.

That means, it must be the quality of the shots that varies across game scores.  In short, we can conclude that when teams get down in a game they open up and take more chances offensively which in turn gives up higher quality shots against which makes perfect sense to me.

When we combine this with my previous post on the Washington Capitals shooting percentage last season, it is probably safe to assume that shot quality exists and we can’t safely assume that all shots can be treated equal in all situations.

The score of a game influences how a team plays.  When a team is trailing they play a more aggressive offensive game, when they are up a goal or more, they play a more defensive game.  The question I answer today is, how does score influence a teams save percentage.

To answer this question I looked at the past 3 seasons of 5v5 even strength save percentage data when the score is tied, when the team is up by a goal, when the team is up by 2 or more goals, when the team is down a goal and when the team is down by 2 or more goals.  For each team and score category I have a data point for 2007-08, 2008-09, 2009-10 as well as a three year average (2007-10).  For each score category I sorted from lowest to highest save percentage and then plotted them on one chart and got the following:

As you can see, when the game is tied generally produces higher save percentages than when a team is leading or trailing and when a team is trailing their save percentages are at their worst.  This is probably not surprising as a team will open up its game in hopes of creating offense but also puts them at risk defensively.  Now, what that table doesn’t tell us is if all teams experience the same score effects or, for whatever reason, do some teams actually have improved save percentages when trailing or leading.  The following chart shows each teams 3 year save percentage by score ordered from lowest 5v5 game tied save percentage.

The majority of teams have the majority of their leading or trailing save percentages below the game tied save percentages but there are a number of occassions where that doesn’t occur and they are mostly related to up2 or up2+ save percentages.  The only teams that had a down1 or down2+ save percentage above game tied save percentage were:

1. Dallas – Down1: 92.51% vs Tied: 91.74%
2. Detroit – Down1: 93.05% vs Tied: 92.16%
3. Pittsburgh: Down2+: 92.87% vs Tied: 92.78%
4. Minnesota:  Down2+: 93.21% vs Tied: 92.89%
5. Florida: Down1: 93.92% vs Tied: 93.23%

On average, teams had their down 1 goal save percentage 1.3% lower than their game tied save percentage and their down 2+ goal save percentage 1.90% lower than their game tied save percentage.  The average team save percentage at 5v5 tied is 92.7% vs 91.4% down a goal, 90.8% down 2+ goals, 92.2% up a goal and 92.1% up 2 goals.  Tailing can have a sizable negative impact on save percentage where as leading can have a minor negative impact.

So what does this mean?  It means we need to be careful when evaluating goalies (and probably shooters to some extent) based on save percentage (special team effects) or even 5v5 even strength save percentage because the game situations a goalie has been exposed to will influence the goalies save percentage.  A goalie on a weak team will have his save percentage lowered simply because his team is going to be trailing more often and be forced to take chances to create offense and thus he will be exposed to tougher shots where as a goalie on a good team who leads the game more than they trail a lot will not face as many tough shots.

One interesting thing I noticed while doing all this was the Toronto Maple Leafs up by a single goal performance over the last 3 seasons.  While they were middle of the pack 5v5 game tied (16th in 3 year 5v5 game tied save percentage), they were downright horrific when they got up a goal.  They just couldn’t hold a lead.  The three worst single season save percentages when up a goal were the 2009-10 Leafs, 2008-09 Leafs, and the 2007-08 Leafs so they were three for three there.  Over the course of the past 3 seasons the Leafs posted an 88.4 save percentage when up a goal which was 3.44 standard deviations from the mean.  Next worse what the Ottawa Senators who were well ahead of them at 90.8, a mere 1.23 standard deviations from the mean.  The good news for Leaf fans is their 5v5 up a goal save percentage is much better this year: 95.6% (better than any team in any of the last 3 seasons), 97.2 for Gustavsson and 93.9% for Giguere so they are much better at maintaining the lead.  Unfortunately this season they can’t score well enough to get them a lead to protect.