SCORE EFFECTS AND THE PERCENTAGES
PLAYING WITH THE LEAD AND PERCENTAGES
Playing with the lead is favorable to the percentages. The relationship is quite strong, too
What’s interesting, however, is how the relationship varies according to shot differential.
In general, teams with negative shot differentials tend to do much better in terms of the percentages (SH%, SV%) than what would otherwise be predicted on the basis of their [Minutes played leading – Minutes played trailing] differential.
· The team that plays with the lead will tend to have a higher scoring chance/shot ratio than a team that plays from behind.
o This is because a team that plays from behind is forced to take more chances in an attempt to tie the score.
· However, a team that has a good shot differential will tend to get the better of the play regardless of whether it is leading or trailing.
· Likewise, a team with a poor shot differential will tend to get dominated territorially regardless of goal state
THE DRIVERS OF SCORE EFFECTS - SH%, SV%
teams that are leading tend to score on a higher proportion of their shots (i.e., they post a higher shooting percentage) than teams that are trailing. The obvious corollary to this is that teams that are leading also see their save percentage rise, giving them a percentage advantage on both offense and defense.
There are 2 things to note here: first, when games are tied teams play better defensively, and fewer shots go in than when one team is leading. This is true for both offense and defense,
Second, goalies and shooters for teams who are leading get a significant bump when they’re up a goal or two: shooters who are up by 1 tend to score on 0.6% more of their shots than shooters who are down by 1, and shooters who are up by 2 nearly hit a 9.5% shooting percentage, almost 2% higher than they shoot when the game is tied. Goalies see the same trend: their save percentage when up is 0.5%-1.5% higher when leading than it is when they’re behind.
Summary:
· Teams post higher shooting percentages when they’re ahead than when they’re behind. But they also see the lowest shooting percentage in tie games.
· Consequently, teams post higher save percentages when they’re ahead than when they’re behind. When they’re tied, they record the highest save percentages of any score state.
· The increase in shooting percentage when leading happens to teams regardless of how much underlying shooting talent they have.
· The increase in save percentage when leading happens to teams regardless of how much underlying goaltending talent they have.
· Teams tend to take more of their shots from high danger zones when they’re ahead. Teams tend to take more of their shots from low danger zones when they’re behind.
· Score effects happen within danger zones as well – even after we’ve split up the shots by danger zone, we still see the same patterns that we do in the overall dataset. In other words, the shift in where shots are taken from is not enough to explain why teams shoot better when they’re leading.
SCORE EFFECTS AND SHOOTING PERCENTAGE
Shooting percentage when trailing is shown to be higher than that with the score tied right up until the end of regulation. But there’s a pretty logical reason for that as well. Teams tied near the end of regulation are playing for overtime. They are far more likely to dump shots from the blue line than to pinch to create opportunities. And both teams are far more worried about not allowing a goal against than scoring a goal for. There is massive loss aversion in play here; shooting percentage is bound to drop. You can’t compare the two situations because looming overtime (or more specifically the loser point) is a confounding variable.
SCORE EFFECTS AND SH%
In any particular season, the sum of a team’s shooting and save percentage is correlated with how much time that team spent playing with the lead, and this relationship is, in turn, related to shot differential.
Here is what has demonstrated thus far:
· The distribution of team EV S% when the score is tied is entirely random.
· There are no ‘real effects’ with respect to EV S% when the score is tied. That is to say, it has no sustain.
· Some of the variation in overall EV S% at the team level is non-random. That is to say, there is more variation than what would be predicted from chance alone.
· This being the case, the logical implication is that the playing to score effect is one of – perhaps the only – non-random contributions to EV S%.
In terms of the second post, I was basically positing the leading/trailing effect as the cause of the increased variance in overall EV S% and SV% relative to EV S% and SV% when the score is tied.
SH% BY GAME STATE
We can see that the further a team gets behind, the more they out-shoot their opponents.
Shooting percentage increases as teams have bigger and bigger leads, but doesn’t change much as they fall further behind
In terms of shot quality, we see roughly the same effect – expected shooting percentage increases as a team gets in the lead, but stays essentially constant as it falls further behind.
EFFECT OF PROTECTING A LEAD ON SH%
(Sept 2009)
Teams do, and should, play to the score. What I did not expect is that they also shoot to the score.
Teams playing with the lead take 5 shots less per 60 minutes than teams playing from behind, a difference of over 15%.
The shots of leading teams, on the other hand, are much more dangerous: while they would have been expected to succeed at a 9.2% success rate, they in fact did so at 9.9%. With over 21,000 shots last year, that’s a difference of 130 goals.
SCORE EFFECTS ON EV SH%
(Jan 2011)
Score effects account for approximately 1.2% of the variation in team even-strength shooting percentage. This is significantly less than the 70% due to luck or the almost 30% due to other factors like shooting talent, shot quality and scorer bias.
Simply put, while shooting percentage varies by score, score effects have only a negligible impact on team shooting percentage over the course of a season.
SCORE EFFECTS ON SH%
(Mar 2011)
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
shot quality exists and varies according to game score?
· Shooting percentages vary according to game score.
· Those shooting percentage differences can’t be attributed to luck.
· 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.
SCORE EFFECTS AND SV%
SCORE EFFECTS ON SV%
(Jan 2011)
how does score influence a teams save percentage
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 isn’t surprising. If the team is losing, they probably aren’t getting very good goaltending. And if a team is winning, it’s probably because they are getting good goaltending.
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.
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.
Comentarios