REAL EFFECTS & TEAM SH%
The overwhelming majority of differences between teams EVshooting%’s was accounted for by luck alone.
In Conclusion:
· Possession may not be everything, but in the big picture it’s damn close to it.
· Unless you’re getting an established star goalie, it doesn’t make a lot of sense to spend a lot on a second tier guy, either in cap space or trade assets. Because the gap between 2nd tier and third tier appears tiny.
· Guys coming off of poor percentage years, but with good underlying numbers, and who play a solid game … these should come at reasonable rates. They should be players that the Oilers buy, not sell.
· Right now in the NHL, the difference in ability between teams to bury their shots (EVshooting% when tied) is virtually nil.
· None of the team-to-team variance in EV S % when the score is tied is due to ability.
LEAFS SHOT QUALITY ANALYSIS
teams rarely sustain good records without a decent shot differential.
To do so, you need your team to have a much higher shooting percentage than its opponents. Some combination of good goaltending and good shooting and a system that eschews long-range shots can make that possible, of course
But even for them, shot differential drives their results more than shooting percentages do.
· The vast majority of the NHL spends the vast majority of its time in that middle band from about 9-10 percent
· About once per year, a team will pop up with a >12 percent shooting percentage over a 50-game span.
· An appearance above 12 percent is generally a brief spike,
EXPECTED SH% REGRESSION
hockey analysts have advocated regressing shooting percentages to league average, but is there a more accurate way of forecasting shooting performance?
At first glance it just doesn’t seem intuitive that every team’s shooting percentage will regress towards the same number, but there is a well-documented basis to this practice.
random variation alone could account for virtually the entire difference between a team’s (even strength) shooting percentage and the league average, leaving almost no room for a team’s skill or shot quality.
Worked out each team’s expected shooting percentage based on each of its player’s individual shots and previous career shooting percentages.
How big is the gap between expected and actual goals? It can be huge, actually +/- 50 or more goals a year.
There’s some evidence to suggest that teams have very slightly different resting points, and that there may therefore be a way to improve on simply regressing shooting percentages to the league average by blending in this process.
TRUE TALENT LEVEL NHL SH% (2 ARTICLES)
It appears there’s no variance in talent at all – that SH% is, indeed, completely random! But … not necessarily.
This analysis suggests that teams who have a very high SH% are demonstrating a couple of 5-on-5 tied goals worth of talent.
Team shooting percentage is considered an unreliable indicator of talent, because its season-to-season correlation is low.
SH isn’t that reliable – after all, there were more negative seasons than strong positive ones.
But: what if we expand our sample size, by looking at the correlation between pairs that are TWO seasons apart? Different story, now:
Now, we do have evidence of talent … and guessing adds only around 0.6 points. If you refuse to allow a guess of how shots vary in quality … well, you still have evidence, without guessing at all, that teams must vary in talent with an SD of at least 0.284 percentage points.
PREDICTING TEAM SH% FROM PLAYER TALENT
For NHL teams, shooting percentage (SH%) doesn’t seem to carry over all that well from year to year.
If shooting percentage is truly (or mostly) random, the correlation between team expected and team actual should be low. It wasn’t that low. It was +0.38.
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