Cole Caufield breaking out

Lafleurs Guy

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Jul 20, 2007
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You mean hot streaks are a thing? Players don’t always continue to shoot at 25%?
And he won’t. He’s at 25 now and that won’t continue. He is way off from last year in terms of shots on goal. The Canadiens have sucked at generating offensive pressure. Past few games he’s finally getting more shots. Of he can keep that up he should get 40+ and maybe even 50.

Last year should’ve been a career year. 315 shots but couldn’t score for his life. Shoulder surgery seemed to have sucked the zap out of his shot. He’s able to score from further out once again.
 

rielledup

Registered User
Sep 17, 2015
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He's probably not gonna keep up his low shooting number too. 2.6s/g vs 3.8s/g last year and 3.6 the year before. I don't think he get 50g this year but 40-45 is something that could happen
I have in fantasy because I figured based on his shot numbers last season he should get 40-50 this year but now his shots are way down which is hard to understand.
 

Lafleurs Guy

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Jul 20, 2007
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probably not, although he should be shooting more.... hes only on pace for 215, while last season he had 314

that said, I wouldnt bet on 50 this season
I wouldn’t bet against it.

He should’ve had a career year last season and that shoulder got in the way. He should’ve had 50 last year. To put it in perspective the previous 82 games under MSL he’d shot at around 18 percent. At that number he’d have been at 56 goals. At 16 percent (very reasonable for someone of his talents) he’d have been at 50.

Is he going to shoot at 25 percent the rest of the way? No. But I think you’ll see a lot more shots than you’ve seen. He’s already starting to ramp up there. He’s playing really good hockey despite being on a pretty weak team.
 

ijuka

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May 14, 2016
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I wouldn’t bet against it.

He should’ve had a career year last season and that shoulder got in the way. He should’ve had 50 last year. To put it in perspective the previous 82 games under MSL he’d shot at around 18 percent. At that number he’d have been at 56 goals. At 16 percent (very reasonable for someone of his talents) he’d have been at 50.

Is he going to shoot at 25 percent the rest of the way? No. But I think you’ll see a lot more shots than you’ve seen. He’s already starting to ramp up there. He’s playing really good hockey despite being on a pretty weak team.
Aggregating the previous 3 seasons, he's got 77 goals over 67 expected goals. Now, he's got 16 goals over 8.42 expected goals.

Adjusting 24 games over a 82-game season and assuming the expected goal generation remains constant, he would have 28.8 expected goals over the season.

Taking the remaining 20.4 expected goals and assuming he'll score on them with a similar ratio to the one he has over his career from the previous three season, he would end up with around 39 goals.

By saying you wouldn't bet against him scoring 50, you're expecting his expected goal generation this season to increase significantly, or you're expecting him to score at a much higher ratio in relation to the expected goals than he has in his career thus far.

But it just is rather unlikely. Even if he scores on his expected goals at the rate of Auston Matthews, he'll only end up with 46 goals. And how likely is that?

By the current information, I'd definitely bet against him reaching 50.
 

ijuka

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pace only doesn't count when it goes against your argument or against your team, especially while speaking with a rival fanbase
now that it's on the other side it counts lol
The reason pace doesn't count is because variance is expected to decrease as the sample size increases. This flattens the difference between the weakest and strongest performers. So, if you take the strongest performer and expect his rate to continue over the course of an entire season, it just is extremely unlikely, even if his advantage over the rest of the field remains identical.

Essentially, we're assuming that for the strongest performer, there is, in addition to skill, also some luck; meaning it's been a fortunate sampling session, and the actual mean value for the generator is lower.
 

Lshap

Hardline Moderate
Jun 6, 2011
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The reason pace doesn't count is because variance is expected to decrease as the sample size increases. This flattens the difference between the weakest and strongest performers. So, if you take the strongest performer and expect his rate to continue over the course of an entire season, it just is extremely unlikely, even if his advantage over the rest of the field remains identical.

Essentially, we're assuming that for the strongest performer, there is, in addition to skill, also some luck; meaning it's been a fortunate sampling session, and the actual mean value for the generator is lower.
I've noticed that "Pace" and "xGF" are equally misused to smudge facts, depending which context you wish to ignore.

Right now, the main fact is Caufield is tied for 3rd in goals-scored. The most reasonable predictions have him finishing with 40-45 goals, with the upward possibility of 50.
 

Lafleurs Guy

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Jul 20, 2007
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Aggregating the previous 3 seasons, he's got 77 goals over 67 expected goals. Now, he's got 16 goals over 8.42 expected goals.

Adjusting 24 games over a 82-game season and assuming the expected goal generation remains constant, he would have 28.8 expected goals over the season.

Taking the remaining 20.4 expected goals and assuming he'll score on them with a similar ratio to the one he has over his career from the previous three season, he would end up with around 39 goals.

By saying you wouldn't bet against him scoring 50, you're expecting his expected goal generation this season to increase significantly, or you're expecting him to score at a much higher ratio in relation to the expected goals than he has in his career thus far.

But it just is rather unlikely. Even if he scores on his expected goals at the rate of Auston Matthews, he'll only end up with 46 goals. And how likely is that?

By the current information, I'd definitely bet against him reaching 50.
Once MSL took over, CC scored 48 goals in his next 83 games before getting injured. It was spread across two seasons so most people didn’t notice. Last season he played very well but couldn’t buy a goal. 314 shots… should’ve been a career year.

This season I expected him to bounce back and he has. I completely agree that he won’t continue at 24 percent, but I also think he’s not going to finish with only 200 shots either. He’s already bringing those shot totals up and I expect that will continue.

So I’ll sum it up this way: His puck luck won’t continue but he’ll likely help to mitigate that with higher shot totals. And no it won’t surprise me at all if he gets 50. I expected him to do it last year but the shoulder got in the way.
 
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ijuka

Registered User
May 14, 2016
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I've noticed that "Pace" and "xGF" are equally misused to smudge facts, depending which context you wish to ignore.

Right now, the main fact is Caufield is tied for 3rd in goals-scored. The most reasonable predictions have him finishing with 40-45 goals, with the upward possibility of 50.
Ideally, you are ignoring no context, and are using all the information available to you. However, doing so would essentially necessitate building a complete statistical model, which is a bit of an overblown measure just for a simple forum post.

The aim is to estimate the generator. That is, what process generated the goals Caufield scored? Were those goals on the low end or the high end of all possible outcomes of an identical generator over 100 million equivalent sampling runs?

Expected goals are most predictive of future goals; more predictive than goals themselves. Additionally, expected goals are very predictive of expected goals. Hence, the decision made was to assume expected goal generation remains similar, and for goal generation to continue at a rate consistent with what it was for his past three years.

Goal generation has far greater variance than expected goal generation, so the sample size required is greater for usable results. It's far less likely for expected goals to be half the amount they should be, versus goals being twice the amount they should be, for instance(which is why expected goals are favored as predictors, and what motivated modeling them in the first place).

Again, a complete statistical model utilizing every stat available would be more effective, but a bit of an overblown measure for a forum discussion and a post that I'll write in under five minutes. Nevertheless, this is a far superior method to using shooting% regression, because your expected shooting% is strongly tied to your expected expected goals.
 
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