Fun fact: Jimmy Vesey has more ixGF and a higher ixGF/60 than Wild Bill.
That’s 5v5. Trying to analyze Vesey’s powerplay numbers would give me a stroke because he’s an awful powerplay player.This is kind of shocking. 5v5 or all situations? How does their ixFsh% compare?
Karlsson is an arbitration eligible RFA. Is he gonna get paid based off this? What do you do here? I think he's UFA eligible after the 19-20 season.
Two year bridge at $4.5m AAV?
ixFSh% is based off Manny's xG model and is essentially the % chance a shot has at going in the net. Used as a complement to raw xG, basically "average danger".That’s 5v5. Trying to analyze Vesey’s powerplay numbers would give me a stroke because he’s an awful powerplay player.
I forget what ixFSh% is, but Vesey is at 9.49 and Karlsson is at 7.78. They’re both at basically 12 iCF/60 (11.8 vs 12.3)
Vesey really isn’t as bad as people make it seem. He’s overused, but he’s fine as a 3rd or 4th liner. The whole media hype around him skewed people’s expecations and still does. I’m curious to see him under a new coach.
Oh sweet, thanks for that. Vesey is better at that than Karlsson too hes actually 7th in the NHL when filtering for 400minixFSh% is based off Manny's xG model and is essentially the % chance a shot has at going in the net. Used as a complement to raw xG, basically "average danger".
R and Python are freeWork gives us excel for free, and I ain't spending any money to get yelled at on HF
Very few people appreciate the work anyway.
The only pythons I know live in Australia. One step at a time.R and Python are free
I'm learning how to use excel for work and I just ran some correlations.
Of the top 30 most used defensemen the last 4 years:
Rel CF% to TOI QoT - -0.07 (Almost nothing)
Rel CF% to CF% QoT - -0.21 (Crap)
Rel CF% to TOI QoC - -0.41 (Below Average)
Rel CF% to CF% QoC +0.50 (Moderate Correlation)
1)I was surprised by how well QoC performed. I think we've underestimated it.
2)CF% QoC > TOI QoC. CF% beat TOI for both. This confirms what I thought. Actual results > what coaches think they are seeing.
3)None of these even sniffed the +/-0.7 barrier of being a strong correlation. At the end of the day, the driving force behind a player's analytics is THE PLAYER. Everything else is context.
Excel? Peasant.... We actually still use at Excel at work and it is a royal pain in my ass, on the other hand, the things we've figured out how to do in it, in terms of automated reporting since we refuse to move to R and the agency won't get Tableau for us... I mean... some of these formulas are stupid at this point.
Never really had a reason toYou've never used excel before?
Doesn't make it right.Most companies use excel.
Never really had a reason to
I don't really do advanced stats. I just read the ones already available.So what have you been using to do your advanced stats on?
I lean towards R^2 as well, but everything needs to be caveated. Correlation != causation, etc...@silverfish I prefer to use R Squared over correlations because it's more intuitive what the number actually means. Thoughts? You think I'm missing out by not using correlation?
I lean towards R^2 as well, but everything needs to be caveated. Correlation != causation, etc...
The main question I try to focus on is how well does one variable predict another.
I don't really do advanced stats. I just read the ones already available.
I want to make a Zipay Twitter bot.
I think I'm squared up with the NWHL for the most part so this seriously may be my next projectLove bots like that. They can really come up with some brink-of-sanity type profound **** lol
Inspired by this?I want to make a Zipay Twitter bot.