Frag
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Everything posted by Frag
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NBA refs are so inconsistent.
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Need Benny Hill music for that half.
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Talk about squeaking by that 4th quarter.
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Could be a good time to snatch one of Anaheim's goalies.
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Also, with Las Vegas getting a team soon, there is always the issue of the expansion draft.
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There is some level of skill from defencemen, but a lot of it is dependant on the coaching/system.
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I've read that Gardiner and Marincin had decent to good numbers.
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I'm so happy the Leafs won. Woooooooo!!
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Goaltenders are such voodoo, it is best to draft them after the 2nd round (or later, even).
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Travis Dermott is a pretty good D prospect. Andrew Nielsen has potential, too.
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Hoping DeBrincat drops to them.
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I'd wonder how Jim Benning would f*** this up.
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Over Matthews? Doubt the Leafs would do that.
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It's weird seeing a Game 7 occur the same day as a Game 1 of the next round.
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He's a better defensive player than DD, which is probably not saying much.
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The Spurs are a possible exception to this. Their bench is a playoff team, which is insane.
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Didn't see that coming.
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Giroux Stepan Plekanec Draisaitl Carter Bennett Couture Nyquist Perreault Carlson Maatta Franson Dubnyk Mrazek Gibson These are my likely keepers. I am open to offers, whether it is one (or some) of the players listed above or one of my prospects not named Kyle Connor.
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I still cannot unsee that video.
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I'll be cutting De Leo, Roy, and Roslovic from my prospect list.
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Good thing I'll likely be cutting more than half my D, or else I would have some really tough choices. Hell, I may still have some tough choices ahead.
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Or increased usage results in decreased efficiency. May have to look at it game-by-game. Also, based on the sample I used, I did not find a significant change in usage with efficient scoring. Age played more of a role in the change in usage, which doesn't surprise me.
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Refs have not been good in this Blues-Hawks game.
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Also, Basketball Reference is annoying.
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Early work, but your previous comment got me interested in determining whether a significant correlation exists between change in TS% and change in Usage between seasons (between the 2013-14 & 2014-15 seasons [n = 384], and between the 2014-15 & 2015-16 seasons[n = 333]). TS% and Usage, obviously, had high and significant correlations between seasons with themselves (very similar results in two separate models), but I found that change in TS% did not significantly correlate with change in Usage between seasons (p > 0.20). Now, this may be due to the fact that players on the tails of the distributions don't see major shifts in their usage/TS% further away from the median. Quality of teammates likely factors in a bit, too. Nonetheless, it's an interesting start. My knowledge in basketball is not as strong as it is with baseball and hockey, so it's possible I missed some important confounding variables to account for in the model.
