PSA: Hoop Explorer has shot charts now: https://hoop-explorer.com/?gender=Men&year=2024%2F25&
You can apply their queries to look at shot charts in different lineups.
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NET is out. We are 125.
68 WAB tho, and undefeated in quads 2-4. Put us in Lunardi, you coward!
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NET of 125 not good, but it is early so the raw number doesnt mean much. Do have a Q2 win which is good, both losses in Q1 that is good. If we could have blown out the teams we should have blown out we would probably be up in the 60s/70s. Would be nice to beat either Florida/Memphis both would be good wins. Win one of those, avoid losses to Bethune Cookman and American and we arent in horrible shape heading into conference play.
And oh yeah, dont get blown out!
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@Raleigh_Hoo How are you thinking about weighing NET vs WAB vs quadrant-by-quadrant record in your bracketology?
I havent thought about it too much yet honestly.
But WAB will be like SOR to me, which carries alot of weight. SOR since it is a resume based metric, not predictive metric, has carried a high correlation with at-large selections in recent years, in fact I think it is the main reason we got an at-large bid last year.
For me it is 1) Quad records 2) SOR/WAB 3) NET
With that said, it is understood you have to have a NET top 70/80 to even be considered generally.
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I am hoping the committee jettisons looking at quad records in favor of WAB. WAB is a more principled and legible way of looking at the same thing that quad records capture.
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Agreed. If we can go 8-3 in OOC and then sneak to 12-8 in the ACC to finish 20-11, thatās a little better than I was expecting pre-season (which was 18 or 19 wins). Maybe the 5 or 6 seed in the ACC and a win or two in the ACC tournament. Thatād be a nice result.
Of course, that probably means the NIT and a coaching search in March so its not a good result relative to recent history, just better than my expectations.
Iām not in love with the analytic approach here (specifically the amount of dichotomizing), but this post by EvanMiya argues that teams with more newcomers are falling short of expectations compared to teams with returners:
Maybe thatās just obviously true to people, but good to put some numbers on how much continuity matters.
Side note: I did not realize how much KState has been struggling relative to expectations. Coleman Hawkins was their big splash transfer and heās been bad on offense. Dug McDaniel hasnāt been great for them either.
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Itāll be interesting to redo the analysis at the end of the year to see if the transfer-heavy teams close the gap. Anecdotally speaking, weāve seen some of our teams do well in the early season relative to less experienced teams only to drop off towards the end of the year.
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Random thing I noticed while sadly looking through player stats:
Per KenPom, TJ Powerās current ORtg is the worst of any player getting āsignificant minutesā in the CTB+CRS era. Worse than Dante last year (his saving grace was being a shockingly effective rebounder) or Morsell in 2020 (who wins the āworst results over the largest amount of playing timeā over Rohde last season). The only real arguments revolve around where we want to set the cut-off for āsignificantā and include Teven Jones in 2014 and Jespersonās first year in 2012.
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@AdventiveQuasar or anyone else who knows, with the demise of hoop-math.com (no longer updating as of Nov 17 2024), where do you find transition stats and similar?
I donāt see it in Torvik or KenPom, at least obviously. Maybe one of those pay sitesā¦
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Hoop Vision team Analysis page lists the transition percentiles I think, though they donāt have a good team leaderboard to look at all teams.
Edit: hoop explorer: https://hoop-explorer.com/?gender=Men&year=2024%2F25&
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Got a link? You mean Sperberās old site?
Sorry meant a different site:
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Awesome. Thanks!
I signed up for the free tier of cbbanalytics.com and thereās some interesting stuff in there.
A few interesting things on our last 5 v full season:
Last 5 fast break and second chance points:
Full season fast break and second chance points:
Transition - last 5:
(now with context added, sorry)
Transition - full season:
Some improvement in transition and second chance points. Nothing dramatic, but every bit helps.
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Somewhat off topic here, but hopefully close enoughā
Does anyone know a good source to get live-ish player data (only need player name and scoring) for NCAA tournament games?
A friend of mine runs a pool where you draft individual players in march madness and get their points scored for the entire run, and he keeps the stats by doing manual data entry, but surely there is a better way? Bonus points if you can get womenās too, every team selects one player on the womenās side. There are lots of places to pull regular season data in an easy form, but not many for post-season only.
Also if anyone has any good ideas on building a model for drafting let me know lol. Iām the reigning champion off of a pretty basic PPG x Probability of advancing model, but always looking to improve!
I would try hereā¦
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Oh I think this is perfect actually, depending on how quickly they update it during the tournament. Thank you!
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