Championship game, Rock Chalk day! ❤️🏀💙
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@RockChalkinTexas agree!
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@JayHawkFanToo who do you put on him? I don’t think he likes being pushed around, don’t think Lucas can keep up. Do you? Hope I’m wrong!
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@JayHawkFanToo espn said not to switch channels on our game, 'cause of ISU coming back their last 4 games, same thing could be said of us.
that doesn’t happen though!!!
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Are you talking about McKay? I would start with Traylor who has the speed to keep up with him, but neutralize him by drawing fouls on him. Oubre definitely has the athleticism to go against him and either score or draw the foul…or both.
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@Crimsonorblue22 If they play small to counter ISU, I wonder how Oubre would do on floppy hair…
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@JayHawkFanToo Great minds.
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I love your sign? Is this just a picture or something you have at home? I will see if I can Photoshop just the sign, print it and hang it on the front door for my game time guest to see.
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@ajvan so who is your starting 5? Ellis, oubre(on McKay) Selden, frank and ?
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We do need to watch fouls on oubre, need a lot of minutes from him!
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@JayHawkFanToo Speaking of luck, MR. POM POM has had a sudden epiphany about KU’s defense. Mr. bookcooker has now changed his tune…
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MR. POM POM…I like that. Of course he still ranks KU and other conference teams lower than most.
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@JayHawkFanToo Don’t get the trashing of Pomeroy. He doesn’t “rank” teams - he just plugs data after every game into an algorithm. You may not like his formula, but I would encourage anyone to look at the tempo “rankings” over the past decade. It strikes me that offensive and defensive efficiency as calculated by him have been remarkably well correlated with the best teams during that period - both season long and tournament results. A couple of exceptions, but for the most part, defensive efficiency - and KU has been in the top ten almost every year (NOT last year, and just sneaked in this year due to the Baylor results) - have been highly indicative of the best teams, more so than offensive efficiency.
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I loved Wigs… even though Self didn’t properly utilize him. He should have been instructed WHEN to take it to the rack and WHEN to pull up for the easy mid range J.
I just like Kelly and the impact he has on the rest of the guys. He’s not counted on as our closer, so everyone else has to continue to hustle.
The problem we had last year was not Wigs… it was everyone else! They played super soft (and usually became spectators) because they expected Wigs to carry the load.
Very different chemistry with Kelly. He flows right in with the rest of our guys.
None of this was Wigs fault. Most of it was the media hype. It started with the SI cover. Put the spot light on HIM and not Kansas! The spot light should have been on Kansas having both Wigs and Embiid.
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“Are you talking about McKay? I would start with Traylor who has the speed to keep up with him, but neutralize him by drawing fouls on him. Oubre definitely has the athleticism to go against him and either score or draw the foul…or both”
YES YES YES YES YES YES YES YES YES YES YES YES!
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@Crimsonorblue22 Hmm…I didn’t get to watch the game closely last night but I know Greene wasn’t
️ threes, so…Graham gets the nod! Who you got?
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@ajvan I’m thinking Dg too. He had some bad TO’s, but who didn’t?
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He and the algorithm he uses are one and the same. His algorithm does indeed “rank” teams and it is out of whack with most other computer rankings out there, so I am not the only one that feels his algorithm is flawed. I am on record as saying that some of his data, i.e. tempo is good and helpful, but the ranking portion is seriously flawed. Do a search for posts of mine where I have compared and documented his rankings against other computer and human rankings and you will see that he is consistent at odds with the great majority of other rankings.
Kenneth Massey has a table comparing 40 computer rankings and it is very easy to see where he is off the norm.
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@JayHawkFanToo I’ve seen the Massey composite - don’t recall his being out of whack this year - has KU about the same as the composite last time I had seen it. I don’t follow most others - the reason I follow Pomeroy is because, as I mentioned, his efficiency rankings, esp. defensive, have been HIGHLY correlated to season long success and tournament success each year over the past decade. That may well be true for others, as well - don’t know that.
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Just some exciting Jayhawk news, Jarod Haase’s team is winning conference USA championship.
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Again, look at my posts on the subject and you will see extensive documentation, including screen shots, of the disconnect. I am not making this up, it is recorded and readily available in the forum archives.
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Great news. Hasse is one of the toughest players to ever wear the KU uniform. Floor Burns is an apt description for the title of his book.
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I was hoping everyone would give their opinions on starters for today.
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@JayHawkFanToo Um - I’m not suggesting you are making anything up - and I’m not in a position to compare and contrast. The only thing I know is that his efficiency ratings have been, and apologies for the repetition, HIGHLY correlated to actual season and tournament performance since 2002. That’s it. If there is someone else out there that has demonstrated even better correlated or predictive results over a long time period, I’m just not aware of them - but, would welcome your pointing me in his or her direction. I’m not married to Pomeroy.
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Starters are the same as last night
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@Crimsonorblue22 No one’s assist/TO ratio is untouchable when Bad Ball is in effect…except Mason’s?
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@Crimsonorblue22 C’mon Bill, mix it up a little to keep us happy, would ya?
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Here’s a look at the past Big 12 title games.
1997: Kansas beat Missouri
1998: Kansas beat Oklahoma
1999: Kansas beat Oklahoma State
2000: Iowa State beat Oklahoma
2001: Oklahoma beat Texas
2002: Oklahoma beat Kansas
2003: Oklahoma beat Missouri
2004: Oklahoma State beat Texas
2005: Oklahoma State beat Texas Tech
2006: Kansas beat Texas
2007: Kansas beat Texas, 88-84 (OT)
2008: Kansa beat Texas
2009: Missouri beat Baylor
2010: Kansas beat K-State
2011: Kansas beat Texas
2012: Missouri beat Baylor
2013: Kansas beat K-State
2014: Iowa State beat Baylor
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Maryland behind, that’s good for us? Not for turg!
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Also heard the crowd at p and l was 80-20 ISU
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Your kids do my favorite art work about KU of all time. Send them to a good art institute.
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The media is cruel. That kid will have his tears documented throughout his entire life. Just part of us being demonized by the media. “Those nasty Jayhawks made this poor kid cry! And that EJ player rubbed it in with his emphatic slam dunk!”
What they failed to report was the numerous times ISU fans called EJ the “N-word” and other tasteless abusive language.
ISU got what they deserved. I’d replay all that hate stuff to our current team to build the enthusiasm.
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@Crimsonorblue22 Here I go again, all Manic Depressive n shizz. 2015 : ISU beats KU
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@Lulufulu are we sure that’s not you crying on mrs mayors lap?
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@DCHawker Who devised the algorithm? I don’t really give 2 figs about Kenpom but Nate Silver he ain’t.
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@Crimsonorblue22 HA! It might be me, I look a lil young in that photo though and its not my best side.
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@sfbahawk Well, his name is attached - if he didn’t, he probably has other (legal) problems as he has a subscription model
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If you want better results look at the original, Jeff Sagarin. You can also check Kenneth Massey, who many think has the better system and his web site also lists a summary of all 40 computer rankings so you can see for yourself how well they correlate to reality and each other.
The problem I have with some of the systems is that they were developed by people that might know a lot about statistical methods but are really clueless about basketball and try to explain everything with numbers, even when they really do not duplicate reality.
As I indicated before, I develop (engineering) models for a living and the fist test we run is what we call the “reasonableness test” in which you look at the results/predictions and match them against the real world results and see how close they match; the better the match the better the model. For example, if I develop a model to sort KU players by height based on various physical measurements, the logical order would be:
- Landen Lucas 6-10
- Hunter Mickelson 6-10
- Cliff Alexander 6-8
- Sviatoslav Mykhailiuk 6-8
- Jamari Traylor 6-8
- Perry Ellis 6-8
- Kelly Oubre Jr. 6-7
- Brannen Greene 6-7
- Wayne Selden Jr. 6-5
- Christian Garrett 6-4
- Josh Pollard 6-4
- Evan Manning 6-3
- Tyler Self 6-2
- Frank Mason III 5-11
Or something very close to that, based on numbers presented in the KU Official Roster.
Now, if the model has Lucas and Mickelson reversed or Alexander, Svi, Traylor , Perry and and Green in different order but grouped together it would also be acceptable since they are all roughly the same height. However, if the model had Tyler Self ahead of Ellis and Mason right behind Oubre and Traylor and Selden at the bottom, you would know the model has some serious flaws, right? It does not make a difference what numbers you use to justify, we know it is wrong because we can simply put them side by side, and unless you are 100% blind, you can see the difference clear as day, and again, regardless of the numbers, the difference is obvious, and it is even more convincing when 38 out of 40 models list the order as shown above or with slight variations. Of course the model creator can say the he used a “subjective factor” (Pomeroy’s Luck) to arrive at the “true” height and justify the numbers, but the end result still does not pass the reasonableness test. I guess the justification would be in the words of Groucho Marx …who are you going to believe, me or your own eyes?
I am not sure how closely you have followed Pomeroy’s rankings throughout the season in relation to KU, a few of us in this forum have, and like I indicated, I documented the numbers and the discrepancy with the great majority of the other rankings. I believe this is as much as I can write on the subject, you can decide for yourself which predictor your trust the most…unfortunately there is no model to predict that…:(
In the end there are no right and wrong or blacks and white answers and its is really 50 shades of grey…minus all the kinky stuff…:)
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@JayHawkFanToo great explanation!
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@JayHawkFanToo Thanks for following up - appreciate the information.
