According to Ken Pomeroy and Mr. Picklesimer (anybody else read “Picklemiester” every time?).� UNC is still slightly favored in a head-to-head matchup, but Kansas has an easier path.� Of course, I suspect this doesn’t include UCLA’s home state advantage should they meet the Jayhawks in the Elite 8.� I might be rooting for Pittsburgh next round.

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These were done, as always, with data from www.kenpom.com.� Each column is the team’s chance of advancing to that round.� They take into account the fact that these games are being played at the Ford Center in Oklahoma City- all Ok. St.’s games are considered “semi-home”.

A couple specifics of interest- Kansas beats Texas A&M 57.5% of the time, and beats Texas 77.9% of the time.� They beat Colorado 98.9% of the time by an average of 29.2 points (although that may or may not be of interest).

Click here for the preview that actually gives you some ideas about how this game’s going to be played. Read on for the one with pretty graphs and hand waving. Format is the same as last time, so you can skip the next paragraph unless you need a refresher. (And for reference, here is the original post that kind of explains what I’m doing).

After the break, for both teams I’ve included a graph that charts the offensive and defensive ratings for each game of the season. Keep in mind that for the defensive rating, lower is better. For both offense and defense, I’ve included a trendline showing roughly how each unit has progressed over the year. The dotted line shows the national average efficiency. I’ve also included the average ratings for their last ten games, to give a snapshot of how the team is playing right now. To give these numbers some context, I show where this would rank in the full-season stats, and what team’s full-season rating is the closest. (more…)

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I posted an efficiency laden preview of the Ohio St vs. Wisconsin game over at yocohoops. I’m going to do the same thing here for the KU-OU game, but with less explanation of the numbers, since you PB readers have had a couple posts to get used to them. For reference, here is the original post that explains what I’m doing. There’s not going to be a lot of analysis, just numbers and graphs. Sorry about that, but I feel Hoopinion and Chalmersfan do a much better job of that than I do.

After the break, for both teams I’ve included a graph that charts the offensive and defensive ratings for each game of the season. Keep in mind that for the defensive rating, lower is better. For both offense and defense, I’ve included a trendline showing roughly how each unit has progressed over the year. Also, the dotted line shows the national average efficiency.

I’ve also included the average ratings for their last ten games, to give a snapshot of how the team is playing right now. To give these numbers some context, I show where this would rank in the full-season stats, and what team’s full-season rating is the closest. (more…)

Recently I posted some game-by-game adjusted efficiency ratings for Kansas, derived from Ken Pomeroy’s Game Plan and season efficiency ratings. The Hawks’ numbers looked good, but Jeremy asked for some context on how the numbers were changing as the season progressed, and how this compared to other top teams. So I ran the game-by-game numbers for Pomeroy’s top 11 teams. (Why top 11? I’ll explain Michigan State’s case later on.) Just showing you a mess o’ single game numbers doesn’t do a whole lot of good - there’s a lot of game to game variation. To smooth that noise out and get a better idea of a team’s general trend, we can look at a moving 10-game snapshot.

Graphs after the jump… (more…)

It has seemed to me like Kansas has gotten their act together a little since the Texas Tech loss. They’ve stopped letting inferior teams hang around, they’ve pushed the tempo, and their offense seems to have benefited. I wanted to see what the stats said about this, so I played with Pomeroy’s.

His Game Plan pages list raw game-by-game efficiency stats on offense and defense. These tell you only half of the story, though. You can see a team’s output, but you need the context of that output. 1.1 points per possession against Texas A&M is excellent. Against Baylor, eh. To get that context, you need the opponent’s seasonal adjusted efficiency stats. Taking those two pieces of the puzzle, I worked backwards from the formulas and parameters Pomeroy lists on his site to obtain adjusted game-by-game efficiency stats.

So, was my perception correct? Has KU’s offense been on an uptick? Here are the game-by-game adjusted efficiency numbers since the Texas Tech loss. “Equiv Rnk” indicates what their Pomeroy Rating rank would be if they played like that every game… OR what rank team they could be expected to beat on a neutral court if they performed at that level.

The offense has indeed taken a step forward. A full season Adj Off Eff of 125.1 would rank 2nd in the country (behind Georgetown). The defense has slipped a little - 84.6 would only rank 6th. One caveat, though - the one game where they needed to play like a top-5 team (vs. Texas A&M), they didn’t.

One other caveat - I cherry-picked this data to show only their recent warm streak. How do the Hawks stack up if I do the same for the other top teams? For each team, I used their most recent 5 to 10 games, whatever gave them the best results. I looked at the top 10 and a few other teams I suspected might be able to crack the top, so there’s a chance I missed some team on a ridiculous tear. But I think these are the 10 hottest teams. “.99+” is the number of .99+ games in the past 10.

Three things jump out at me:

• Georgetown’s offense is unstoppable.
• If not for the letdown against NC St, I’d be calling UNC’s defense unbreakable.
• It’s UNC and everyone else.

I’m sure I’ll mess around with this sort of thing more as we get closer to the tournament. For now it’s nice to see that KU can get as hot as any almost team in the country.

[Was going to wait and post this as a comment to Hoopinion’s usual preview, but I don’t know if I’ll be at the computer at the right time.] I’ve looked at the ratings on the Massey comparison page (plus the Dunkel), and compiled predictions for those that either list them or give explicit instructions on how to calculate them. So, here is what the computers (and Vegas) think about tonight’s game. (Game scores are rounded, so may not match score margins. And I used Sagarin’s “pure points.”)

• Greenfield … +9.3 … 83.1%
• Dokter … +12.5
• Dolphin … +13.3 … 88.4% (79-65)
• Sagarin … +14.5
• Vegas … +15.5 … (79-64)
• Dunkel … +16
• Ashby … +16 … (78-62)
• Pomeroy … +16 … 92% (80-64)
• Lynch … +18.3
• Moore … +22.9

Mean: +15.4 … Median: +15.8 … right in line with Vegas.