Archive for the 'South' Category

There’s a very good chance that this game (though it will likely be played at a faster pace, and thus, be higher scoring) will produce a lower rate of offensive efficiency than the Kansas/UCLA game. Neither Ohio State nor Memphis shoot the ball especially well (though Ohio State is clearly better both from the field and the line), though both compensate by taking good care of the ball. Memphis’s poor free throw shooting may not be much of a hindrance in this game as Ohio State does an excellent job of keeping their opponents off the free throw line.

Though Memphis is unquestionably a good team, two of their most important strengths (offensive rebounding and opponents’ turnover rate) are quite likely influenced to a significant degree by the vast talent gap between themselves and most of the teams on their schedule.

Ohio State is good both at taking care of the ball and keeping their opponents off the offensive glass. There’s no doubt Memphis is capable of performing better in both of these areas than the average Ohio State opponent, but it’s unlikely that the Tigers can match their typical performance, against their relatively low-level of competition on the season as a whole, in either area when playing Ohio State. Of course, in one game anything can happen.

The Memphis tendency most likely to cause Ohio State problems is the Tigers’s unwillingness to allow their opponents to attempt three-point shots. (On the year, just 28.8% of opponents’ attempts have come from behind the arc.) In their narrow wins over Xavier and Tennessee, Ohio State took 37.7% of their shots and made 39.5% of those attempts. Ron Lewis (53.6% of FGA are 3PTA), Jamar Butler (76% of FGA are 3PTA), and Ivan Harris (57.9% of FGA are 3PTA) will have to find atypical ways in which to maintain their scoring contributions.

It bears reminding that, prior to the unlikely events (missed Acie Law IV layup followed shortly thereafter by consecutive made free throws by Antonio Anderson) that secured Memphis’s narrow win over Texas A&M, the best team Memphis had beaten all season was Kentucky. In Maui. In November.

FIRST 3 GAMES ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Ohio St. 62.9 125.5 95.2 .9600
Memphis 65.3 115.8 84.6 .9737

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Ohio St. 70, Memphis 68
  • Last 10 Prediction … Ohio St. 67, Memphis 63
  • Vs. Good Prediction … Ohio St. 69, Memphis 68
  • Trendline Prediction … Ohio St. 65, Memphis 62
  • Tourney So Far Prediction … Memphis 66, Ohio St. 64

UPDATED GRAPHS

Ohio St. team capsule

Memphis team capsule

Everybody loves a rematch.

At least I do.

The last time these two teams played both teams shot poorly, combining to shoot 6-39 on jump shots. Both teams made a lot of money with layups and dunks, but ultimately, OSU prevailed at home 68-66. Judging by that game alone, one would expect a very close game. And one is probably right to do so. Tennessee is a better team than they were during UT - OSU round one, and HTB’s trendline analysis predicts an almost identical score of 68-65, still in favor of the Buckeyes.

But for UT, Wayne Chism has emerged as a dynamic presence, perhaps the answer everyone’s looking for to the question of who can drag Greg Oden from his position in the post and open up the lane for penetration by UT’s guards.

Despite looking pretty unimpressive in beating Xavier, OSU should win this game, but not by much. The crowd will probably be behind UT, which may give them energy to overcome what should be a slight disadvantage relative to the much hyped Buckeyes.

FIRST 2 GAMES ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Ohio St. 64.3 118.0 87.6 .9685
Tennessee 69.5 134.8 98.2 .9745

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Ohio St. 79, Tennessee 70
  • Last 10 Prediction … Ohio St. 71, Tennessee 68
  • Vs. Good Prediction … Ohio St. 77, Tennessee 70
  • Trendline Prediction … Ohio St. 68, Tennessee 65
  • Best 6 Prediction … Ohio St. 78, Tennessee 70

UPDATED GRAPHS

Ohio St. team capsule

Tennessee team capsule

This one is a battle of genres…Memphis is a Mystery and Texas A&M is a Western, complete with a hero who has made more big shots in the last half of the season than most teams do in a decade. Statistically speaking, this game is a wash. Texas A&M has played a little bit better over the course of the season, but Memphis is on the rise and gaining respectability as they’ve emerged from the close-lit caves of Conference USA to the bright lights of the Big Dance.

Complicating predictions is the fact that both teams are probably a little misunderstood. Gillespie’s Aggies are broadly known for their defensive prowess, but they’ve actually been a better offensive (or oh-ffensive if you’re Rick Majerus, and if you are Rick Majerus, you are probably not reading this) team than defensive over the last half of the season. Similarly, or maybe oppositely, people tend to think of Memphis as a running, gunning group of athletes. But they’re actually really good defensively.

Memphis does play faster than A&M, but A&M is better at scoring once they get in a half court set.

If Chris Douglas-Roberts plays for Memphis, it will be a close, entertaining game, with the edge going in the end to the more experienced, more battle-tested Aggies. They do have Acie Law (and a maroon caravan from San Anton to College Station) on their side, and in a close game, there’s not a better player in America. If CDR can’t go, the Aggies should win by 6-8 points.

FIRST 2 GAMES ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Memphis 67.6 109.7 81.7 .9674
Texas A&M 61.9 123.0 88.5 .9778

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Texas A&M 69, Memphis 66
  • Last 10 Prediction … Texas A&M 68, Memphis 65
  • Vs. Good Prediction … Texas A&M 67, Memphis 66
  • Trendline Prediction … Memphis 67, Texas A&M 67
  • Best 6 Prediction … Texas A&M 69, Memphis 65

UPDATED GRAPHS

Memphis team capsule

Texas A&M team capsule

1st ROUND GAME ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Memphis 66.7 103.2 84.7 0.9071
Nevada 67.1 118.2 88 0.9675

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Memphis 78, Nevada 69
  • Last 10 Prediction … Memphis 74, Nevada 69
  • Vs. Good Prediction … Memphis 77, Nevada 68
  • Trendline Prediction … Memphis 72, Nevada 71
  • Best 6 Prediction … Memphis 84, Nevada 68

UPDATED GRAPHS

Memphis team capsule

Nevada team capsule

1st ROUND GAME ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Virginia 59 143.1 97.3 0.9883
Tennessee 69.6 152.2 104.5 0.9869

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Tennessee 81, Virginia 79
  • Last 10 Prediction … Tennessee 76, Virginia 71
  • Vs. Good Prediction … Tennessee 79, Virginia 76
  • Trendline Prediction … Tennessee 75, Virginia 69
  • Best 6 Prediction … Virginia 77, Tennessee 77

UPDATED GRAPHS

Virginia team capsule

Tennessee team capsule

Against Stanford, Louisville showed that their relatively poor offensive showing in the previous game (in the Big East tournament against Georgetown) was just a momentary blip in an otherwise excellent stretch. Their defense turned in another solid performance, and the game was never close. If they play as well against Texas A&M, they’ve got a good chance of advancing to the Sweet 16.

Texas A&M was down midway through the 2nd half in their game against Penn before pulling away late. Most of the blame for the game being close can be placed on their offense, which had been their strength lately. They need to bounce back against Louisville, especially with the game being played in Kentucky.

They way the tams have been playing lately, combined with the home-state crowd, gives the edge to Louisville.

1st ROUND GAME ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Texas A&M 60.1 102.3 86.5 0.8733
Louisville 67.9 125.2 81.1 0.9933

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Texas A&M 66, Louisville 61
  • Last 10 Prediction … Louisville 69, Texas A&M 67
  • Vs. Good Prediction … Texas A&M 66, Louisville 62
  • Trendline Prediction … Louisville 76, Texas A&M 67
  • Best 6 Prediction … Texas A&M 66, Louisville 62

UPDATED GRAPHS

Texas A&M team capsule

Louisville team capsule

1st ROUND GAME ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Ohio St. 65.1 119.1 92.2 0.9501
Xavier 66.2 123.5 97.8 0.9359

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Ohio St. 74, Xavier 66
  • Last 10 Prediction … Ohio St. 67, Xavier 63
  • Vs. Good Prediction … Ohio St. 75, Xavier 66
  • Trendline Prediction … Ohio St. 64, Xavier 58
  • Best 6 Prediction … Ohio St. 73, Xavier 67

UPDATED GRAPHS

Ohio St. team capsule

Xavier team capsule

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Memphis 86, North Texas 62
  • Last 10 Prediction … Memphis 82, North Texas 57
  • Vs. Good Prediction … Memphis 82, North Texas 65
  • Trendline Prediction … Memphis 79, North Texas 63
  • Best 6 Prediction … Memphis 82, North Texas 58

explanation

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 69.4 11 116.2 23 86.1 8 .9690 9
Vs. Good 67.7 21 118.3 19 87.4 9 .9701 8
Trendline 66.8 23 116.2 26 91.0 20 .9434 21
Last 10 66.7 19 117.4 26 87.8 9 .9657 12
Best 6 66.2 33 127.1 10 84.3 18 .9912 9

As winners of 22 straight games heading into the tournament, it might seem like Memphis is, by definition, one of the hottest teams in the dance. If you go by wins alone, sure. But a closer look at their performance reveals a team that has, at times, been doing just enough to win against mediocre teams. Only two of their last 6 adjusted game ratings have been NCAA-quality (over .95), and in only one of their last four has their offense and defense both been better than average. On the other hand, they are still rated 8th-best over the last 10 games, and 12 of their past 13 games they’ve posted an adjusted offensive efficiency over 110. Memphis fans should hope the trendlines are just aberrations created by a couple outlying results, and not actually a sign of things to come.

Points, assists, turnovers, blocks, and steals listed per 100 individual possessions

PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Anderson 67.3 44.5 64.6 0.97 16.0 7.5 2.7 0.5 3.6 4.6 11.1
Dozier 62.5 50.0 62.7 1.08 22.1 2.4 4.2 3.2 2.1 10.8 15.3
Dorsey 62.2 62.7 47.5 1.21 19.8 0.7 3.9 5.3 3.6 18.8 22.6
Douglas-Roberts 62.0 57.3 72.4 1.23 32.8 3.9 4.1 0.8 2.6 4.4 9.2
Hunt 58.6 54.2 68.8 1.15 32.7 3.4 3.3 0.9 3.4 2.8 10.3
Kemp 55.6 50.0 41.0 0.99 16.7 6.1 3.5 0.2 1.9 2.6 9.3
Allen 47.8 39.2 49.3 0.84 14.6 8.8 4.8 0.1 3.8 2.9 7.7
Mack 34.9 57.6 69.0 1.19 28.5 3.4 2.8 1.1 2.1 6.5 10.3
Cooper 21.6 52.3 62.5 1.10 21.7 1.4 3.8 2.8 1.2 12.4 21.2

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 70.2 9 99.3 62 103.3 57 .3870 62
Vs. Good 73.8 3 101.0 56 94.4 37 .6859 53
Trendline 70.4 5 100.0 63 98.3 43 .5484 61
Last 10 69.5 6 96.1 64 102.7 55 .3176 63
Best 6 68.1 19 104.2 58 97.0 55 .6948 60

North Texas is actually a below average team over the last 10 games, and for the year as a whole, but they’re not as bad as the graph makes them look. The really terrible stretch about a third of the way into the season coincided with the return of their 2nd-leading scorer, Kendrick Davis. The defense was fine while he was out, tanked when he returned, and took a few games to get back to where it was before. Davis may have come back a couple games to early and not been at full speed yet, or may have disrupted team chemistry, but whatever the problem was, they solved it and now are playing at an average level.

Points, assists, turnovers, blocks, and steals listed per 100 individual possessions

NORTH TEXAS PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Bell 75.5 46.5 59.7 0.99 13.4 5.6 4.0 0.2 2.2 2.8 8.9
Watson 74.6 53.7 63.7 1.11 28.8 2.4 3.9 0.6 1.5 3.6 10.4
Williams 63.5 57.9 54.7 1.18 22.8 3.5 4.3 2.3 1.5 12.1 18.4
Young 60.6 56.1 75.0 1.20 13.1 3.9 3.0 2.3 2.3 6.4 12.1
Wooden 57.6 51.7 66.3 1.12 22.1 2.9 5.3 2.3 0.8 8.9 18.1
Davis 50.8 49.6 80.4 1.06 25.9 3.0 3.9 0.3 1.8 3.2 6.5
Sturns 45.0 50.2 69.8 1.10 38.2 5.3 6.8 0.2 2.8 7.8 14.6
Stewart 43.5 45.3 61.1 1.00 12.8 1.8 3.9 2.0 1.0 8.9 14.9

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Creighton 70, Nevada 67
  • Last 10 Prediction … Creighton 72, Nevada 67
  • Vs. Good Prediction … Creighton 69, Nevada 68
  • Trendline Prediction … Creighton 74, Nevada 65
  • Best 6 Prediction … Creighton 70, Nevada 66

explanation

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 67.2 32 116.8 20 99.7 54 .8610 42
Vs. Good 66.0 35 119.1 14 99.3 57 .8908 39
Trendline 69.5 9 116.2 27 97.1 38 .8867 34
Last 10 65.9 30 119.7 18 102.1 54 .8625 42
Best 6 70.1 8 117.9 31 96.9 54 .9056 48

Senior point guard Kyle Shiloh, Nevada’s best on-the-ball defender, is expected back for their first round game, after missing the WAC championship game with a hamstring injury. This is great news for the Wolfpack, as the game he missed was their worst outing in the last 7 games. Nevada’s tempo is trending upwards, which could be a good sign for them, as their best 6-game stretch was played at a faster pace than most of their other games.

Points, assists, turnovers, blocks, and steals listed per 100 individual possessions

PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Kemp 76.8 54.9 79.0 1.17 35.5 4.6 5.5 0.3 1.3 3.8 12.0
Sessions 74.7 47.7 83.5 1.12 24.7 9.3 5.0 0.4 1.8 4.9 13.3
Shiloh 71.0 56.4 69.6 1.18 20.0 6.7 3.5 0.3 2.5 4.9 8.1
Fazekas 70.0 60.7 84.0 1.30 40.3 3.4 3.7 2.8 1.5 12.6 29.0
Ikovlev 62.5 63.2 75.0 1.30 16.0 2.2 1.8 1.4 0.9 7.8 9.5
Burleson 37.0 43.1 70.0 0.91 7.4 8.3 3.4 0.3 3.2 1.1 5.5
Ellis 28.9 47.4 86.7 1.05 11.2 1.7 1.8 3.0 0.7 5.6 11.7
McGee 25.5 64.5 48.4 1.26 19.6 0.8 4.3 5.0 0.6 12.0 12.6
Fields 20.6 44.5 56.3 0.93 15.4 5.6 3.7 0.0 2.1 4.8 9.1
Hanson 18.0 58.8 0.0 1.15 12.6 3.7 1.9 1.6 1.3 2.3 9.4
LaGrone 13.0 50.0 20.0 0.89 7.4 0.7 5.2 0.0 0.4 13.3 21.6

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 63.7 53 114.1 32 91.5 26 .9270 29
Vs. Good 62.6 58 114.6 32 94.0 34 .9073 35
Trendline 64.8 39 115.3 32 85.0 9 .9710 9
Last 10 63.6 45 114.8 34 91.4 24 .9327 23
Best 6 60.9 59 116.0 38 88.6 39 .9567 44

Other than a slow start to the season, Creighton’s offense has been fairly consistent. Their defense has improved from its nonconference levels, but has hit a couple of speed bumps along the way. After the first bad stretch (4 games from Dec 22 to Jan 1), the defense got their act together and had 11 straight good games. That lasted until their second bad stretch began (5 games from Feb 7 to 20). Since then, they’ve had good defensive efforts in a row. Hopefully for the Bluejays, those continue in the NCAA tournament, because they’re 5-5 in subpar defensive games, 17-5 otherwise.

CREIGHTON PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Funk 85.5 54.5 86.7 1.21 33.2 5.7 4.1 0.2 2.3 2.9 9.9
Tolliver 79.0 51.7 65.9 1.13 27.4 4.0 4.2 3.6 1.5 9.4 17.2
Watts 70.0 55.4 72.2 1.18 23.2 2.0 3.0 0.6 1.5 8.6 19.6
Porter 69.0 47.4 80.6 1.18 24.8 5.8 5.3 0.1 2.5 8.1 17.0
Miles 54.5 49.4 76.7 1.07 17.7 5.0 3.3 0.1 2.9 3.9 8.5
Dotzler 38.2 28.8 86.7 0.86 7.4 6.9 6.3 0.3 2.9 1.1 4.5
Bahe 37.7 60.4 60.0 1.22 13.3 4.2 3.6 0.0 1.5 5.7 9.7
Hibma 29.7 48.1 75.0 0.99 9.0 2.0 2.6 0.5 1.7 5.8 9.1
Gakou 14.2 42.9 50.0 0.92 11.7 0.4 4.6 0.0 0.4 8.6 9.5

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Texas A&M 78, Penn 60
  • Last 10 Prediction … Texas A&M 78, Penn 59
  • Vs. Good Prediction … Texas A&M 84, Penn 62
  • Trendline Prediction … Texas A&M 74, Penn 62
  • Best 6 Prediction … Texas A&M 83, Penn 61

explanation

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 65.6 42 120.4 7 85.9 7 .9800 5
Vs. Good 63.8 53 121.8 10 87.3 8 .9785 6
Trendline 64.3 41 119.3 17 93.7 26 .9418 23
Last 10 64.4 42 124.1 5 89.5 14 .9773 6
Best 6 65.0 42 128.6 9 81.3 8 .9949 4

Texas A&M’s defense is one of the best in the country, and if they make a deep run in the tournament, it will be the defense that anchors the run, or so goes the conventional wisdom. But looking at the graph, their defense has been less dominant lately, and even threw up a couple bad games (although one was against Kevin Durant, so they get a mulligan). Meanwhile the offense has been great, thanks to a reduction in their turnover rate. Their loss to Oklahoma State in the Big 12 tournament is less worrisome than it first appears, considering that the game was in Oklahoma City (and that Oklahoma State gave Texas a run for its money the next day). Whether it’s their offense or defense leading the way, the Aggies are one of the top teams in the tourney by pretty much any measure.

Points, assists, turnovers, blocks, and steals listed per 100 individual possessions

PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Law 83.4 55.8 76.5 1.21 32.6 9.6 4.8 0.1 2.3 0.8 9.7
Kirk 74.2 54.1 68.2 1.13 13.4 6.0 2.6 0.5 1.7 1.0 11.1
Carter 73.2 67.1 77.9 1.39 26.1 5.3 2.1 1.1 1.5 3.7 11.8
Kavaliauskas 70.7 57.3 66.0 1.20 26.5 3.7 3.8 1.6 1.5 8.9 17.6
Jones 67.4 56.9 81.6 1.28 30.2 2.8 3.6 1.7 2.6 12.1 17.0
Sloan 43.5 55.6 68.4 1.17 18.5 6.4 4.2 0.2 2.6 3.2 9.5
Pompey 30.2 50.0 57.7 1.09 13.9 3.1 4.4 1.3 1.9 11.3 8.8
Davis 16.5 38.5 72.7 0.91 16.6 2.4 7.7 3.9 3.3 25.9 26.3

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 69.3 12 107.0 50 98.8 52 .7150 54
Vs. Good 69.6 11 108.3 49 105.4 64 .5768 57
Trendline 69.0 13 101.3 62 95.7 32 .6590 56
Last 10 68.7 10 101.8 62 96.5 39 .6509 56
Best 6 68.7 18 115.0 41 98.3 58 .8593 53

Penn is playing their best defense of the season, with 6 of their past 9 games under 95 in adjusted defensive efficiency. Their offense is on a slight decline, precipitated by a decline in offensive rebounding, but still above average in 4 of the last 5 games. Against above average teams, the offense performs fine, but the defense struggles. Their best hope of an upset will be if they face a team that sometimes struggles to score. That way the opponent can take themselves out of the game offensively, instead of Penn having to do it.

Points, assists, turnovers, blocks, and steals listed per 100 individual possessions

PENN PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Jaaber 91.7 57.0 66.7 1.19 25.6 8.4 4.7 0.9 4.8 5.8 8.8
Grandieri 78.2 54.7 71.2 1.15 22.2 4.7 3.5 0.5 2.0 6.0 14.3
Zoller 78.1 61.2 78.4 1.31 33.9 5.3 5.0 0.8 3.4 7.7 21.5
Danley 70.7 51.2 66.7 1.16 18.8 4.4 3.5 1.9 1.4 6.2 14.0
McMahon 44.8 47.7 47.7 0.97 16.6 4.0 4.9 0.1 1.6 2.6 9.1
Egee 33.0 57.5 41.7 1.13 18.0 2.9 2.3 0.5 1.7 3.6 7.1
Smith 29.7 51.2 66.7 1.07 16.4 4.1 5.0 0.2 1.5 1.4 4.1
Kach 28.1 52.9 67.9 1.13 16.7 4.3 3.4 0.2 1.8 3.8 11.3
Votel 22.7 43.8 50.0 0.89 13.5 4.7 2.9 1.1 1.1 10.4 9.0




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