Archive for the 'UNLV' Category
These are rolling 10 game averages of the offensive (top, up is good) and defensive (bottom, down is good) efficiencies of all the teams left in the tournament, broken down by region. If that’s not interesting to you, you are really missing out on a number of worldly experiences.
Basically, if a team’s top line […]
Check out our game previews for the Sweet 16 … I know, we picked a lot of chalk. If we have to pick a #1 seed to lose, my gut says USC takes down UNC. (Which probably means UNC wins in a blowout.)
[BE SURE TO CLICK THROUGH TO THE ACTUAL PREVIEWS. THEY […]
I didn’t have either of these teams making it this far at this time last week.
Oregon is riding an atypically strong defensive run over the last six games with Miami, OH being the only team to score more than one point per possession. As impressive as the Ducks have been over the last two weeks, it should be remembered that, entering the regular season finale against Oregon State, Oregon had been outscored in Pac-10 play.
UNLV scored 108 points more than their MWC opponents, but almost half (50 points) of that positive scoring margin came in the three extra home games they got to play as part of the conference tournament. (The remaining 16 teams outscored conference opponents between 351 (Memphis—also with three extra home games) and 1 (Vanderbilt) point this year.)
Only the pace of play will keep this from being the highest-scoring Sweet 16 game. Both teams made it this far by outscoring their opponents. UNLV allowed 1.08 points per possession to Georgia Tech and 1.06 to the Brian Butch-less Wisconsin Badges. Oregon gave up 1.07 points per possession to the MAC’s fourth-place team in the first round and 0.99 points per possession to Winthrop despite the Eagles making just five free throws and missing 23 of their 31 three-point attempts.
Oregon has no depth (Joevan Catron is the only reserve expected to see extended action) but they have as good an offensive starting five as any team left in the tournament. Aaron Brooks, Tajuan Porter, Bryce Taylor, Malik Hairston, and Maarty Leunen each score at least 20 points per 100 possessions. And they score efficiently. Each of the five scores at least 1.17 points per weighted shot.
Barring foul trouble or in-game injury, Oregon’s lack of depth will only hurt them if Porter is unable to make shots. He doesn’t really do anything helpful other than score. He’s the only regular with an assist-to-turnover ratio below one and rebounds one-third as often as the next worst starter on the offensive glass, and one-half as often as the next worst starter on the defensive glass.
Oregon’s reliance on the three-point shot (42% of their field goal attempts on the year) may increase due to the presence of UNLV’s Joel Anthony (10.3 Blocks per 100 possessions) and Gaston Essengue (4 Blocks/100) in the paint. Increasing their reliance (even though it would only figure to amount to one or two extra three-point attempts over the course of the low-possession style Oregon favors) on the least consistent method of scoring may not hurt Oregon. The Ducks don’t usually get too many offensive rebounds, but UNLV has allowed four of their last ten opponents to get at least 40% of the possible offensive rebounds.
Because they’re a good offensive rebounding team and almost never turn the ball over, UNLV’s offense does not depend on making shots to the degree that Oregon’s offense does. Oregon is not especially adept at either forcing turnovers or (Maarty Leunen and Catron, excepted) controlling the defensive glass. If the Ducks allow (as they normally do their opponents) UNLV to make a higher-than-normal percentage of their shots and maintain their average rates of offensive rebounding and turnovers, the Oregon offense will be under tremendous pressure to keep up.
FIRST 2 GAMES ADJ. EFFICIENCY
| Tempo | Offense | Defense | Overall | |
| Oregon | 61.6 | 124.4 | 97.7 | .9415 |
| UNLV | 63.1 | 129.2 | 90.4 | .9838 |
EFFICIENCY PREDICTIONS
- Full Season Prediction … Oregon 71, UNLV 69
- Last 10 Prediction … Oregon 67, UNLV 65
- Vs. Good Prediction … Oregon 70, UNLV 67
- Trendline Prediction … Oregon 69, UNLV 65
- Best 6 Prediction … Oregon 66, UNLV 61
UPDATED GRAPHS


Hope these “Just Stats” posts aren’t too annoying, but Mondays are busy nights. Should have some commentary up tomorrow at the latest.
Tempo
Rnk
Offense
Rnk
Defense
Rnk
Overall
Rnk
Kansas
69.9
1
126.4
2
82.3
1
0.9928
1
N. Carolina
69.8
2
127.9
1
90.3
8
0.9822
2
Georgetown
60.1
15
121.1
8
85.9
3
0.9813
3
Florida
65.5
7
123.8
4
90.2
7
0.9745
4
Ohio St.
63.6
9
117.7
12
86.0
4
0.9736
5
Texas A&M
63.1
11
122.4
5
91.8
10
0.9650
6
Oregon
62.2
13
126.0
3
94.5
13
0.9646
7
UCLA
62.2
14
116.8
14
88.6
5
0.9602
8
Tennessee
69.6
3
121.4
6
92.1
11
0.9598
9
S. Illinois
62.5
12
110.9
16
85.8
2
0.9504
10
UNLV
64.1
8
117.3
13
91.0
9
0.9491
11
Memphis
66.9
4
114.4
15
89.0
6
0.9472
12
Pittsburgh
63.1
10
120.2
10
93.7
12
0.9457
13
Vanderbilt
66.4
5
119.3
11
95.8
14
0.9258
14
USC
66.0
6
121.1
9
97.4
15
0.9241
15
Butler
57.9
16
121.3
7
98.4
16
0.9171
16
Here’s a chart of the adjusted tempo and efficiencies of all the Sweet 16 teams for the first 2 games of the tournament. I was going to post it with each team’s rank in each category, but the ranks exaggerate some differences in performance and minimize others. So I broke the offenses and […]
12:10 PM: #4 Virginia vs. #5 Tennessee
40 MINUTE GAME OF HORSE. Both of these teams played great on offense and poor on defense in the first round. The reason the scores look so different is all about the tempo and opponent. Both teams are likely to improve their defensive performance a bit, […]
1st ROUND GAME ADJ. EFFICIENCY
| Tempo | Offense | Defense | Overall | |
| Wisconsin | 64.8 | 108.9 | 85.5 | 0.9415 |
| UNLV | 59.9 | 121.4 | 88.1 | 0.9756 |
EFFICIENCY PREDICTIONS
- Full Season Prediction … Wisconsin 68, UNLV 60
- Last 10 Prediction … Wisconsin 61, UNLV 57
- Vs. Good Prediction … Wisconsin 67, UNLV 59
- Trendline Prediction … Wisconsin 58, UNLV 57
- Best 6 Prediction … Wisconsin 64, UNLV 56
UPDATED GRAPHS


EFFICIENCY PREDICTIONS
- Full Season Prediction … Georgia Tech 73, UNLV 68
- Last 10 Prediction … Georgia Tech 70, UNLV 64
- Vs. Good Prediction … Georgia Tech 72, UNLV 68
- Trendline Prediction … Georgia Tech 72, UNLV 70
- Best 6 Prediction … Georgia Tech 63, UNLV 61
ADJUSTED GAME EFFICIENCY DATA

| Tempo | Rnk | Offense | Rnk | Defense | Rnk | Overall | Rnk | |
| Overall | 66.0 | 39 | 112.4 | 36 | 93.0 | 29 | .8980 | 38 |
| Vs. Good | 65.1 | 39 | 111.0 | 42 | 93.1 | 30 | .8826 | 42 |
| Trendline | 66.6 | 24 | 114.9 | 35 | 92.8 | 25 | .9208 | 28 |
| Last 10 | 65.1 | 37 | 114.2 | 37 | 93.4 | 29 | .9093 | 34 |
| Best 6 | 63.7 | 48 | 111.9 | 50 | 82.1 | 11 | .9723 | 30 |
UNLV’s had a couple of their best games defensively recently, and their offense is doing about as well as it has all year. They’re not very consistent on either end of the court, though, so how they’ll play in the tournament is a mystery to me. Their stat averages say they should be somewhere in the 7 to 10 range. 4 of their last 7 games have been NCAA-quality (over .95), so they’ve got a decent chance of moving to the next round.
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% |
| Adams | 77.2 | 46.0 | 74.8 | 1.03 | 27.3 | 4.5 | 3.8 | 0.3 | 2.9 | 3.2 | 10.6 |
| White | 64.0 | 50.8 | 66.1 | 1.07 | 31.4 | 2.6 | 3.5 | 0.9 | 2.8 | 10.7 | 15.5 |
| Kruger | 62.1 | 55.6 | 84.0 | 1.24 | 27.2 | 9.9 | 4.2 | 0.2 | 2.2 | 0.8 | 8.6 |
| Umeh | 51.4 | 51.6 | 73.9 | 1.09 | 20.1 | 3.8 | 3.0 | 0.3 | 1.4 | 2.8 | 11.7 |
| Essengue | 50.4 | 53.4 | 78.0 | 1.15 | 22.3 | 1.2 | 2.9 | 4.1 | 2.2 | 12.9 | 15.2 |
| Terry | 49.0 | 46.8 | 71.4 | 0.99 | 13.8 | 5.3 | 3.0 | 0.1 | 2.6 | 2.8 | 9.1 |
| Anthony | 44.6 | 60.3 | 60.0 | 1.23 | 17.7 | 1.3 | 2.9 | 10.4 | 1.5 | 11.0 | 15.4 |
| Lawrence | 37.1 | 29.3 | 46.7 | 0.67 | 5.8 | 9.1 | 3.6 | 0.0 | 4.1 | 5.7 | 9.4 |
| Darger | 27.8 | 56.9 | 82.4 | 1.21 | 28.7 | 1.9 | 2.3 | 0.6 | 1.9 | 6.5 | 12.2 |
| Bailey | 22.2 | 65.3 | 39.1 | 1.24 | 17.4 | 2.0 | 2.6 | 0.2 | 2.2 | 4.6 | 7.1 |
ADJUSTED GAME EFFICIENCY DATA

| Tempo | Rnk | Offense | Rnk | Defense | Rnk | Overall | Rnk | |
| Overall | 68.3 | 20 | 118.5 | 13 | 91.1 | 23 | .9540 | 14 |
| Vs. Good | 67.3 | 26 | 119.8 | 12 | 94.7 | 38 | .9370 | 24 |
| Trendline | 63.8 | 44 | 125.1 | 10 | 97.5 | 39 | .9463 | 20 |
| Last 10 | 64.6 | 41 | 121.1 | 13 | 91.2 | 23 | .9631 | 13 |
| Best 6 | 70.6 | 6 | 115.5 | 39 | 82.2 | 12 | .9805 | 22 |
The trendlines for Georgia Tech look exactly the same, but if you look closer at the individual points, a slightly different picture is painted (one that’s prettier to Tech fans). The offense is in the midst of its best run of the season, with adjusted efficiencies better than 115 in 10 of the past 11 games. The defense, meanwhile, is only trending up because of their last game, an inexplicable loss to Wake Forest. Notice that the last game they played so badly on defense was also against Wake. Those 2 games are by far their worst defensive efforts in the past 23 games, so perhaps Wake presents unique matchup problems for Tech. Take out those two aberrations, and the Yellow Jacket defense looks much better. According to the ratings, they’re 4 to 6 seed quality, yet they’re slotted in at #10. They are a prime candidate to pull off a couple of upsets and make the Sweet 16.
Points, assists, turnovers, blocks, and steals listed per 100 individual possessions
GEORGIA TECH PLAYER STATS
| Name | %Min | eFG% | FT% | PPWS | Pts | A | TO | BS | S | OR% | DR% |
| Crittenton | 77.8 | 50.6 | 78.3 | 1.13 | 26.5 | 10.4 | 7.0 | <0.1/td> | 3.7 | 3.4 | 10.9 |
| Young | 70.8 | 54.1 | 73.5 | 1.13 | 28.1 | 4.0 | 4.2 | 0.8 | 2.6 | 9.7 | 10.6 |
| Smith | 62.8 | 60.6 | 48.1 | 1.19 | 19.0 | 3.6 | 4.0 | 0.8 | 3.4 | 11.1 | 16.7 |
| Dickey | 56.3 | 59.8 | 74.7 | 1.28 | 20.6 | 2.6 | 5.8 | 2.5 | 1.6 | 8.9 | 19.9 |
| Morrow | 50.9 | 55.3 | 83.9 | 1.18 | 27.5 | 2.5 | 2.4 | 0.2 | 1.6 | 7.0 | 8.4 |
| West | 45.9 | 55.5 | 69.6 | 1.19 | 14.2 | 5.2 | 3.6 | 1.1 | 5.0 | 5.0 | 11.0 |
| Peacock | 44.3 | 52.8 | 60.0 | 1.10 | 16.2 | 1.9 | 3.0 | 0.8 | 1.9 | 7.2 | 11.2 |
| Faye | 28.7 | 45.1 | 47.1 | 0.92 | 18.7 | 3.8 | 5.7 | 2.2 | 3.2 | 10.4 | 16.3 |
| Bell | 19.0 | 42.1 | 62.5 | 0.89 | 8.9 | 3.1 | 3.6 | 1.0 | 3.4 | 2.5 | 7.2 |
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