Archive for the 'Pittsburgh' 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 […]
This game is as close to a toss-up as you can get. Two teams of roughly equal ability, whose coaches are familiar with each other, who both hope to play at a slow pace, and have only the slightest differences in how they win games. Factor in that both team’s most significant worry offensively is converting free throw chances and I figure that any single play could be plucked from the game action Thursday night and used to explain one team’s narrow victory or loss.
The thing that made UCLA slightly better than Pittsburgh over the course of the year was the Bruins ability to force turnovers. UCLA forced turnovers on 24% of opponents’ possessions in all games and 22% of their Pac-10 opponents’ possessions. Pittsburgh forced turnovers on just 19.2% of their opponents’ possessions in all games. Though they did bump that up to 20.3% in Big East play, in their first two NCAA tournament games, the Panthers forced just 15 turnovers over 169 defensive possessions.
Due to the lack of turnovers, both Wright State and VCU attempted 14 more field goals than Pittsburgh while the Panthers attempted just 12 more free throws than their opponents over the course of the two games. As it’s unlikely that Pittsburgh will be able to shoot 60 eFG% against UCLA (though both Cal and BYU managed to do so in Pauley Pavilion this year), should Pittsburgh again allow far more field goal attempts than they manage themselves they will need to excel in all other facets of play to remain competitive.
Though UCLA has struggled to make shots over their last five games (all played away from home), Luc Richard Mbah a Moute, Lorenzo Mata, and Alfred Aboya each get at least 10% of the available offensive rebounds when they’re on the floor. Pittsburgh relies on Aaron Gray (25.5 DR%) to do the bulk of their defensive rebounding. The Panthers could be at a decided disadvantage on the defensive glass when Gray is on the bench.
With the exception of their two games against Georgetown, Pittsburgh has been outstanding offensively over their last 10 games. With the exception of their two games against Cal, UCLA has been equally outstanding defensively. Over the course of the season, UCLA demonstrated a greater sustained ability to play good offense than Pittsburgh demonstrated they could play good defense. Taken together (and, if you wish to do so, giving UCLA some benefit for playing in their home state), I’d expect that to mean that UCLA wins this game 6 out of 10 times, though the pace of play may minimize the slight advantages UCLA possesses.
FIRST 2 GAMES ADJ. EFFICIENCY
| Tempo | Offense | Defense | Overall | |
| UCLA | 60.4 | 107.4 | 71.1 | .9914 |
| Pittsburgh | 67.2 | 121.7 | 90.5 | .9679 |
EFFICIENCY PREDICTIONS
- Full Season Prediction … UCLA 63, Pittsburgh 60
- Last 10 Prediction … UCLA 63, Pittsburgh 61
- Vs. Good Prediction … UCLA 64, Pittsburgh 62
- Trendline Prediction … UCLA 61, Pittsburgh 58
- Best 6 Prediction … UCLA 62, Pittsburgh 62
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 […]
1:10 PM: #1 Ohio St. vs. #9 Xavier
Both teams played well, but not spectacular, in their first round games. Xavier’s only player over 6′9″ averages less than 2 minutes per game, so Greg Oden should be able to control the game. All the numbers say this should be a fairly low scoring, close […]
1st ROUND GAME ADJ. EFFICIENCY
| Tempo | Offense | Defense | Overall | |
| Pittsburgh | 74.5 | 121.1 | 79.4 | 0.9923 |
| VCU | 71.2 | 135.7 | 96.9 | 0.9795 |
EFFICIENCY PREDICTIONS
- Full Season Prediction … Pittsburgh 72, VCU 64
- Last 10 Prediction … Pittsburgh 73, VCU 64
- Vs. Good Prediction … Pittsburgh 72, VCU 63
- Trendline Prediction … Pittsburgh 76, VCU 67
- Best 6 Prediction … Pittsburgh 66, VCU 61
UPDATED GRAPHS


When I fill out a bracket for an NCAA tournament pool (entered for pride only, no $$ exchanged of course), I’m obviously hoping in vain to get every game right. Not gonna happen. I have two other main goals (besides winning the pool): picking the Final Four correctly, and calling the first round […]
EFFICIENCY PREDICTIONS
- Full Season Prediction … Pittsburgh 67, Wright St. 54
- Last 10 Prediction … Pittsburgh 62, Wright St. 60
- Vs. Good Prediction … Pittsburgh 66, Wright St. 57
- Trendline Prediction … Pittsburgh 61, Wright St. 61
- Best 6 Prediction … Pittsburgh 62, Wright St. 56
ADJUSTED GAME EFFICIENCY DATA

| Tempo | Rnk | Offense | Rnk | Defense | Rnk | Overall | Rnk | |
| Overall | 62.9 | 57 | 118.9 | 10 | 90.5 | 20 | .9590 | 12 |
| Vs. Good | 62.8 | 56 | 121.7 | 11 | 91.2 | 21 | .9651 | 12 |
| Trendline | 64.0 | 43 | 115.4 | 30 | 94.0 | 28 | .9129 | 29 |
| Last 10 | 62.6 | 51 | 116.4 | 28 | 94.5 | 33 | .9169 | 32 |
| Best 6 | 61.5 | 58 | 126.3 | 11 | 87.3 | 30 | .9858 | 14 |
Pittsburgh’s offense is trending slightly downward recently, partly due to the struggles of Aaron Gray. In 9 of the past 10 games he has either picked up 4 fouls or been held to 10 or fewer points. The one game where he avoid both those fates was their best offensive game in that stretch. If he can stay out of foul trouble and get involved in the offense, they should be able to score. He needs to avoid fouls for their defense to succeed as well - they haven’t had a dominating game in that 10-game stretch, either. If they play like the have recently, they’ll win a couple games, but they need step up their offensive effort if they have hopes of a Final Four trip.
PITTSBURGH PLAYER STATS
| Name | %Min | eFG% | FT% | PPWS | Pts | A | TO | BS | S | OR% | DR% |
| Fields | 72.3 | 50.8 | 78.8 | 1.11 | 20.3 | 9.8 | 3.8 | 0.1 | 2.3 | 2.1 | 12.4 |
| Graves | 69.5 | 51.6 | 66.7 | 1.09 | 21.4 | 5.6 | 3.3 | 0.7 | 1.7 | 2.2 | 6.7 |
| Gray | 67.8 | 56.3 | 54.8 | 1.15 | 31.8 | 3.6 | 3.6 | 3.8 | 1.0 | 15.2 | 25.7 |
| Kendall | 64.5 | 46.8 | 73.8 | 1.05 | 14.0 | 4.5 | 2.7 | 1.9 | 2.0 | 10.6 | 14.9 |
| Cook | 63.1 | 53.3 | 68.6 | 1.15 | 26.2 | 6.6 | 4.3 | 0.1 | 1.5 | 5.6 | 9.6 |
| Ramon | 58.5 | 62.2 | 85.9 | 1.34 | 23.0 | 6.1 | 4.1 | 0.2 | 1.5 | 0.8 | 7.9 |
| Young | 41.5 | 49.5 | 60.7 | 1.03 | 25.5 | 2.8 | 4.3 | 1.6 | 2.0 | 12.9 | 11.5 |
| Biggs | 28.7 | 53.2 | 65.4 | 1.11 | 18.9 | 3.6 | 2.8 | 0.8 | 1.3 | 6.6 | 12.8 |
| Benjamin | 28.0 | 46.4 | 47.8 | 0.94 | 18.8 | 4.0 | 3.3 | 0.0 | 1.8 | 3.9 | 11.0 |
ADJUSTED GAME EFFICIENCY DATA

| Tempo | Rnk | Offense | Rnk | Defense | Rnk | Overall | Rnk | |
| Overall | 63.6 | 54 | 103.6 | 56 | 95.1 | 41 | .7270 | 52 |
| Vs. Good | 63.8 | 52 | 105.6 | 53 | 92.4 | 26 | .8238 | 47 |
| Trendline | 63.6 | 45 | 108.4 | 48 | 88.4 | 16 | .9124 | 30 |
| Last 10 | 63.8 | 44 | 108.5 | 50 | 91.0 | 21 | .8833 | 41 |
| Best 6 | 65.2 | 39 | 109.6 | 52 | 83.2 | 13 | .9599 | 42 |
Wright State has shown the most dramatic improvement over the course of the year of any team in the entire tournament, possibly explained by the team gradually learning exactly what’s expected of them by first-year coach Brad Brownell. Over their first ten games they were an 85/101 (Off/Def) team, which would place them around 230th in the nation over a full season. Over the last ten games, they’re a 108/91 team, good for around 55th. They lost to Butler by 29 points in early January, then beat them twice in their last 6 games. That Butler loss was their worst performance of the season, and also seems to be a turning point. Since then they’ve won 14 of 16, and their performance against above-average teams is a very good 113/86 (which would be the 14th best among tourney teams). Their Horizon league titles (regular season and conference tournament) were no fluke.
WRIGHT ST PLAYER STATS
| Name | %Min | eFG% | FT% | PPWS | Pts | A | TO | BS | S | OR% | DR% |
| Wood | 89.5 | 49.4 | 88.6 | 1.11 | 35.6 | 6.9 | 4.5 | 0.3 | 3.4 | 3.7 | 13.6 |
| Duggins | 80.6 | 44.7 | 73.4 | 0.97 | 17.7 | 5.1 | 3.9 | 0.1 | 1.7 | 2.2 | 10.4 |
| Burleson | 74.2 | 55.6 | 76.5 | 1.19 | 18.9 | 1.8 | 3.0 | 0.4 | 1.8 | 10.1 | 13.9 |
| Pleiman | 60.6 | 57.1 | 57.5 | 1.17 | 19.5 | 0.8 | 4.1 | 0.8 | 1.0 | 11.6 | 16.4 |
| Brown | 57.7 | 48.1 | 74.1 | 1.03 | 23.9 | 3.2 | 2.8 | 0.5 | 1.2 | 3.2 | 12.3 |
| Graham | 54.1 | 46.3 | 68.6 | 1.06 | 10.2 | 6.3 | 4.2 | 0.2 | 2.3 | 1.4 | 9.9 |
| Wilson | 36.6 | 58.3 | 58.8 | 1.19 | 19.2 | 0.8 | 5.3 | 1.5 | 1.1 | 9.9 | 16.5 |
| Smith | 28.0 | 40.4 | 53.3 | 0.85 | 9.0 | 4.1 | 3.2 | 0.7 | 1.8 | 1.4 | 10.3 |
| Scott | 14.8 | 35.9 | 66.7 | 0.77 | 17.6 | 3.7 | 5.1 | 0.3 | 1.0 | 9.2 | 7.7 |
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Florida - Butler Preview
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