Archive for the 'Southern Illinois' 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 […]

Neither of these teams have a real defensive weakness, but there’s one thing they clearly both do least well defensively: they send their opponents on the free throw line fairly often. Their respective free throw rates allowed (opponents’ FTA/opponents FGA) are inflated somewhat due to the number of turnovers they force: Kansas forces turnovers on 24% of opponents’ possessions, Southern Illinois does so on 25% of opponents’ possessions so there’s a practical limit to how many field goal attempts either team allows. Still, Kansas allows their opponents a little more than one free throw attempt for every three field goal attempts while Southern Illinois allows one free throw attempt for every two field goal attempts.

Similarly, neither team’s offense appears likely to take advantage of frequent trips to the free throw line. Kansas shoots 66.6% on free throws, Southern Illinois shoots 69.1%. If Matt Shaw is unable to play, Southern Illinois’s free throw shooting is unlikely to match their season average. Shaw has made 81.7% of his free throws while taking about 15% of Southern Illinois’s free throws on the year.

Even with Shaw, Southern Illinois is far more limited offensively than Kansas. Whereas the Jayhawks feature seven players who score between 19.8 and 30.8 points per 100 possessions, Southern Illinois relies on Jamaal Tatum (30.4 Pts/100), Randal Falker (27.7 Pts/100), Tony Young (23.3 Pts/100), and Shaw (24.6 Pts/100) for almost all their scoring. Bryan Mullins (13.9 Pts/100) is the next most frequent scorer on the team. Tony Boyle provided a significant boost off the bench against Holy Cross (14 points in 21 minutes) but it was massively atypical (Boyle over the rest of the season: 67 points in 375 minutes).

In addition to their greater depth, Kansas does a much better job on the offensive glass (37.9 OR%) than Southern Illinois (31.7 OR%) and in taking care of the ball (19.8 TO% vs. 23% for Southern Illinois). The Jayhawks should put far more pressure on the Salukis’ defense than vice-versa. If Kansas can dictate the pace of play (they’d prefer 8-10 more possessions per game than Southern Illinois typically allows), each of their advantages will be magnified.

FIRST 2 GAMES ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Kansas 73.5 133.7 87.4 .9925
Southern Illinois 63.1 113.0 77.6 .9869

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Kansas 64, Southern Illinois 56
  • Last 10 Prediction … Kansas 69, Southern Illinois 59
  • Vs. Good Prediction … Kansas 65, Southern Illinois 58
  • Trendline Prediction … Kansas 68, Southern Illinois 60
  • Best 6 Prediction … Kansas 67, Southern Illinois 53

UPDATED GRAPHS

Kansas team capsule

Southern Illinois team capsule

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
Southern Illinois 67.2 103.9 80.5 0.9498
Virginia Tech 63.8 107.3 82.2 0.9557

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Virginia Tech 58, S. Illinois 57
  • Last 10 Prediction … S. Illinois 57, Virginia Tech 57
  • Vs. Good Prediction … Virginia Tech 59, S. Illinois 58
  • Trendline Prediction … S. Illinois 56, Virginia Tech 55
  • Best 6 Prediction … Virginia Tech 61, S. Illinois 60

UPDATED GRAPHS

Southern Illinois team capsule

Virginia Tech team capsule

Neither team expects any scoring off their benches. Holy Cross doesn’t really expect much scoring from anyone other than SR G Torey Thomas, SR G Keith Simmons, and JR C Tim Clifford.

The Crusaders compensate for their pedestrain field goal shooting (50.9 eFG% in the Patriot league) by making a good number of free throws. The only weakness Southern Illinois displays defensively is in allowing their opponents one free throw attempt for every two field goal attempts. In a game that expects to be played at or below 60 possessions and in which both teams enter forcing and committing turnovers on over 22% of their possessions in both at-risk and conference games, there just aren’t going to be many scoring opportunities of any kind. Holy Cross should get a massive proportion of their scoring chances at the free throw line.

If there’s a top four seed in the tournament that can beat by scoring a single point at a time against them, it’s Southern Illinois.

Prediction: Southern Illinois 59 Holy Cross 57

If you’re looking for excitement and you think excitement is run and gun for fun, this is not your game. If you like paced, measured basketball and have a copy of Hoosiers in a safe deposit box to preserve its vision for the future, you have found your special purpose in this game.

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Southern Illinois 58, Holy Cross 50
  • Last 10 Prediction … Southern Illinois 57, Holy Cross 50
  • Vs. Good Prediction … Southern Illinois 59, Holy Cross 50
  • Trendline Prediction … Southern Illinois 57, Holy Cross 52
  • Best 6 Prediction … Southern Illinois 52, Holy Cross 46

explanation

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 61.8 61 108.9 47 87.5 13 .9250 31
Vs. Good 61.2 61 110.3 46 88.5 11 .9267 27
Trendline 62.7 49 104.9 55 84.4 7 .9240 26
Last 10 62.3 52 107.9 53 84.3 4 .9450 20
Best 6 62.7 53 108.1 56 80.4 7 .9679 37

Southern Illinois very consistently won without dominating in the Missouri Valley Conference this season. Looking at the graph, the difference between their offensive and defensive efficiencies seems to be more consistent than the efficiencies themselves, perhaps a reflection of this non-domination. Their defense has consistently averaged 85 to 90, but with a lot of variation. It’s trending slightly better recently, but the offense it trending slightly worse to counteract that. They gutted out a solid win at Butler before falling to Creighton in the MVC tourney, and will likely play a solid game in the first round of the NCAA tourney.

SOUTHERN ILLINOIS PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Tatum 81.6 53.4 77.8 1.17 30.4 4.9 4.7 0.0 2.3 3.5 9.2
Shaw 78.1 55.0 81.0 1.21 24.3 2.4 4.1 1.1 2.0 7.9 16.9
Mullins 77.6 48.5 74.6 1.07 13.5 7.7 4.0 0.1 3.0 1.5 7.6
Falker 74.2 60.8 54.9 1.22 28.1 2.5 5.5 4.8 1.4 11.2 24.2
Young 66.9 48.2 84.8 1.06 23.2 5.3 5.5 0.5 3.1 2.4 8.9
Clemmons 40.2 44.5 67.4 1.03 12.3 2.0 4.6 0.1 1.3 5.6 18.7
Green 28.7 40.3 50.0 0.88 7.2 1.1 3.4 0.2 1.3 7.8 8.5
Boyle 27.7 43.3 62.5 0.95 12.4 0.7 4.3 1.9 1.9 6.5 11.2
Bone 13.8 42.2 100 0.87 14.9 2.6 0.4 0.0 1.9 6.5 10.4

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 63.3 55 100.9 60 93.0 29 .7180 53
Vs. Good 64.0 49 98.0 59 93.2 31 .6405 55
Trendline 65.4 33 102.8 58 90.7 18 .8096 47
Last 10 63.3 48 102.1 61 90.5 16 .8003 47
Best 6 62.7 54 98.3 64 83.5 15 .8670 52

Holy Cross has shown slight improvement over the course of the season, and has a decent defense as of late, but the “Vs. Good” line in the above chart is troubling. In 10 games against above-average teams, they’ve played like the 130th-best team in the country, and their best performance would have only been good enough to beat the 60th-best team.

HOLY CROSS PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Thomas 92.5 45.6 76.4 1.08 27.2 9.5 7.7 0.0 5.6 2.8 17.4
Simmons 87.5 57.2 77.0 1.25 36.5 4.0 3.9 1.5 4.8 10.1 15.4
Clifford 71.4 50.3 83.0 1.10 30.3 3.2 6.9 5.0 2.1 11.7 13.9
Vander Baan 71 49.7 69.4 1.09 16.7 4.3 4.9 0.8 1.6 12.5 15.5
Doherty 48.7 46.7 73.9 0.99 16.4 6.6 4.4 0.1 4.0 2.2 9.2
Meister 37.3 53.0 40.7 1.04 14.8 2.2 3.4 2.2 3.3 10.9 24.7
Cruze 32.9 40.3 100 0.85 11.5 5.6 3.7 0.2 3.9 2.1 14.7
Cunningham 23.7 38.8 53.6 0.85 14.1 4.0 7.1 0.0 1.9 5.4 13.9
McCarthy 18.5 48.4 68.2 1.05 22.6 2.4 5.4 2.7 1.2 16.0 11.5




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