Archive for the 'Boston College' Category

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 […]

Over the past 10 games, Boston College’s tempo has been lower than their season average, and it’s been trending downward. Against Georgetown, they’re going to want to reverse that trend, because the Hoyas’ offense is at its most efficient when they take their time. So their slightly faster pace against Texas Tech was a good sign. Their poor defense against the Red Raiders, however, was not.

Georgetown’s win over Belmont doesn’t tell us much, but it does continue their run of very solid performances. 12 of their past 13 games have garnered overall ratings higher than .95, which ought to be enough to beat Boston College most nights.

1st ROUND GAME ADJ. EFFICIENCY

  Tempo Offense Defense Overall
Georgetown 60.4 132.8 90.3 0.9883
Boston College 67.1 136.9 103.2 0.9626

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Georgetown 69, Boston College 61
  • Last 10 Prediction … Georgetown 66, Boston College 56
  • Vs. Good Prediction … Georgetown 68, Boston College 60
  • Trendline Prediction … Georgetown 67, Boston College 57
  • Best 6 Prediction … Georgetown 69, Boston College 62

UPDATED GRAPHS

Georgetown team capsule

Boston College team capsule

EFFICIENCY PREDICTIONS

  • Full Season Prediction … Boston College 72, Texas Tech 69
  • Last 10 Prediction … Boston College 69, Texas Tech 62
  • Vs. Good Prediction … Boston College 70, Texas Tech 66
  • Trendline Prediction … Boston College 64, Texas Tech 56
  • Best 6 Prediction … Boston College 66, Texas Tech 64

explanation

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 64.7 48 118.9 10 96.7 48 .9150 34
Vs. Good 64.3 47 118.6 16 96.1 45 .9182 32
Trendline 57.3 62 115.3 31 98.5 45 .8597 42
Last 10 60.5 60 121.7 9 98.4 47 .9197 29
Best 6 67.3 25 119.9 26 87.9 34 .9724 29

The big story for Boston College this year was Sean Williams getting kicked off the team for his shenanigans. As you might expect, losing a player who averaged 5 a ridiculous 5 blocks per game severely handicapped BC’s defense, and essentially eliminated any chance they had of being an elite team. Here are efficiency splits (offense/defense/overall) related to the absence of Williams (and Dudley):

  • missing Dudley … 109.3 / 111.9 / .4328
  • missing Williams … 119.6 / 99.8 / .8886
  • missing neither … 119.0 / 89.8 / .9621

Without Williams, the offense must shoulder the entire load. It looked at first as if they might be OK, but the offense has sputtered in the past few games, and the outlook isn’t rosy heading into the tourney.

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

BOSTON COLLEGE PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Rice 90.3 52.8 78.1 1.18 28.6 9.2 5.6 0.4 2.1 3.2 7.4
Dudley 86.4 62.1 74.7 1.34 30.0 4.8 4.2 0.6 2.1 10.3 15.1
Marshall 80.6 51.2 68.5 1.08 27.6 3.6 4.1 0.4 2.1 6.5 9.8
Spears 53.0 55.8 75.6 1.25 20.1 2.4 4.7 0.5 1.2 12.2 13.4
Oates 49.1 42.0 73.5 0.92 13.4 2.4 2.6 1.2 1.0 5.0 15.0
Haynes 42.8 50.9 56.0 1.04 13.9 6.0 4.4 0.5 1.6 2.2 5.8
Blair 35.8 48.9 60.4 1.10 9.9 0.8 2.3 7.6 0.5 5.8 13.7
Roche 19.2 43.4 55.6 0.91 9.6 3.0 2.5 0.0 1.5 6.6 12.0

ADJUSTED GAME EFFICIENCY DATA

  Tempo Rnk Offense Rnk Defense Rnk Overall Rnk
Overall 65.7 41 112.3 37 96.3 46 .8530 43
Vs. Good 64.7 42 112.5 38 96.8 50 .8497 45
Trendline 63.0 48 107.1 51 104.4 56 .5742 58
Last 10 63.5 47 112.0 43 101.1 52 .7661 50
Best 6 62.5 55 118.1 29 89.4 42 .9611 41

Texas Tech is one of the most confusing teams in the tournament. They can truly beat anyone or lose to anyone, as evidenced by one of the weirdest 8-game stretches in recent memory. They went 3-5 from January 20th to February 13th. The 5 losses: Missouri, Texas, Oklahoma, Nebraska, Oklahoma St. The 3 wins: Kansas, Texas A&M, Texas A&M. That inconsistency shows up in the graph. They’re not playing so hot entering the tournament, but in their case, that doesn’t seem to matter.

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

TEXAS TECH PLAYER STATS

Name %Min eFG% FT% PPWS Pts A TO BS S OR% DR%
Jackson 94.2 51.5 78.9 1.14 32.2 2.8 2.2 0.0 2.2 3.2 7.5
Zeno 88.0 51.0 78.8 1.18 28.1 5.5 4.6 0.5 2.2 4.1 14.4
Burgess 71.9 50.9 72.2 1.11 17.5 5.0 4.1 0.2 1.7 4.3 12.0
Dora 42.1 51.9 74.1 1.09 17.2 5.1 3.3 1.7 0.5 5.5 12.8
Plefka 39.5 50.7 73.3 1.12 21.0 2.3 1.8 1.4 1.0 7.0 15.0
Voskuil 33.8 55.9 88.0 1.22 15.7 3.6 1.7 0.0 2.4 4.1 8.5
D White 30.2 54.3 57.1 1.11 19.5 2.4 4.4 0.8 1.8 10.1 9.8
Prince 28.8 39.3 63.6 0.88 9.2 4.1 3.2 0.8 3.8 7.6 14.1
Suljagic 20.5 39.0 44.0 0.83 9.5 2.7 4.0 1.3 2.0 7.7 16.2




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