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2023-2024 HuskerGeek Ratings Leaders

Sport School Rating
ViPR D1 Volleyball Wisconsin 1,711.3731

UMAC - Conference Overview

Conference Division: Division 3
Rnk. Team Résumé Recent ViPR Adj SP% Adj SO% Adj. Hit Mar.
1st Northwestern-St. Paul 1,504.4887 1,474.7316 1,489.5358 57.86 71.97 0.286
2nd Minn.-Morris 1,452.2584 1,429.3367 1,440.7520 57.14 66.36 0.234
3rd St. Scholastica 1,270.8906 1,252.2627 1,261.5423 46.77 56.84 0.050
4th Wis.-Superior 1,268.4163 1,248.1548 1,258.2448 47.95 55.22 0.036
5th Martin Luther 1,239.5774 1,217.3557 1,228.4163 44.67 55.46 0.026
6th Bethany Lutheran 1,184.9456 1,190.4207 1,187.6800 45.50 51.64 -0.022
7th Northland 1,102.7516 1,082.8798 1,092.7705 41.25 45.29 -0.129
8th Crown (MN) 1,068.0894 1,061.5865 1,064.8330 38.25 45.18 -0.168
9th North Central (MN) 1,042.1768 1,052.7500 1,047.4500 37.44 44.63 -0.158

ViPR Adjusted Offenses and Defenses are adjusted to expected values against an average team in the same division.

ViPR Division Adjusted Offenses

Rnk. Team Hit% Kill% HE% AST% O_DIG% O_BLK% ACE%
1st Northwestern-St. Paul 0.3412 44.58 10.46 41.04 42.46 3.40 8.91
2nd Minn.-Morris 0.2821 40.71 12.50 37.56 43.79 3.74 9.32
3rd St. Scholastica 0.2156 34.29 12.73 32.34 51.93 4.83 8.56
4th Martin Luther 0.1810 33.64 15.54 31.40 48.13 4.62 6.02
5th Wis.-Superior 0.1676 31.16 14.40 29.84 57.66 3.59 7.98
6th Bethany Lutheran 0.1457 31.93 17.36 29.26 53.19 4.12 8.55
7th North Central (MN) 0.0764 23.96 16.32 22.27 64.71 4.06 7.13
8th Northland 0.0763 25.40 17.77 24.00 61.31 5.01 6.58
9th Crown (MN) 0.0574 24.97 19.23 23.25 61.53 3.95 6.26

ViPR Division Adjusted Defenses

Rnk. Team O_Hit% O_Kill% O_HE% O_AST% DIG% BLK% O_ACE%
1st Minn.-Morris 0.0484 23.49 18.65 21.73 63.28 5.78 6.21
2nd Northwestern-St. Paul 0.0556 23.35 17.79 21.76 62.73 5.93 3.38
3rd Wis.-Superior 0.1314 30.57 17.43 28.35 51.46 3.79 8.28
4th Martin Luther 0.1549 32.90 17.42 29.71 51.69 5.57 8.59
5th St. Scholastica 0.1654 33.17 16.63 30.58 52.71 4.71 7.14
6th Bethany Lutheran 0.1682 33.53 16.71 30.56 53.13 3.43 8.14
7th Northland 0.2058 35.21 14.63 31.71 55.61 3.15 11.10
8th Crown (MN) 0.2255 36.86 14.31 33.80 52.64 2.32 9.84
9th North Central (MN) 0.2346 39.14 15.68 35.73 47.47 3.27 12.58

Conference Strength

Description Average Remove First and Last Remove Top and Bottom 2 Remove Top and Bottom 3 Composite
Scores 1,230.1361 1,219.1770 1,205.7308 1,224.7803 1,219.9560
Difference -10.9591 -24.4053 -5.3557 -13.5734

Point Totals

Offense Defense
Team Sets S SP SA SE SP% S/SA S/SE OS SPA SAA SEA SO% OS/SAA OS/SEA
Northwestern-St. Paul 138 2,875 1,490 225 222 51.83 12.8 13.0 2,227 787 114 212 64.66 19.5 10.5
Minn.-Morris 123 2,686 1,409 223 233 52.46 12.0 11.5 2,137 827 147 183 61.30 14.5 11.7
Wis.-Superior 110 2,019 969 185 132 47.99 10.9 15.3 1,961 914 185 198 53.39 10.6 9.9
St. Scholastica 116 2,141 944 173 187 44.09 12.4 11.4 2,258 1,071 181 231 52.57 12.5 9.8
Martin Luther 113 1,812 797 121 194 43.99 15.0 9.3 1,949 926 211 201 52.49 9.2 9.7
Bethany Lutheran 96 1,974 904 169 246 45.80 11.7 8.0 2,132 1,068 169 194 49.91 12.6 11.0
Northland 87 1,370 586 101 142 42.77 13.6 9.6 1,725 959 227 204 44.41 7.6 8.5
North Central (MN) 81 1,381 523 98 160 37.87 14.1 8.6 1,930 1,108 239 201 42.59 8.1 9.6
Crown (MN) 82 1,380 513 85 128 37.17 16.2 10.8 1,954 1,123 189 171 42.53 10.3 11.4
Conference Average 105 1,960 904 153 183 44.89 13.2 10.8 2,030 976 185 199 51.54 11.7 10.2
  • Sets - Team Sets Played
  • S - Serves
  • SP - Service Points
  • SA - Service Aces
  • SE - Service Errors
  • SP% - Service Point Percentage
  • S/SA - Serves Per Service Ace
  • S/SE - Serves Per Service Error
  • OS - Opponent Serves
  • SPA - Service Points Allowed
  • SAA - Service Aces Allowed
  • SEA - Service Errors Against
  • SO% - Team Sideout Percentage
  • OS/SAA - Serves Per Ace Allowed
  • OS/SEA - Serves Per Error Against

The Best Games in the UMAC

Game Link EPIC Game Date Location Teams Sets Set 1 Set 2 Set 3 Set 4 Set 5
GAME

68.90

2017-11-04 St. Paul, Minn.
Northwestern-St. Paul
Minn.-Morris
3
0
26
24
25
20
25
23
GAME

68.33

2017-09-16
Minn.-Morris
Northwestern-St. Paul
1
3
19
25
25
21
24
26
21
25
GAME

66.89

2017-10-11 St. Paul, Minn.
Northwestern-St. Paul
Minn.-Morris
3
2
14
25
25
20
25
15
21
25
15
10
GAME

61.54

2017-10-02 Superior, Wis.
Wis.-Superior
St. Scholastica
3
1
25
20
25
23
21
25
25
18
GAME

61.41

2017-10-30 New Ulm, Minn.
Martin Luther
St. Scholastica
3
2
23
25
25
18
25
27
25
18
16
14
GAME

61.16

2017-09-30 New Ulm, Minn.
Martin Luther
St. Scholastica
2
3
28
30
25
23
22
25
25
19
10
15
GAME

60.84

2017-09-19 Superior, WI
Wis.-Superior
St. Scholastica
3
1
25
21
25
21
15
25
25
21
GAME

60.72

2017-10-17 St. Paul, Minn.
Northwestern-St. Paul
Wis.-Superior
3
0
25
13
25
23
25
13
GAME

60.50

2017-10-17 New Ulm, Minn.
Martin Luther
Minn.-Morris
1
3
24
26
7
25
25
23
14
25
GAME

60.40

2017-09-22 Mankato, Minn.
Bethany Lutheran
Northwestern-St. Paul
0
3
19
25
23
25
21
25

HuskerGeek UMAC All-Conference

1st Team

Name Team Role
A
A
A
A
A
D
S

2nd Team

Name Team Role
A
A
A
A
D
D
S

Player of the Year

Rank Name Team
1
2
3
4
5

Attacker of the Year

Rank Name Team
1
2
3
4
5

Setter of the Year

Rank Name Team
1
2
3
4
5

Defensive Player of the Year

Rank Name Team
1
2
3
4
5

WPA

Rk. Name Team WPA
1 35.1958
2 21.6090
3 20.2959
4 19.2121
5 16.8339
6 15.6537
7 15.5779
8 14.1853
9 13.9325
10 12.7009

Offensive WPA

Rk. Name Team OWPA
1 21.5983
2 14.7005
3 13.0668
4 11.3585
5 9.1282
6 8.6037
7 8.4694
8 8.3534
9 7.6736
10 7.5119

Defensive WPA

Rk. Name Team DWPA
1 18.4275
2 15.3981
3 13.5975
4 11.7234
5 11.0859
6 10.3846
7 9.4088
8 8.9374
9 8.9217
10 8.8223

WPA Per Set

Rk. Name Team WPA/S
1 0.3061
2 0.1935
3 0.1896
4 0.1858
5 0.1735
6 0.1689
7 0.1642
8 0.1449
9 0.1379
10 0.1292

Offensive WPA Per Set

Rk. Name Team OWPA/S
1 0.1878
2 0.1290
3 0.1156
4 0.1049
5 0.1023
6 0.0971
7 0.0896
8 0.0751
9 0.0750
10 0.0733

Defensive WPA Per Set

Rk. Name Team DWPA/S
1 0.1575
2 0.1426
3 0.1282
4 0.1261
5 0.1182
6 0.1155
7 0.1045
8 0.0959
9 0.0939
10 0.0937


Explanations

Conference Strength – The Conference Strength table has two parts.  The first row is a list of averages of the scores for a selection of teams in the conference ranging from all of them under the heading “Average” to an average of teams in the conference if we remove the top and bottom three teams.  This is designed to check if a conference is propped up by its elite teams of held down by its weakest teams.  The Composite score on the far right is an average of those scores.  It is a weighted score where the middle teams have a higher value than the edge teams.  The second row containing difference is simply a measure of how different removing the edge teams makes the conference from its initial average.  If the numbers are positive, then removing the edge teams increases the conferences rating.  If a value grows from the value before it, then the team removed at the bottom of the ratings was rated farther outside of the mean than the team removed at the top of the ratings.  It was weighing the average down so to speak.  The Composite difference at the far right is simply an average of the differences.

The Best Conference Games – A short list of the best games played between two members of the conference which is calculated using the EPIC score of each game.  EPIC score is essentially very simple amounting to adding the teams combined ViPR Rating and the total Win Probability Added scored by each team.

All-Conference Teams – All-conference teams are calculated using Win Probability Added per Set Played and the quality of the team that the player plays on. Team quality is included because better teams tend to have better players and more of them.  This often means that players on better teams have fewer opportunities than standouts on lesser teams.

Awards Lists – Each awards list uses the same formula that is used to calculate All-Conference Teams, and decides based on the focus of the list.  Player of the Year has no limitation on how the player score is added up. While Attacker of the Year must have a higher attack score than any other metric.  Similarly Setter and Defensive Player must acquire most of their score through those metrics.

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