Nerdly Nebraska.
2023-2024 HuskerGeek Ratings Leaders
Sport | School | Rating |
---|---|---|
ViPR D1 Volleyball | Wisconsin | 1,711.3731 |
Sport | School | Rating |
---|---|---|
ViPR D1 Volleyball | Wisconsin | 1,711.3731 |
Rnk. | Team | Résumé | Recent | ViPR | Adj SP% | Adj SO% | Adj. Hit Mar. |
---|---|---|---|---|---|---|---|
1st | Texas | 1,676.1472 | 1,680.6293 | 1,678.3868 | 56.82 | 68.59 | 0.328 |
2nd | Baylor | 1,630.7776 | 1,638.4801 | 1,634.6243 | 55.68 | 65.71 | 0.267 |
3rd | West Virginia | 1,549.8065 | 1,551.3088 | 1,550.5575 | 55.67 | 56.82 | 0.136 |
4th | Texas Tech | 1,546.6735 | 1,550.8312 | 1,548.7509 | 54.60 | 58.37 | 0.152 |
5th | Iowa St. | 1,535.3415 | 1,542.0922 | 1,538.7131 | 55.08 | 56.53 | 0.166 |
6th | Kansas | 1,534.0706 | 1,535.9226 | 1,534.9963 | 54.09 | 58.01 | 0.147 |
7th | Kansas St. | 1,510.4983 | 1,519.2195 | 1,514.8526 | 50.97 | 58.83 | 0.121 |
8th | TCU | 1,479.9669 | 1,487.1734 | 1,483.5658 | 51.03 | 55.23 | 0.081 |
9th | Oklahoma | 1,474.2887 | 1,480.7368 | 1,477.5092 | 51.39 | 54.26 | 0.080 |
ViPR Adjusted Offenses and Defenses are adjusted to expected values against an average team in the same division.
Rnk. | Team | Hit% | Kill% | HE% | AST% | O_DIG% | O_BLK% | ACE% |
---|---|---|---|---|---|---|---|---|
1st | Texas | 0.4188 | 49.87 | 7.99 | 45.94 | 38.37 | 2.26 | 10.60 |
2nd | Baylor | 0.3639 | 47.89 | 11.50 | 42.93 | 38.63 | 3.92 | 5.82 |
3rd | Texas Tech | 0.2876 | 40.47 | 11.71 | 36.22 | 46.29 | 4.31 | 6.02 |
4th | Iowa St. | 0.2844 | 41.06 | 12.61 | 37.30 | 44.51 | 4.59 | 7.21 |
5th | Kansas | 0.2837 | 40.50 | 12.13 | 36.86 | 46.59 | 4.22 | 6.45 |
6th | Kansas St. | 0.2702 | 40.72 | 13.70 | 37.81 | 45.88 | 3.79 | 7.21 |
7th | West Virginia | 0.2572 | 39.67 | 13.95 | 35.56 | 45.55 | 5.04 | 6.79 |
8th | TCU | 0.2435 | 40.45 | 16.10 | 37.26 | 42.60 | 6.57 | 6.60 |
9th | Oklahoma | 0.2422 | 38.32 | 14.10 | 34.55 | 46.28 | 5.31 | 5.78 |
Rnk. | Team | O_Hit% | O_Kill% | O_HE% | O_AST% | DIG% | BLK% | O_ACE% |
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1st | Texas | 0.0910 | 29.90 | 20.80 | 27.20 | 53.22 | 9.45 | 6.19 |
2nd | Baylor | 0.0965 | 29.22 | 19.58 | 26.90 | 52.72 | 8.87 | 4.36 |
3rd | Iowa St. | 0.1186 | 29.96 | 18.11 | 27.79 | 55.08 | 8.04 | 4.95 |
4th | West Virginia | 0.1209 | 29.24 | 17.16 | 26.51 | 55.69 | 7.35 | 3.84 |
5th | Texas Tech | 0.1356 | 31.75 | 18.18 | 28.61 | 52.63 | 7.54 | 5.11 |
6th | Kansas | 0.1365 | 31.29 | 17.64 | 28.97 | 52.83 | 8.65 | 5.67 |
7th | Kansas St. | 0.1489 | 31.80 | 16.91 | 30.55 | 52.81 | 7.62 | 4.79 |
8th | Oklahoma | 0.1618 | 33.22 | 17.04 | 30.27 | 51.20 | 8.19 | 5.49 |
9th | TCU | 0.1623 | 33.62 | 17.39 | 30.56 | 50.47 | 8.42 | 5.97 |
Description | Average | Remove First and Last | Remove Top and Bottom 2 | Remove Top and Bottom 3 | Composite |
---|---|---|---|---|---|
Scores | 1,551.3285 | 1,543.7229 | 1,537.5741 | 1,540.8201 | 1,543.3614 |
Difference | -7.6056 | -13.7544 | -10.5084 | -10.6228 |
Offense | Defense | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Team | Sets | S | SP | SA | SE | SP% | S/SA | S/SE | OS | SPA | SAA | SEA | SO% | OS/SAA | OS/SEA |
Texas | 99 | 2,276 | 1,126 | 218 | 304 | 49.47 | 10.4 | 7.5 | 1,824 | 670 | 126 | 229 | 63.27 | 14.5 | 8.0 |
Baylor | 103 | 2,290 | 1,096 | 110 | 211 | 47.86 | 20.8 | 10.9 | 2,042 | 819 | 111 | 235 | 59.89 | 18.4 | 8.7 |
West Virginia | 102 | 2,250 | 1,155 | 154 | 192 | 51.33 | 14.6 | 11.7 | 2,059 | 968 | 94 | 180 | 52.99 | 21.9 | 11.4 |
Texas Tech | 116 | 2,203 | 1,067 | 125 | 183 | 48.43 | 17.6 | 12.0 | 2,154 | 995 | 134 | 213 | 53.81 | 16.1 | 10.1 |
Kansas | 114 | 2,331 | 1,116 | 134 | 224 | 47.88 | 17.4 | 10.4 | 2,314 | 1,081 | 150 | 245 | 53.28 | 15.4 | 9.4 |
Iowa St. | 102 | 2,132 | 1,041 | 137 | 233 | 48.83 | 15.6 | 9.2 | 2,093 | 1,004 | 124 | 181 | 52.03 | 16.9 | 11.6 |
Kansas St. | 107 | 2,228 | 1,010 | 143 | 239 | 45.33 | 15.6 | 9.3 | 2,254 | 1,030 | 124 | 201 | 54.30 | 18.2 | 11.2 |
TCU | 98 | 1,793 | 816 | 109 | 214 | 45.51 | 16.4 | 8.4 | 1,904 | 941 | 132 | 207 | 50.58 | 14.4 | 9.2 |
Oklahoma | 107 | 2,175 | 1,000 | 106 | 219 | 45.98 | 20.5 | 9.9 | 2,332 | 1,166 | 147 | 234 | 50.00 | 15.9 | 10.0 |
Conference Average | 105 | 2,186 | 1,047 | 137 | 224 | 47.85 | 16.6 | 9.9 | 2,108 | 964 | 127 | 214 | 54.46 | 16.8 | 10.0 |
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Game Link | EPIC | Game Date | Location | Teams | Sets | Set 1 | Set 2 | Set 3 | Set 4 | Set 5 |
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GAME |
76.39 |
2021-10-01 |
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GAME |
75.67 |
2021-10-29 |
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GAME |
75.12 |
2021-10-09 |
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GAME |
75.07 |
2021-10-07 |
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GAME |
74.98 |
2021-11-19 |
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GAME |
74.97 |
2021-10-27 |
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GAME |
74.54 |
2021-10-23 |
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GAME |
74.41 |
2021-11-06 |
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GAME |
74.10 |
2021-10-14 |
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GAME |
73.88 |
2021-11-26 |
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Name | Team | Role |
---|---|---|
Brionne Butler | Texas | A |
Logan Eggleston | Texas | A |
Molly Phillips | Texas | A |
Yossiana Pressley | Baylor | A |
Avery Skinner | Baylor | A |
Nalani Iosia | Texas | D |
Hannah Lockin | Baylor | S |
Lacey Zerwas | West Virginia | S |
Name | Team | Role |
---|---|---|
Skylar Fields | Texas | A |
Candelaria Herrera | Iowa St. | A |
Eleanor Holthaus | Iowa St. | A |
Briana Lynch | West Virginia | A |
Kenna Sauer | Texas Tech | A |
Adrian Ell | West Virginia | D |
Natali Petrova | West Virginia | D |
Alex Kirby | Texas Tech | S |
Rank | Name | Team |
---|---|---|
1 | Logan Eggleston | Texas |
2 | Avery Skinner | Baylor |
3 | Hannah Lockin | Baylor |
4 | Yossiana Pressley | Baylor |
5 | Lacey Zerwas | West Virginia |
Rank | Name | Team |
---|---|---|
1 | Logan Eggleston | Texas |
2 | Avery Skinner | Baylor |
3 | Yossiana Pressley | Baylor |
4 | Skylar Fields | Texas |
5 | Kenna Sauer | Texas Tech |
Rank | Name | Team |
---|---|---|
1 | Hannah Lockin | Baylor |
2 | Lacey Zerwas | West Virginia |
3 | Alex Kirby | Texas Tech |
4 | Jaden Newsome | Iowa St. |
5 | Jhenna Gabriel | Texas |
Rank | Name | Team |
---|---|---|
1 | Nalani Iosia | Texas |
2 | Natali Petrova | West Virginia |
3 | KJ Adams | Texas Tech |
4 | Asjia O'Neal | Texas |
5 | Shanel Bramschreiber | Baylor |
Rk. | Name | Team | WPA |
---|---|---|---|
1 | Logan Eggleston | Texas | 24.0080 |
2 | Hannah Lockin | Baylor | 22.5879 |
3 | Alex Kirby | Texas Tech | 22.5458 |
4 | Avery Skinner | Baylor | 22.4773 |
5 | Lacey Zerwas | West Virginia | 21.3940 |
6 | Kenna Sauer | Texas Tech | 19.8080 |
7 | Yossiana Pressley | Baylor | 19.6655 |
8 | Teana Adams-Kaonohi | Kansas St. | 19.2906 |
9 | Jaden Newsome | Iowa St. | 18.8770 |
10 | Adrian Ell | West Virginia | 18.6652 |
Rk. | Name | Team | OWPA |
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1 | Alex Kirby | Texas Tech | 15.4484 |
2 | Hannah Lockin | Baylor | 15.4240 |
3 | Logan Eggleston | Texas | 14.7423 |
4 | Avery Skinner | Baylor | 12.9832 |
5 | Lacey Zerwas | West Virginia | 12.7054 |
6 | Jaden Newsome | Iowa St. | 12.2713 |
7 | Teana Adams-Kaonohi | Kansas St. | 12.1946 |
8 | Yossiana Pressley | Baylor | 12.1921 |
9 | Skylar Fields | Texas | 11.1556 |
10 | Peyton Dunn | Oklahoma | 11.1509 |
Rk. | Name | Team | DWPA |
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1 | Callie Kemohah | Oklahoma | 14.2036 |
2 | Mackenzie Morris | Kansas St. | 14.0339 |
3 | KJ Adams | Texas Tech | 13.7133 |
4 | Alexa Hasting | West Virginia | 12.0987 |
5 | Marija Popovic | Iowa St. | 11.4829 |
6 | Shanel Bramschreiber | Baylor | 10.5235 |
7 | Kenna Sauer | Texas Tech | 10.5209 |
8 | Adrian Ell | West Virginia | 10.2336 |
9 | Jenny Mosser | Kansas | 9.6164 |
10 | Avery Skinner | Baylor | 9.4942 |
Rk. | Name | Team | WPA/S |
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1 | Logan Eggleston | Texas | 0.2527 |
2 | Avery Skinner | Baylor | 0.2417 |
3 | Hannah Lockin | Baylor | 0.2378 |
4 | Alex Kirby | Texas Tech | 0.2324 |
5 | Lacey Zerwas | West Virginia | 0.2252 |
6 | Yossiana Pressley | Baylor | 0.2138 |
7 | Kenna Sauer | Texas Tech | 0.2063 |
8 | Jaden Newsome | Iowa St. | 0.2030 |
9 | Teana Adams-Kaonohi | Kansas St. | 0.1968 |
10 | Adrian Ell | West Virginia | 0.1965 |
Rk. | Name | Team | OWPA/S |
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1 | Hannah Lockin | Baylor | 0.1624 |
2 | Alex Kirby | Texas Tech | 0.1593 |
3 | Logan Eggleston | Texas | 0.1552 |
4 | Avery Skinner | Baylor | 0.1396 |
5 | Lacey Zerwas | West Virginia | 0.1337 |
6 | Yossiana Pressley | Baylor | 0.1325 |
7 | Jaden Newsome | Iowa St. | 0.1319 |
8 | Teana Adams-Kaonohi | Kansas St. | 0.1244 |
9 | Skylar Fields | Texas | 0.1174 |
10 | McKenzie Nichols | TCU | 0.1133 |
Rk. | Name | Team | DWPA/S |
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1 | Marija Popovic | Iowa St. | 0.1511 |
2 | Callie Kemohah | Oklahoma | 0.1435 |
3 | KJ Adams | Texas Tech | 0.1414 |
4 | Mackenzie Morris | Kansas St. | 0.1376 |
5 | Alexa Hasting | West Virginia | 0.1274 |
6 | Shanel Bramschreiber | Baylor | 0.1108 |
7 | Kenna Sauer | Texas Tech | 0.1096 |
8 | Adrian Ell | West Virginia | 0.1077 |
9 | Avery Skinner | Baylor | 0.1021 |
10 | Eleanor Holthaus | Iowa St. | 0.1009 |
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.