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 | Nebraska | 1,848.4761 | 1,768.1937 | 1,807.8893 | 57.13 | 77.92 | 0.339 |
2nd | Minnesota | 1,823.4266 | 1,746.7690 | 1,784.6863 | 56.77 | 74.15 | 0.295 |
3rd | Wisconsin | 1,804.3720 | 1,726.8991 | 1,765.2106 | 53.67 | 75.62 | 0.286 |
4th | Penn St. | 1,789.9002 | 1,719.1044 | 1,754.1452 | 54.65 | 73.99 | 0.290 |
5th | Michigan | 1,742.1434 | 1,667.2729 | 1,704.2971 | 52.80 | 69.60 | 0.225 |
6th | Michigan St. | 1,736.8863 | 1,669.8409 | 1,703.0337 | 53.39 | 68.19 | 0.213 |
7th | Ohio St. | 1,733.2466 | 1,664.4965 | 1,698.5238 | 52.43 | 69.43 | 0.220 |
8th | Illinois | 1,728.3976 | 1,665.1363 | 1,696.4721 | 51.82 | 69.23 | 0.231 |
9th | Purdue | 1,730.0669 | 1,649.4175 | 1,689.2610 | 49.89 | 71.06 | 0.218 |
10th | Iowa | 1,683.0855 | 1,604.6409 | 1,643.3952 | 48.87 | 67.75 | 0.173 |
11th | Maryland | 1,650.6171 | 1,575.9810 | 1,612.8674 | 47.51 | 65.50 | 0.113 |
12th | Indiana | 1,647.9009 | 1,577.5133 | 1,612.3231 | 46.00 | 65.16 | 0.115 |
13th | Northwestern | 1,615.1805 | 1,555.4833 | 1,585.0509 | 46.12 | 62.78 | 0.122 |
14th | Rutgers | 1,498.1001 | 1,431.6533 | 1,464.4999 | 39.78 | 55.22 | -0.036 |
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 | Minnesota | 0.3816 | 47.39 | 9.23 | 44.03 | 41.08 | 3.26 | 5.98 |
2nd | Nebraska | 0.3718 | 47.60 | 10.42 | 43.52 | 41.02 | 3.61 | 6.42 |
3rd | Penn St. | 0.3714 | 47.08 | 9.94 | 43.63 | 41.65 | 3.86 | 6.28 |
4th | Wisconsin | 0.3555 | 46.41 | 10.86 | 43.46 | 41.09 | 4.77 | 6.43 |
5th | Purdue | 0.3429 | 48.04 | 13.75 | 44.71 | 38.48 | 3.96 | 5.77 |
6th | Michigan | 0.3357 | 45.01 | 11.44 | 41.47 | 40.43 | 5.33 | 6.08 |
7th | Illinois | 0.3303 | 44.99 | 11.97 | 42.16 | 42.05 | 4.09 | 5.66 |
8th | Ohio St. | 0.3290 | 47.11 | 14.21 | 43.79 | 39.12 | 4.72 | 6.71 |
9th | Iowa | 0.3145 | 45.40 | 13.95 | 42.53 | 40.73 | 6.51 | 6.15 |
10th | Michigan St. | 0.3098 | 44.97 | 13.99 | 41.15 | 42.24 | 4.66 | 9.07 |
11th | Indiana | 0.2924 | 46.05 | 16.81 | 41.78 | 36.54 | 6.21 | 7.64 |
12th | Northwestern | 0.2747 | 40.51 | 13.03 | 37.66 | 47.40 | 4.94 | 6.34 |
13th | Maryland | 0.2473 | 39.32 | 14.59 | 36.27 | 47.60 | 5.60 | 6.82 |
14th | Rutgers | 0.1961 | 36.78 | 17.17 | 33.78 | 49.04 | 6.12 | 5.60 |
Rnk. | Team | O_Hit% | O_Kill% | O_HE% | O_AST% | DIG% | BLK% | O_ACE% |
---|---|---|---|---|---|---|---|---|
1st | Nebraska | 0.0327 | 23.80 | 20.53 | 22.99 | 59.25 | 9.34 | 2.37 |
2nd | Wisconsin | 0.0695 | 25.47 | 18.52 | 24.29 | 58.66 | 8.19 | 2.30 |
3rd | Penn St. | 0.0817 | 28.61 | 20.43 | 27.60 | 54.70 | 8.82 | 3.72 |
4th | Minnesota | 0.0861 | 27.78 | 19.17 | 26.98 | 54.56 | 8.32 | 3.55 |
5th | Michigan St. | 0.0966 | 28.82 | 19.16 | 27.33 | 54.24 | 8.76 | 4.64 |
6th | Illinois | 0.0998 | 29.94 | 19.96 | 28.67 | 51.88 | 9.14 | 5.32 |
7th | Ohio St. | 0.1092 | 28.97 | 18.06 | 27.69 | 57.18 | 7.14 | 4.42 |
8th | Michigan | 0.1111 | 30.02 | 18.91 | 28.57 | 54.55 | 8.15 | 3.21 |
9th | Purdue | 0.1253 | 31.04 | 18.50 | 28.92 | 52.57 | 7.55 | 4.34 |
10th | Maryland | 0.1340 | 31.51 | 18.11 | 30.14 | 52.86 | 8.12 | 4.45 |
11th | Iowa | 0.1412 | 31.94 | 17.82 | 29.38 | 52.60 | 6.04 | 4.16 |
12th | Northwestern | 0.1527 | 32.92 | 17.65 | 30.69 | 51.88 | 6.69 | 6.02 |
13th | Indiana | 0.1772 | 35.70 | 17.98 | 32.70 | 48.76 | 7.39 | 4.88 |
14th | Rutgers | 0.2325 | 40.51 | 17.26 | 37.26 | 41.77 | 7.92 | 8.34 |
Description | Average | Remove First and Last | Remove Top and Bottom 2 | Remove Top and Bottom 3 | Composite |
---|---|---|---|---|---|
Scores | 1,680.1182 | 1,687.4389 | 1,687.9529 | 1,687.7494 | 1,685.8149 |
Difference | 7.3206 | 7.8347 | 7.6312 | 7.5955 |
Offense | Defense | ||||||||||||||
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Team | Sets | S | SP | SA | SE | SP% | S/SA | S/SE | OS | SPA | SAA | SEA | SO% | OS/SAA | OS/SEA |
Nebraska | 117 | 2,787 | 1,311 | 142 | 215 | 47.04 | 19.6 | 13.0 | 2,196 | 688 | 69 | 236 | 68.67 | 31.8 | 9.3 |
Penn St. | 121 | 2,770 | 1,295 | 147 | 242 | 46.75 | 18.8 | 11.4 | 2,273 | 782 | 98 | 238 | 65.60 | 23.2 | 9.6 |
Minnesota | 126 | 2,919 | 1,360 | 135 | 106 | 46.59 | 21.6 | 27.5 | 2,455 | 865 | 105 | 212 | 64.77 | 23.4 | 11.6 |
Wisconsin | 122 | 2,738 | 1,197 | 143 | 242 | 43.72 | 19.1 | 11.3 | 2,378 | 802 | 69 | 208 | 66.27 | 34.5 | 11.4 |
Michigan St. | 117 | 2,616 | 1,205 | 223 | 286 | 46.06 | 11.7 | 9.1 | 2,340 | 915 | 123 | 210 | 60.90 | 19.0 | 11.1 |
Michigan | 131 | 2,986 | 1,324 | 147 | 209 | 44.34 | 20.3 | 14.3 | 2,743 | 1,058 | 116 | 224 | 61.43 | 23.6 | 12.2 |
Ohio St. | 132 | 2,847 | 1,251 | 165 | 297 | 43.94 | 17.3 | 9.6 | 2,646 | 1,027 | 137 | 249 | 61.19 | 19.3 | 10.6 |
Illinois | 112 | 2,421 | 1,057 | 110 | 193 | 43.66 | 22.0 | 12.5 | 2,245 | 875 | 137 | 224 | 61.02 | 16.4 | 10.0 |
Iowa | 110 | 2,358 | 995 | 130 | 246 | 42.20 | 18.1 | 9.6 | 2,263 | 881 | 118 | 213 | 61.07 | 19.2 | 10.6 |
Purdue | 129 | 2,860 | 1,159 | 127 | 226 | 40.52 | 22.5 | 12.7 | 2,736 | 1,031 | 143 | 294 | 62.32 | 19.1 | 9.3 |
Indiana | 114 | 2,439 | 987 | 172 | 359 | 40.47 | 14.2 | 6.8 | 2,449 | 1,005 | 130 | 255 | 58.96 | 18.8 | 9.6 |
Maryland | 114 | 2,366 | 955 | 147 | 247 | 40.36 | 16.1 | 9.6 | 2,403 | 1,009 | 123 | 266 | 58.01 | 19.5 | 9.0 |
Northwestern | 112 | 2,332 | 907 | 126 | 281 | 38.89 | 18.5 | 8.3 | 2,545 | 1,130 | 166 | 203 | 55.60 | 15.3 | 12.5 |
Rutgers | 108 | 1,919 | 667 | 102 | 189 | 34.76 | 18.8 | 10.2 | 2,454 | 1,240 | 233 | 208 | 49.47 | 10.5 | 11.8 |
Conference Average | 119 | 2,597 | 1,119 | 144 | 238 | 42.81 | 18.5 | 11.8 | 2,438 | 951 | 126 | 231 | 61.09 | 21.0 | 10.6 |
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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 |
85.94 |
2016-11-23 | Minneapolis, MN |
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GAME |
85.66 |
2016-12-09 | Lincoln, Nebraska |
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GAME |
85.23 |
2016-11-20 | Minneapolis, MN |
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GAME |
83.97 |
2016-10-05 | University Park, Pa. |
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GAME |
83.96 |
2016-10-22 | Ann Arbor, Mich. |
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GAME |
82.90 |
2016-11-04 | University Park, Pa. |
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GAME |
82.02 |
2016-12-09 | Madison, Wis. |
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GAME |
81.68 |
2016-10-23 | Lincoln, Nebraska |
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GAME |
81.32 |
2016-11-12 | Evanston, Ill. |
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GAME |
81.31 |
2016-09-24 | East Lansing, Mich. |
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Name | Team | Role |
---|---|---|
Briana Holman | Nebraska | A |
Kadie Rolfzen | Nebraska | A |
Hannah Tapp | Minnesota | A |
Sarah Wilhite | Minnesota | A |
Justine Wong-Orantes | Nebraska | D |
Lauren Carlini | Wisconsin | S |
Kelly Hunter | Nebraska | S |
Name | Team | Role |
---|---|---|
Mikaela Foecke | Nebraska | A |
Molly Haggerty | Wisconsin | A |
Simone Lee | Penn St. | A |
Molly Lohman | Minnesota | A |
Amber Rolfzen | Nebraska | A |
Dalianliz Rosado | Minnesota | D |
Samantha Swenson | Minnesota | S |
Rank | Name | Team |
---|---|---|
1 | Sarah Wilhite | Minnesota |
2 | Lauren Carlini | Wisconsin |
3 | Kelly Hunter | Nebraska |
4 | Samantha Swenson | Minnesota |
5 | Kadie Rolfzen | Nebraska |
Rank | Name | Team |
---|---|---|
1 | Sarah Wilhite | Minnesota |
2 | Kadie Rolfzen | Nebraska |
3 | Molly Haggerty | Wisconsin |
4 | Simone Lee | Penn St. |
5 | Mikaela Foecke | Nebraska |
Rank | Name | Team |
---|---|---|
1 | Lauren Carlini | Wisconsin |
2 | Kelly Hunter | Nebraska |
3 | Samantha Swenson | Minnesota |
4 | Abby Detering | Penn St. |
5 | Jordyn Poulter | Illinois |
Rank | Name | Team |
---|---|---|
1 | Justine Wong-Orantes | Nebraska |
2 | Dalianliz Rosado | Minnesota |
3 | Kelli Bates | Wisconsin |
4 | Kendall White | Penn St. |
5 | Annika Albrecht | Nebraska |
Rk. | Name | Team | WPA |
---|---|---|---|
1 | Sarah Wilhite | Minnesota | 29.9611 |
2 | Lauren Carlini | Wisconsin | 28.2205 |
3 | Samantha Swenson | Minnesota | 27.3075 |
4 | Ashley Evans | Purdue | 26.7551 |
5 | Taylor Hughes | Ohio St. | 25.6965 |
6 | Mackenzi Welsh | Michigan | 24.9045 |
7 | Rachel Minarick | Michigan St. | 23.1310 |
8 | Taylor Sandbothe | Ohio St. | 22.8758 |
9 | Kelly Hunter | Nebraska | 22.8482 |
10 | Kadie Rolfzen | Nebraska | 21.5179 |
Rk. | Name | Team | OWPA |
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1 | Sarah Wilhite | Minnesota | 19.2518 |
2 | Taylor Hughes | Ohio St. | 18.3355 |
3 | Samantha Swenson | Minnesota | 18.1743 |
4 | Ashley Evans | Purdue | 17.8710 |
5 | Taylor Sandbothe | Ohio St. | 17.5370 |
6 | Danielle Cuttino | Purdue | 16.8771 |
7 | Lauren Carlini | Wisconsin | 16.6571 |
8 | Mackenzi Welsh | Michigan | 16.3250 |
9 | Rachel Minarick | Michigan St. | 15.9531 |
10 | Kelly Hunter | Nebraska | 14.9895 |
Rk. | Name | Team | DWPA |
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1 | Jenna Lerg | Michigan | 16.8102 |
2 | Valeria León | Ohio St. | 15.8184 |
3 | Kelli Bates | Wisconsin | 15.1852 |
4 | Brandi Donnelly | Illinois | 15.1522 |
5 | Kelsey Wicinski | Maryland | 14.6785 |
6 | Dalianliz Rosado | Minnesota | 14.6670 |
7 | Kendall White | Penn St. | 14.4048 |
8 | Justine Wong-Orantes | Nebraska | 13.9006 |
9 | Annika Olsen | Iowa | 12.8189 |
10 | Taylor Lebo | Indiana | 12.4858 |
Rk. | Name | Team | WPA/S |
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1 | Sarah Wilhite | Minnesota | 0.2378 |
2 | Lauren Carlini | Wisconsin | 0.2313 |
3 | Samantha Swenson | Minnesota | 0.2167 |
4 | Rachel Minarick | Michigan St. | 0.2084 |
5 | Ashley Evans | Purdue | 0.2074 |
6 | Taylor Hughes | Ohio St. | 0.2023 |
7 | Kelly Hunter | Nebraska | 0.1953 |
8 | Mackenzi Welsh | Michigan | 0.1901 |
9 | Jordyn Poulter | Illinois | 0.1882 |
10 | Loxley Keala | Iowa | 0.1840 |
Rk. | Name | Team | OWPA/S |
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1 | Sarah Wilhite | Minnesota | 0.1528 |
2 | Taylor Hughes | Ohio St. | 0.1444 |
3 | Samantha Swenson | Minnesota | 0.1442 |
4 | Rachel Minarick | Michigan St. | 0.1437 |
5 | Ashley Evans | Purdue | 0.1385 |
6 | Taylor Sandbothe | Ohio St. | 0.1381 |
7 | Lauren Carlini | Wisconsin | 0.1365 |
8 | Danielle Cuttino | Purdue | 0.1308 |
9 | Kelly Hunter | Nebraska | 0.1281 |
10 | Abby Detering | Penn St. | 0.1275 |
Rk. | Name | Team | DWPA/S |
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1 | Brandi Donnelly | Illinois | 0.1353 |
2 | Kelsey Wicinski | Maryland | 0.1347 |
3 | Jenna Lerg | Michigan | 0.1283 |
4 | Valeria León | Ohio St. | 0.1246 |
5 | Kelli Bates | Wisconsin | 0.1245 |
6 | Justine Wong-Orantes | Nebraska | 0.1219 |
7 | Annika Olsen | Iowa | 0.1198 |
8 | Kendall White | Penn St. | 0.1190 |
9 | Dalianliz Rosado | Minnesota | 0.1164 |
10 | Taylor Lebo | Indiana | 0.1095 |
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.