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 | 1,819.0441 | 1,712.6518 | 1,765.0465 | 54.25 | 74.63 | 0.267 |
2nd | Wisconsin | 1,801.6989 | 1,701.8295 | 1,751.0523 | 53.21 | 73.97 | 0.261 |
3rd | Penn St. | 1,802.5736 | 1,684.0214 | 1,742.2894 | 54.76 | 72.78 | 0.267 |
4th | Minnesota | 1,797.2564 | 1,685.4350 | 1,740.4479 | 53.93 | 72.73 | 0.250 |
5th | Illinois | 1,762.5918 | 1,645.4264 | 1,703.0018 | 53.42 | 69.56 | 0.207 |
6th | Ohio St. | 1,743.8031 | 1,628.2985 | 1,685.0614 | 51.77 | 69.59 | 0.216 |
7th | Purdue | 1,737.2333 | 1,621.4521 | 1,678.3446 | 50.82 | 67.78 | 0.196 |
8th | Michigan St. | 1,730.1194 | 1,622.0474 | 1,675.2121 | 50.25 | 68.37 | 0.183 |
9th | Michigan | 1,724.1553 | 1,619.8869 | 1,671.2081 | 50.07 | 68.57 | 0.168 |
10th | Northwestern | 1,681.0395 | 1,562.1543 | 1,620.5071 | 48.27 | 65.74 | 0.133 |
11th | Indiana | 1,654.1267 | 1,548.6368 | 1,600.5129 | 46.56 | 63.02 | 0.084 |
12th | Iowa | 1,663.8342 | 1,537.9795 | 1,599.6696 | 46.21 | 65.48 | 0.121 |
13th | Maryland | 1,635.7442 | 1,525.7293 | 1,579.7793 | 44.06 | 63.82 | 0.055 |
14th | Rutgers | 1,541.4378 | 1,438.9070 | 1,489.2903 | 40.32 | 57.38 | -0.020 |
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 | Penn St. | 0.3587 | 46.59 | 10.72 | 43.15 | 42.17 | 3.74 | 5.95 |
2nd | Nebraska | 0.3488 | 45.29 | 10.41 | 41.53 | 42.17 | 3.76 | 5.93 |
3rd | Minnesota | 0.3442 | 44.77 | 10.35 | 42.17 | 43.16 | 4.12 | 5.87 |
4th | Wisconsin | 0.3438 | 46.11 | 11.73 | 43.60 | 40.22 | 4.76 | 5.22 |
5th | Purdue | 0.3198 | 45.02 | 13.04 | 41.93 | 40.84 | 3.93 | 6.23 |
6th | Ohio St. | 0.3114 | 43.92 | 12.78 | 40.61 | 43.11 | 4.41 | 6.25 |
7th | Michigan St. | 0.3088 | 45.03 | 14.15 | 41.60 | 41.11 | 5.12 | 6.18 |
8th | Illinois | 0.3055 | 42.95 | 12.40 | 40.08 | 43.16 | 4.91 | 4.51 |
9th | Michigan | 0.2998 | 42.77 | 12.79 | 39.93 | 42.80 | 5.37 | 4.78 |
10th | Iowa | 0.2852 | 42.18 | 13.66 | 39.80 | 43.61 | 6.28 | 6.46 |
11th | Northwestern | 0.2775 | 41.74 | 13.99 | 38.65 | 43.55 | 6.00 | 6.45 |
12th | Indiana | 0.2517 | 41.41 | 16.24 | 38.35 | 40.98 | 5.66 | 7.10 |
13th | Maryland | 0.2474 | 39.54 | 14.80 | 36.74 | 45.71 | 6.01 | 7.61 |
14th | Rutgers | 0.2027 | 36.37 | 16.09 | 33.79 | 49.55 | 5.87 | 6.07 |
Rnk. | Team | O_Hit% | O_Kill% | O_HE% | O_AST% | DIG% | BLK% | O_ACE% |
---|---|---|---|---|---|---|---|---|
1st | Nebraska | 0.0818 | 26.77 | 18.59 | 25.42 | 56.87 | 8.45 | 2.59 |
2nd | Wisconsin | 0.0832 | 27.30 | 18.98 | 26.12 | 56.85 | 8.54 | 3.84 |
3rd | Penn St. | 0.0915 | 29.65 | 20.50 | 28.31 | 54.68 | 9.46 | 3.91 |
4th | Minnesota | 0.0943 | 28.06 | 18.63 | 27.09 | 55.55 | 8.45 | 3.87 |
5th | Ohio St. | 0.0952 | 28.11 | 18.59 | 26.86 | 56.48 | 8.23 | 4.95 |
6th | Illinois | 0.0980 | 29.09 | 19.29 | 27.66 | 54.50 | 8.71 | 2.99 |
7th | Purdue | 0.1238 | 30.83 | 18.45 | 28.66 | 53.54 | 7.61 | 5.57 |
8th | Michigan St. | 0.1262 | 30.92 | 18.30 | 29.13 | 54.14 | 8.28 | 4.85 |
9th | Michigan | 0.1317 | 30.20 | 17.04 | 28.90 | 55.20 | 6.75 | 3.72 |
10th | Northwestern | 0.1446 | 31.28 | 16.81 | 28.91 | 54.45 | 6.79 | 4.46 |
11th | Iowa | 0.1637 | 32.95 | 16.58 | 30.72 | 53.49 | 5.82 | 4.26 |
12th | Indiana | 0.1677 | 33.21 | 16.44 | 30.39 | 51.46 | 6.72 | 3.65 |
13th | Maryland | 0.1928 | 35.64 | 16.35 | 34.02 | 49.60 | 6.97 | 3.95 |
14th | Rutgers | 0.2231 | 36.53 | 14.21 | 33.79 | 49.49 | 6.51 | 5.71 |
Description | Average | Remove First and Last | Remove Top and Bottom 2 | Remove Top and Bottom 3 | Composite |
---|---|---|---|---|---|
Scores | 1,664.3874 | 1,670.5905 | 1,671.6255 | 1,671.7870 | 1,669.5976 |
Difference | 6.2032 | 7.2381 | 7.3996 | 6.9470 |
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 |
Penn St. | 115 | 2,691 | 1,284 | 129 | 183 | 47.72 | 20.9 | 14.7 | 2,167 | 735 | 94 | 232 | 66.08 | 23.1 | 9.3 |
Nebraska | 129 | 3,051 | 1,387 | 140 | 232 | 45.46 | 21.8 | 13.2 | 2,544 | 850 | 79 | 237 | 66.59 | 32.2 | 10.7 |
Wisconsin | 117 | 2,707 | 1,211 | 107 | 201 | 44.74 | 25.3 | 13.5 | 2,315 | 782 | 94 | 222 | 66.22 | 24.6 | 10.4 |
Minnesota | 129 | 3,005 | 1,374 | 142 | 160 | 45.72 | 21.2 | 18.8 | 2,570 | 901 | 105 | 190 | 64.94 | 24.5 | 13.5 |
Illinois | 122 | 2,785 | 1,262 | 93 | 138 | 45.31 | 29.9 | 20.2 | 2,484 | 953 | 81 | 231 | 61.63 | 30.7 | 10.8 |
Ohio St. | 131 | 2,924 | 1,286 | 147 | 268 | 43.98 | 19.9 | 10.9 | 2,681 | 1,026 | 138 | 229 | 61.73 | 19.4 | 11.7 |
Purdue | 122 | 2,796 | 1,243 | 145 | 224 | 44.46 | 19.3 | 12.5 | 2,564 | 994 | 155 | 214 | 61.23 | 16.5 | 12.0 |
Michigan St. | 119 | 2,667 | 1,141 | 132 | 246 | 42.78 | 20.2 | 10.8 | 2,524 | 981 | 132 | 231 | 61.13 | 19.1 | 10.9 |
Michigan | 123 | 2,774 | 1,165 | 94 | 158 | 42.00 | 29.5 | 17.6 | 2,654 | 1,043 | 109 | 210 | 60.70 | 24.3 | 12.6 |
Northwestern | 107 | 2,323 | 946 | 119 | 223 | 40.72 | 19.5 | 10.4 | 2,363 | 983 | 114 | 191 | 58.40 | 20.7 | 12.4 |
Indiana | 116 | 2,491 | 1,017 | 153 | 300 | 40.83 | 16.3 | 8.3 | 2,556 | 1,092 | 101 | 210 | 57.28 | 25.3 | 12.2 |
Iowa | 115 | 2,461 | 958 | 134 | 257 | 38.93 | 18.4 | 9.6 | 2,587 | 1,085 | 126 | 213 | 58.06 | 20.5 | 12.1 |
Maryland | 122 | 2,600 | 1,008 | 177 | 276 | 38.77 | 14.7 | 9.4 | 2,737 | 1,153 | 117 | 250 | 57.87 | 23.4 | 10.9 |
Rutgers | 109 | 2,072 | 713 | 105 | 203 | 34.41 | 19.7 | 10.2 | 2,582 | 1,261 | 158 | 182 | 51.16 | 16.3 | 14.2 |
Conference Average | 120 | 2,668 | 1,143 | 130 | 219 | 42.56 | 21.2 | 12.9 | 2,523 | 989 | 115 | 217 | 60.93 | 22.9 | 11.7 |
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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 |
86.37 |
2015-10-23 | Lincoln, Nebraska |
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GAME |
83.06 |
2015-11-25 | Minneapolis, MN |
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GAME |
82.18 |
2015-11-21 | West Lafayette, Ind. |
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GAME |
82.17 |
2015-11-18 | Champaign, Ill. |
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GAME |
81.74 |
2015-10-24 | Ann Arbor, Mich. |
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GAME |
81.23 |
2015-11-11 | East Lansing, Mich. |
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GAME |
81.21 |
2015-10-17 | Minneapolis, MN |
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GAME |
80.63 |
2015-11-27 | Ann Arbor, Mich. |
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GAME |
80.01 |
2015-10-02 | University Park, Pa. |
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GAME |
79.99 |
2015-10-14 | Madison, Wis. |
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Name | Team | Role |
---|---|---|
Megan Courtney | Penn St. | A |
Haleigh Nelson | Wisconsin | A |
Amber Rolfzen | Nebraska | A |
Daly Santana | Minnesota | A |
Justine Wong-Orantes | Nebraska | D |
Lauren Carlini | Wisconsin | S |
Kelly Hunter | Nebraska | S |
Name | Team | Role |
---|---|---|
Jocelynn Birks | Illinois | A |
Kadie Rolfzen | Nebraska | A |
Hannah Tapp | Minnesota | A |
Paige Tapp | Minnesota | A |
Taylor Morey | Wisconsin | D |
Ashley Evans | Purdue | S |
Samantha Swenson | Minnesota | S |
Rank | Name | Team |
---|---|---|
1 | Lauren Carlini | Wisconsin |
2 | Daly Santana | Minnesota |
3 | Kelly Hunter | Nebraska |
4 | Samantha Swenson | Minnesota |
5 | Megan Courtney | Penn St. |
Rank | Name | Team |
---|---|---|
1 | Daly Santana | Minnesota |
2 | Megan Courtney | Penn St. |
3 | Kadie Rolfzen | Nebraska |
4 | Jocelynn Birks | Illinois |
5 | Amber Rolfzen | Nebraska |
Rank | Name | Team |
---|---|---|
1 | Lauren Carlini | Wisconsin |
2 | Kelly Hunter | Nebraska |
3 | Samantha Swenson | Minnesota |
4 | Ashley Evans | Purdue |
5 | Jordyn Poulter | Illinois |
Rank | Name | Team |
---|---|---|
1 | Justine Wong-Orantes | Nebraska |
2 | Taylor Morey | Wisconsin |
3 | Dalianliz Rosado | Minnesota |
4 | Brandi Donnelly | Illinois |
5 | Amanda Neill | Purdue |
Rk. | Name | Team | WPA |
---|---|---|---|
1 | Daly Santana | Minnesota | 31.9476 |
2 | Samantha Swenson | Minnesota | 28.7417 |
3 | Kelly Hunter | Nebraska | 28.3029 |
4 | Ashley Evans | Purdue | 27.9866 |
5 | Lauren Carlini | Wisconsin | 27.7496 |
6 | Rachel Minarick | Michigan St. | 24.9458 |
7 | Kadie Rolfzen | Nebraska | 24.7468 |
8 | Jocelynn Birks | Illinois | 23.4809 |
9 | Annie Drews | Purdue | 23.0578 |
10 | Elizabeth Campbell | Ohio St. | 22.2044 |
Rk. | Name | Team | OWPA |
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1 | Daly Santana | Minnesota | 19.6470 |
2 | Samantha Swenson | Minnesota | 19.4375 |
3 | Kelly Hunter | Nebraska | 18.6854 |
4 | Ashley Evans | Purdue | 18.3615 |
5 | Lauren Carlini | Wisconsin | 16.3358 |
6 | Rachel Minarick | Michigan St. | 16.0389 |
7 | Abby Cole | Michigan | 15.4007 |
8 | Annie Drews | Purdue | 15.3686 |
9 | Taylor Tashima | Northwestern | 14.9059 |
10 | Hannah Tapp | Minnesota | 14.6071 |
Rk. | Name | Team | DWPA |
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1 | Valeria León | Ohio St. | 16.9492 |
2 | Annika Olsen | Iowa | 16.8692 |
3 | Justine Wong-Orantes | Nebraska | 16.6216 |
4 | Dalianliz Rosado | Minnesota | 16.5362 |
5 | Caroline Niedospial | Northwestern | 16.3896 |
6 | Brandi Donnelly | Illinois | 15.7287 |
7 | Amanda Neill | Purdue | 15.5518 |
8 | Taylor Morey | Wisconsin | 15.3426 |
9 | Daly Santana | Minnesota | 12.3006 |
10 | Courtney Harnish | Indiana | 12.2238 |
Rk. | Name | Team | WPA/S |
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1 | Daly Santana | Minnesota | 0.2477 |
2 | Lauren Carlini | Wisconsin | 0.2372 |
3 | Ashley Evans | Purdue | 0.2313 |
4 | Samantha Swenson | Minnesota | 0.2245 |
5 | Kelly Hunter | Nebraska | 0.2194 |
6 | Jocelynn Birks | Illinois | 0.2135 |
7 | Rachel Minarick | Michigan St. | 0.2114 |
8 | Megan Courtney | Penn St. | 0.2040 |
9 | Caroline Knop | Michigan | 0.2022 |
10 | Taylor Tashima | Northwestern | 0.1993 |
Rk. | Name | Team | OWPA/S |
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1 | Daly Santana | Minnesota | 0.1523 |
2 | Samantha Swenson | Minnesota | 0.1519 |
3 | Ashley Evans | Purdue | 0.1517 |
4 | Kelly Hunter | Nebraska | 0.1448 |
5 | Lauren Carlini | Wisconsin | 0.1396 |
6 | Taylor Tashima | Northwestern | 0.1393 |
7 | Rachel Minarick | Michigan St. | 0.1359 |
8 | Abby Cole | Michigan | 0.1283 |
9 | Jocelynn Birks | Illinois | 0.1272 |
10 | Annie Drews | Purdue | 0.1260 |
Rk. | Name | Team | DWPA/S |
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1 | Caroline Niedospial | Northwestern | 0.1532 |
2 | Annika Olsen | Iowa | 0.1467 |
3 | Justine Wong-Orantes | Nebraska | 0.1362 |
4 | Taylor Morey | Wisconsin | 0.1311 |
5 | Valeria León | Ohio St. | 0.1294 |
6 | Brandi Donnelly | Illinois | 0.1289 |
7 | Dalianliz Rosado | Minnesota | 0.1282 |
8 | Amanda Neill | Purdue | 0.1275 |
9 | Megan Courtney | Penn St. | 0.1065 |
10 | Courtney Harnish | Indiana | 0.1054 |
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.