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 | Hawaii | 1,728.4305 | 1,690.0747 | 1,709.1450 | 54.60 | 60.79 | 0.159 |
2nd | Cal Poly | 1,698.9000 | 1,663.2097 | 1,680.9601 | 51.34 | 64.08 | 0.128 |
3rd | UC Santa Barbara | 1,684.4963 | 1,653.4438 | 1,668.8978 | 50.53 | 62.80 | 0.135 |
4th | Long Beach St. | 1,630.0265 | 1,590.9630 | 1,610.3763 | 45.14 | 59.75 | 0.069 |
5th | UC Davis | 1,606.4988 | 1,571.9645 | 1,589.1378 | 46.38 | 58.14 | 0.051 |
6th | CSUN | 1,587.0469 | 1,551.1272 | 1,568.9842 | 46.76 | 57.03 | 0.017 |
7th | UC Irvine | 1,536.1162 | 1,500.4580 | 1,518.1824 | 45.42 | 50.39 | -0.035 |
8th | Cal St. Fullerton | 1,526.8393 | 1,494.0140 | 1,510.3375 | 47.67 | 51.41 | -0.035 |
9th | UC Riverside | 1,492.8399 | 1,462.1165 | 1,477.3983 | 44.36 | 50.55 | -0.062 |
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 | UC Santa Barbara | 0.2953 | 42.45 | 12.92 | 39.65 | 42.81 | 4.65 | 6.35 |
2nd | Hawaii | 0.2874 | 41.22 | 12.48 | 37.96 | 43.49 | 4.36 | 7.13 |
3rd | Cal Poly | 0.2680 | 41.20 | 14.40 | 38.50 | 43.26 | 5.98 | 10.06 |
4th | UC Davis | 0.2642 | 41.67 | 15.25 | 38.31 | 44.08 | 5.38 | 7.81 |
5th | Long Beach St. | 0.2561 | 41.01 | 15.40 | 37.77 | 43.18 | 5.25 | 5.73 |
6th | CSUN | 0.2314 | 37.61 | 14.47 | 35.05 | 47.94 | 5.30 | 6.68 |
7th | UC Irvine | 0.2021 | 36.17 | 15.96 | 33.07 | 46.81 | 6.11 | 6.87 |
8th | Cal St. Fullerton | 0.1839 | 31.75 | 13.36 | 29.25 | 53.90 | 5.76 | 5.27 |
9th | UC Riverside | 0.1826 | 34.75 | 16.49 | 31.62 | 48.58 | 6.00 | 5.56 |
Rnk. | Team | O_Hit% | O_Kill% | O_HE% | O_AST% | DIG% | BLK% | O_ACE% |
---|---|---|---|---|---|---|---|---|
1st | Hawaii | 0.1281 | 29.36 | 16.55 | 26.73 | 54.19 | 7.61 | 3.96 |
2nd | Cal Poly | 0.1399 | 31.18 | 17.19 | 28.91 | 52.67 | 6.93 | 4.97 |
3rd | UC Santa Barbara | 0.1600 | 31.15 | 15.16 | 29.04 | 53.44 | 7.20 | 3.74 |
4th | Long Beach St. | 0.1868 | 33.80 | 15.11 | 31.37 | 52.18 | 6.42 | 5.80 |
5th | UC Davis | 0.2127 | 36.34 | 15.07 | 33.00 | 48.97 | 6.33 | 5.77 |
6th | CSUN | 0.2148 | 36.93 | 15.45 | 33.87 | 48.36 | 6.08 | 4.84 |
7th | Cal St. Fullerton | 0.2193 | 34.78 | 12.84 | 32.66 | 51.41 | 4.86 | 5.48 |
8th | UC Irvine | 0.2367 | 37.60 | 13.94 | 34.47 | 46.86 | 5.28 | 8.02 |
9th | UC Riverside | 0.2444 | 37.52 | 13.08 | 34.39 | 48.74 | 4.46 | 5.56 |
Description | Average | Remove First and Last | Remove Top and Bottom 2 | Remove Top and Bottom 3 | Composite |
---|---|---|---|---|---|
Scores | 1,592.6022 | 1,592.4109 | 1,591.1157 | 1,589.4994 | 1,591.4071 |
Difference | -0.1913 | -1.4865 | -3.1027 | -1.5935 |
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 |
Cal Poly | 110 | 2,298 | 1,152 | 204 | 272 | 50.13 | 11.3 | 8.4 | 2,017 | 814 | 110 | 227 | 59.64 | 18.3 | 8.9 |
Hawaii | 114 | 2,521 | 1,278 | 156 | 240 | 50.69 | 16.2 | 10.5 | 2,182 | 945 | 97 | 217 | 56.69 | 22.5 | 10.1 |
UC Santa Barbara | 107 | 2,253 | 1,076 | 130 | 199 | 47.76 | 17.3 | 11.3 | 2,005 | 814 | 90 | 211 | 59.40 | 22.3 | 9.5 |
UC Davis | 112 | 2,362 | 1,063 | 162 | 265 | 45.00 | 14.6 | 8.9 | 2,352 | 1,066 | 137 | 241 | 54.68 | 17.2 | 9.8 |
CSUN | 108 | 2,283 | 1,035 | 133 | 215 | 45.34 | 17.2 | 10.6 | 2,367 | 1,082 | 123 | 209 | 54.29 | 19.2 | 11.3 |
Long Beach St. | 110 | 2,353 | 1,003 | 117 | 236 | 42.63 | 20.1 | 10.0 | 2,337 | 1,024 | 144 | 238 | 56.18 | 16.2 | 9.8 |
Cal St. Fullerton | 100 | 2,037 | 984 | 93 | 125 | 48.31 | 21.9 | 16.3 | 2,168 | 1,091 | 117 | 215 | 49.68 | 18.5 | 10.1 |
UC Riverside | 101 | 2,107 | 940 | 106 | 255 | 44.61 | 19.9 | 8.3 | 2,362 | 1,207 | 126 | 192 | 48.90 | 18.7 | 12.3 |
UC Irvine | 105 | 2,084 | 901 | 112 | 210 | 43.23 | 18.6 | 9.9 | 2,387 | 1,261 | 197 | 214 | 47.17 | 12.1 | 11.2 |
Conference Average | 107 | 2,255 | 1,048 | 135 | 224 | 46.41 | 17.4 | 10.5 | 2,242 | 1,034 | 127 | 218 | 54.07 | 18.3 | 10.3 |
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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 |
80.89 |
2019-11-02 |
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GAME |
76.24 |
2019-10-06 |
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GAME |
75.83 |
2019-11-08 | Davis, Calif. |
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GAME |
75.65 |
2019-10-29 | Santa Barbara, CA |
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GAME |
75.58 |
2019-09-24 | Santa Barbara, CA |
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GAME |
75.00 |
2019-10-26 |
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GAME |
74.81 |
2019-09-28 |
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GAME |
74.63 |
2019-10-13 | Davis, Calif. |
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GAME |
74.39 |
2019-10-11 |
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GAME |
74.16 |
2019-10-24 | Davis, Calif. |
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Name | Team | Role |
---|---|---|
Maia Dvoracek | Cal Poly | A |
Amber Igiede | Hawaii | A |
Lindsey Ruddins | UC Santa Barbara | A |
Sky Williams | Hawaii | A |
Zoe Fleck | UC Santa Barbara | D |
Norene Iosia | Hawaii | D |
Avalon DeNecochea | Cal Poly | S |
Name | Team | Role |
---|---|---|
Julia Crawford | Cal St. Fullerton | A |
Hanna Hellvig | Hawaii | A |
Madilyn Mercer | Cal Poly | A |
Meredith Phillips | Cal Poly | A |
Brooke Sickle | Hawaii | D |
Riley Wagoner | Hawaii | D |
Carly Aigner-Swesey | Long Beach St. | S |
Rank | Name | Team |
---|---|---|
1 | Lindsey Ruddins | UC Santa Barbara |
2 | Norene Iosia | Hawaii |
3 | Avalon DeNecochea | Cal Poly |
4 | Maia Dvoracek | Cal Poly |
5 | Brooke Sickle | Hawaii |
Rank | Name | Team |
---|---|---|
1 | Lindsey Ruddins | UC Santa Barbara |
2 | Maia Dvoracek | Cal Poly |
3 | Hanna Hellvig | Hawaii |
4 | Amber Igiede | Hawaii |
5 | Julia Crawford | Cal St. Fullerton |
Rank | Name | Team |
---|---|---|
1 | Avalon DeNecochea | Cal Poly |
2 | Carly Aigner-Swesey | Long Beach St. |
3 | Jane Seslar | UC Davis |
4 | Tia Chavira | Long Beach St. |
5 | Kelly Negron | UC Irvine |
Rank | Name | Team |
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1 | Zoe Fleck | UC Santa Barbara |
2 | Riley Wagoner | Hawaii |
3 | Savahna Costello | Cal St. Fullerton |
4 | Mika Dickson | Cal Poly |
5 | Torre Glasker | UC Santa Barbara |
Rk. | Name | Team | WPA |
---|---|---|---|
1 | Lindsey Ruddins | UC Santa Barbara | 23.1928 |
2 | Avalon DeNecochea | Cal Poly | 20.3732 |
3 | Julia Crawford | Cal St. Fullerton | 20.0728 |
4 | Maia Dvoracek | Cal Poly | 19.7062 |
5 | Jane Seslar | UC Davis | 19.3833 |
6 | Lauren Matias | UC Davis | 19.1292 |
7 | Norene Iosia | Hawaii | 19.0892 |
8 | Savahna Costello | Cal St. Fullerton | 17.1812 |
9 | Kelly Negron | UC Irvine | 16.9877 |
10 | Yizhi Xue | Long Beach St. | 16.3511 |
Rk. | Name | Team | OWPA |
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1 | Avalon DeNecochea | Cal Poly | 14.4416 |
2 | Lindsey Ruddins | UC Santa Barbara | 14.1512 |
3 | Jane Seslar | UC Davis | 12.6227 |
4 | Maia Dvoracek | Cal Poly | 12.2866 |
5 | Yizhi Xue | Long Beach St. | 11.3343 |
6 | Julia Crawford | Cal St. Fullerton | 10.8006 |
7 | Lauren Matias | UC Davis | 10.4986 |
8 | Kashauna Williams | Long Beach St. | 9.9366 |
9 | Seyvion Waggoner | CSUN | 9.5505 |
10 | Kelly Negron | UC Irvine | 9.1523 |
Rk. | Name | Team | DWPA |
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1 | Savahna Costello | Cal St. Fullerton | 16.3150 |
2 | Hailey Harward | Long Beach St. | 14.4786 |
3 | Makayla Bradford | CSUN | 12.7601 |
4 | Zoe Fleck | UC Santa Barbara | 12.0291 |
5 | Mika Dickson | Cal Poly | 10.5744 |
6 | Shira Lahav | UC Davis | 10.3887 |
7 | Norene Iosia | Hawaii | 10.0794 |
8 | Chloe Owens | UC Irvine | 9.6381 |
9 | Julia Crawford | Cal St. Fullerton | 9.2722 |
10 | Lexi McLeod | CSUN | 9.2614 |
Rk. | Name | Team | WPA/S |
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1 | Lindsey Ruddins | UC Santa Barbara | 0.2577 |
2 | Julia Crawford | Cal St. Fullerton | 0.2230 |
3 | Avalon DeNecochea | Cal Poly | 0.1997 |
4 | Maia Dvoracek | Cal Poly | 0.1932 |
5 | Morgan Kline | UC Riverside | 0.1826 |
6 | Savahna Costello | Cal St. Fullerton | 0.1809 |
7 | Kelly Negron | UC Irvine | 0.1807 |
8 | Norene Iosia | Hawaii | 0.1801 |
9 | Jane Seslar | UC Davis | 0.1731 |
10 | Carly Aigner-Swesey | Long Beach St. | 0.1716 |
Rk. | Name | Team | OWPA/S |
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1 | Lindsey Ruddins | UC Santa Barbara | 0.1572 |
2 | Avalon DeNecochea | Cal Poly | 0.1416 |
3 | Maia Dvoracek | Cal Poly | 0.1205 |
4 | Julia Crawford | Cal St. Fullerton | 0.1200 |
5 | Jane Seslar | UC Davis | 0.1127 |
6 | Carly Aigner-Swesey | Long Beach St. | 0.1120 |
7 | Yizhi Xue | Long Beach St. | 0.1059 |
8 | Kelly Negron | UC Irvine | 0.0974 |
9 | Tia Chavira | Long Beach St. | 0.0972 |
10 | Seyvion Waggoner | CSUN | 0.0965 |
Rk. | Name | Team | DWPA/S |
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1 | Savahna Costello | Cal St. Fullerton | 0.1717 |
2 | Hailey Harward | Long Beach St. | 0.1353 |
3 | Zoe Fleck | UC Santa Barbara | 0.1240 |
4 | Makayla Bradford | CSUN | 0.1204 |
5 | Mika Dickson | Cal Poly | 0.1037 |
6 | Julia Crawford | Cal St. Fullerton | 0.1030 |
7 | Lindsey Ruddins | UC Santa Barbara | 0.1005 |
8 | Renata Bath | UC Riverside | 0.0986 |
9 | Chloe Owens | UC Irvine | 0.0974 |
10 | Morgan Kline | UC Riverside | 0.0965 |
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.