Columbus, OH - Columbus, OH, USA
Explore the pool victory probability density for each fencer, with their actual victories highlighted in a box. Learn more.
| # | Name | Number of victories | ||||||
|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | ||
| 1 | VALADEZ Emily T. | - | 3% | 16% | 33% | 31% | 14% | 2% |
| 2 | MARSEE Samantha | - | 2% | 11% | 32% | 37% | 16% | 2% |
| 3 | BUHAY Rachel T. | - | - | 3% | 12% | 30% | 37% | 18% |
| 3 | DESAI Maya D. | - | 1% | 5% | 18% | 34% | 31% | 11% |
| 5 | NEWELL Alexia C. | - | - | 3% | 14% | 32% | 36% | 15% |
| 6 | ZIELINSKI Isabella G. | - | 1% | 9% | 25% | 36% | 23% | 6% |
| 7 | FERRARI-BRIDGERS Marinella O. | - | 3% | 14% | 30% | 32% | 17% | 3% |
| 8 | MATAIEV Natalie S. | - | 1% | 6% | 21% | 35% | 29% | 8% |
| 9 | WANG Elsabella Y. | - | 4% | 18% | 33% | 30% | 13% | 2% |
| 10 | KALINICHENKO Alexandra (Sasha) | - | 3% | 18% | 38% | 32% | 9% | |
| 11 | KUZNETSOVA Nastassja | - | - | 3% | 15% | 33% | 35% | 14% |
| 12 | TUCKER Iman R. | - | - | 1% | 8% | 26% | 41% | 25% |
| 13 | PETTIT Sara M. | - | 8% | 25% | 35% | 23% | 7% | 1% |
| 14 | SCHMITT Alana P. | - | 2% | 11% | 28% | 34% | 20% | 5% |
| 15 | ROGERS Pauline E. | - | 7% | 25% | 35% | 24% | 8% | 1% |
| 16 | YODER Bridget H. | 1% | 6% | 23% | 37% | 26% | 7% | |
| 17 | MANUBAG Amanda R. | - | 1% | 8% | 24% | 35% | 25% | 7% |
| 18 | TOM Kristen Noelle C. | - | 2% | 11% | 28% | 35% | 20% | 4% |
| 19 | FISHER Nicole C. | - | 1% | 6% | 21% | 35% | 28% | 9% |
| 20 | BALMASEDA Sabrina F. | - | 1% | 11% | 29% | 35% | 20% | 4% |
| 21 | XU Ellen | - | 2% | 9% | 25% | 35% | 23% | 6% |
| 22 | KOO Samantha | - | - | 2% | 12% | 34% | 39% | 12% |
| 23 | SHAY-TANNAS Zoe | - | 1% | 9% | 28% | 37% | 21% | 4% |
| 24 | XI Shining | - | 1% | 7% | 23% | 36% | 26% | 7% |
| 25 | KOBERSTEIN Maggie | - | - | 2% | 10% | 30% | 39% | 19% |
| 26 | MERRIAM Katherine I. | - | 3% | 16% | 32% | 31% | 14% | 3% |
| 27 | FEIGELES Carolyn A. | - | 4% | 16% | 31% | 31% | 16% | 3% |
| 28 | CHANG Emily | - | 1% | 4% | 16% | 33% | 33% | 13% |
| 29 | NEIBART Fiona | 4% | 19% | 33% | 29% | 13% | 3% | - |
| 30 | LARIMER Katherine E. | - | 5% | 21% | 38% | 28% | 7% | |
| 31 | SCALAMONI-GOLDSTEIN Charlotte S. | - | 4% | 16% | 33% | 33% | 13% | |
| 32 | DHAR Aamina | 9% | 28% | 35% | 21% | 7% | 1% | - |
| 33 | CHIOLDI Mina | - | - | 2% | 9% | 28% | 40% | 22% |
| 34 | LAMBERT Jasmine M. | - | - | - | 2% | 14% | 42% | 42% |
| 35 | CHERNOMORSKY Alexandra E. | - | - | 3% | 13% | 32% | 36% | 16% |
| 36 | DARINGA Arianna | - | 1% | 8% | 24% | 36% | 25% | 6% |
| 37 | CHEN Chloe Y. | - | 1% | 11% | 29% | 36% | 19% | 4% |
| 38 | OXENSTIERNA Carolina | - | 2% | 9% | 24% | 34% | 25% | 7% |
| 39 | LI Victoria J. | - | - | 2% | 11% | 29% | 38% | 19% |
| 40 | STONE Hava S. | - | - | 4% | 16% | 33% | 33% | 13% |
| 41 | GULATI Ria | - | - | 2% | 10% | 28% | 39% | 20% |
| 42 | MEIEROVICH Sophie | 1% | 6% | 20% | 33% | 28% | 12% | 2% |
| 43 | BENTOLILA Thalia | 6% | 24% | 34% | 25% | 9% | 2% | - |
| 44 | ABOUDAHER Janna A. | - | 5% | 17% | 31% | 30% | 14% | 3% |
| 45 | EDWARDS Darby | - | 1% | 7% | 24% | 36% | 25% | 7% |
| 46 | RHIE Lena | - | 4% | 19% | 34% | 29% | 12% | 2% |
| 47 | LIM Isabel K. | - | 2% | 11% | 30% | 38% | 18% | |
| 48 | NIELSEN Dianna M. | 2% | 14% | 35% | 34% | 14% | 2% | |
| 49 | BHATTACHARJEE Rhea | - | 5% | 22% | 38% | 28% | 6% | |
| 50 | ROBINSON Stella | 7% | 27% | 37% | 23% | 6% | 1% | |
| 51 | BAE EMMELINE | 1% | 11% | 32% | 36% | 17% | 3% | |
| 52 | EDGINGTON Grace | - | 1% | 5% | 17% | 34% | 32% | 11% |
| 53 | BENOIT Adelaide L. | - | 1% | 9% | 26% | 35% | 22% | 5% |
| 54 | PLONKA Kaley V. | 5% | 29% | 38% | 21% | 6% | 1% | - |
| 55 | KRYLOVA Valery | - | 1% | 8% | 25% | 36% | 24% | 6% |
| 56 | MILLER Mattea K. | - | 3% | 18% | 35% | 30% | 12% | 2% |
| 57 | SHIN Andrea Y. | - | 2% | 14% | 35% | 35% | 13% | |
| 58 | SKAGGS Natalie M. | - | 2% | 11% | 29% | 35% | 19% | 4% |
| 59 | KALRA Siya L. | - | 1% | 8% | 24% | 36% | 25% | 7% |
| 60 | BINSTOCK Mari I. | - | 8% | 27% | 35% | 22% | 7% | 1% |
| 61 | NOBREGA Carolina S. | 2% | 10% | 26% | 33% | 21% | 6% | 1% |
| 62 | CARLUCCI Laura A. | 7% | 26% | 36% | 23% | 7% | 1% | - |
| 63 | IYER Mohini R. | - | 4% | 16% | 33% | 32% | 14% | 2% |
| 64 | GEYER Carolina M. | 1% | 8% | 23% | 33% | 25% | 9% | 1% |
| 65 | MACE Eliza M. | 1% | 10% | 27% | 35% | 22% | 5% | |
| 66 | PATEL Riya | 1% | 11% | 30% | 36% | 19% | 4% | |
| 67 | WILSON Isley N. | - | - | 4% | 19% | 42% | 35% | |
| 68 | PETE Gillian C. | 5% | 28% | 38% | 22% | 6% | 1% | |
| 69 | SUN Alyssa | 1% | 14% | 36% | 34% | 13% | 2% | - |
| 70 | NORMAN Lillia M. | - | 2% | 9% | 24% | 35% | 24% | 7% |
| 70 | YURT Leyla | - | 3% | 13% | 30% | 33% | 17% | 3% |
| 72 | CODY Alexandra C. | - | 2% | 9% | 25% | 35% | 24% | 6% |
| 73 | SHINN-CUNNINGHAM Barbara | - | 1% | 7% | 22% | 36% | 27% | 7% |
| 73 | LOCKETT Audrey | 5% | 23% | 35% | 25% | 9% | 2% | - |
| 75 | BOIS Adele | - | - | 1% | 7% | 25% | 41% | 26% |
| 76 | CANNON Sophia E. | - | 1% | 4% | 16% | 33% | 33% | 13% |
| 77 | ZINNI Kaylyn M. | - | 5% | 20% | 36% | 29% | 9% | |
| 78 | FAUCHER Erin | - | 2% | 12% | 32% | 38% | 16% | |
| 79 | TSAI Anna A. | 22% | 40% | 27% | 9% | 1% | - | - |
| 80 | BAWA Sanya | - | 2% | 16% | 35% | 32% | 13% | 2% |
| 81 | DODRILL Brooke | - | 4% | 18% | 34% | 30% | 12% | 2% |
| 82 | NI Sharon | 1% | 6% | 20% | 34% | 28% | 11% | 1% |
| 83 | HURST Kennedy | 7% | 25% | 34% | 24% | 9% | 2% | - |
| 84 | CALVERT Sarah-Jane E. | - | 1% | 6% | 23% | 37% | 26% | 7% |
| 85 | ULIBARRI Nevaeh L. | 7% | 25% | 34% | 24% | 9% | 2% | - |
| 86 | KITTLE Lauren | 21% | 43% | 28% | 8% | 1% | - | |
| 87 | NOVICK Mia J. | 7% | 29% | 39% | 21% | 5% | - | |
| 88 | DANIELS Erica | 2% | 13% | 31% | 34% | 17% | 3% | |
| 89 | CHEN Grace | 11% | 34% | 35% | 16% | 3% | - | |
| 90 | DEPEW Charlotte R. | 1% | 17% | 35% | 31% | 13% | 3% | - |
| 91 | SHIH Christina | 9% | 31% | 36% | 19% | 5% | 1% | - |
| 92 | BAKER Audrey C. | - | 4% | 18% | 33% | 30% | 13% | 2% |
| 93 | HOVERMAN Hannah A. | - | 5% | 24% | 39% | 25% | 6% | - |
| 94 | GUZMAN Claudia | 10% | 30% | 34% | 19% | 6% | 1% | - |
| 95 | OSBORN Charlotte | - | 2% | 13% | 32% | 34% | 16% | 3% |
| 96 | KIM Sujin | 4% | 19% | 34% | 29% | 12% | 2% | - |
| 96 | HOLMES Emma | 59% | 33% | 7% | 1% | - | - | - |
| 98 | HUA Catherine W. | 19% | 38% | 30% | 11% | 2% | - | - |
| 99 | CLIFTON Nicole R. | 12% | 32% | 34% | 17% | 4% | - | - |
| 99 | DAVIS Jayna M. | 3% | 16% | 31% | 30% | 15% | 4% | - |
| 101 | MEYTIN Sophia E. | 14% | 53% | 27% | 5% | 1% | - | - |
| 102 | GRIFFIN Afwe | 13% | 36% | 34% | 14% | 3% | - | - |
| 103 | BATRA Simran | 23% | 42% | 27% | 8% | 1% | - | |
| 104 | STOODLEY Theresa R. | 5% | 22% | 34% | 26% | 10% | 2% | - |
| 105 | SCHIKORE Anna M. | 7% | 26% | 35% | 23% | 8% | 1% | - |
| 106 | PANIGRAHI Sophia | 11% | 33% | 34% | 17% | 4% | 1% | - |
| 106 | BILILIES Sophia | 6% | 38% | 39% | 15% | 3% | - | - |
| 108 | HAYES Grace Y. | 1% | 7% | 22% | 34% | 26% | 10% | 1% |
| 109 | GORDON Sarah | 15% | 36% | 32% | 14% | 3% | - | - |
| 110 | JIN Olivia P. | 2% | 12% | 28% | 33% | 19% | 5% | 1% |
| 111 | BENTOLILA Yedida | 5% | 21% | 34% | 27% | 11% | 2% | - |
| 112 | WU Michelle | 4% | 30% | 39% | 21% | 5% | 1% | - |
| 113 | SPORN Melanie | 1% | 7% | 24% | 35% | 24% | 8% | 1% |
| 114 | GLUCK Myriam | - | 6% | 23% | 35% | 26% | 9% | 1% |
| 115 | ZENG Xiaoyi | 37% | 43% | 16% | 3% | - | - | - |
| 116 | BHOGAL Sukhleen | 63% | 31% | 5% | - | - | - | - |
| 117 | HUANG Tina | 9% | 35% | 40% | 14% | 2% | - | - |
| 118 | BOWDEN Ms Hope A. | 29% | 46% | 20% | 4% | - | - | - |
| 119 | KIM Nam Heui | 21% | 39% | 28% | 10% | 2% | - | - |
| 119 | ADAMS Morrigan B. | 22% | 40% | 27% | 9% | 1% | - | - |
| 121 | STARR Cynthia (Cindy) H. | 28% | 44% | 22% | 5% | 1% | - | |
| 122 | GLUCK Ariel | 18% | 43% | 29% | 9% | 1% | - | - |
| 122 | LITTLE Shannon | 4% | 20% | 34% | 28% | 12% | 2% | - |
| 125 | WHEELER Kira | 34% | 42% | 20% | 4% | - | - | |
| 126 | WONG Isabelle S. | 15% | 37% | 33% | 13% | 3% | - | - |
| 128 | ELDER Rhiannon C. | 73% | 24% | 3% | - | - | - | - |
| 129 | MORO Diana | 73% | 24% | 3% | - | - | - | - |
The heatmap in this table provides a visual representation of the victory probability distribution for each fencer in their respective pools:
This heatmap visualization offers an immediate understanding of each fencer's expected performance compared to their actual results.