Gaylord National Resort and Convention Center - National Harbor, MD, 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 | PANTALEON-MAZOLA Amari | - | - | 2% | 12% | 32% | 37% | 16% |
| 2 | MALEK Zolie | - | - | - | 4% | 19% | 41% | 35% |
| 3 | BERMAN greta | - | - | - | 3% | 18% | 44% | 35% |
| 3 | GUGALA Hanna | - | - | - | 4% | 20% | 45% | 31% |
| 5 | JIANG Evelyn | - | - | 1% | 11% | 32% | 40% | 16% |
| 6 | LIU Hannah | - | - | 1% | 7% | 26% | 43% | 24% |
| 7 | LI Sonia | - | 2% | 12% | 29% | 34% | 18% | 4% |
| 8 | FAVO Isabella | - | - | - | - | 2% | 21% | 76% |
| 9 | FERNANDEZ Martina | - | - | - | 1% | 8% | 33% | 58% |
| 9 | ZENG Sarah | - | - | - | 1% | 7% | 33% | 59% |
| 11 | DANTULURI Shalini | - | - | - | 1% | 10% | 37% | 52% |
| 12 | DHAR Layla | - | - | 1% | 6% | 24% | 42% | 27% |
| 12 | HSU Leah | - | - | 1% | 8% | 26% | 41% | 24% |
| 14 | CHIANG Melissa | - | - | 1% | 5% | 23% | 43% | 28% |
| 15 | VINOKUR Anita | - | 1% | 6% | 19% | 34% | 30% | 10% |
| 16 | MYAT Chloe | - | 1% | 5% | 20% | 36% | 30% | 8% |
| 17 | MERCHANT Aishwarya | - | - | 1% | 8% | 29% | 43% | 18% |
| 18 | CHAVAN Arya | - | - | 2% | 10% | 28% | 39% | 21% |
| 19 | KURAEVA Vasilisa | - | - | - | - | 6% | 33% | 60% |
| 20 | BUSH Bethany | - | 2% | 10% | 28% | 35% | 21% | 4% |
| 20 | SUNG Olivia | - | 2% | 12% | 30% | 37% | 18% | 1% |
| 22 | KWON Ava | - | - | 2% | 12% | 35% | 42% | 10% |
| 23 | YUEN Nicole | - | 1% | 7% | 27% | 40% | 22% | 3% |
| 24 | HU Anna | - | - | 1% | 5% | 23% | 46% | 26% |
| 25 | MCAFEE Jada | - | - | 5% | 22% | 38% | 27% | 7% |
| 26 | REN Katherine | - | 3% | 14% | 32% | 34% | 15% | 1% |
| 27 | RANDALL-COLLINS Shea M. | - | 4% | 22% | 42% | 27% | 5% | |
| 28 | WEI JoyAnn | - | - | - | 4% | 18% | 42% | 37% |
| 29 | HAMMERSTROM Aria | - | - | 2% | 11% | 32% | 39% | 16% |
| 30 | STADNIK Emilia | - | 5% | 20% | 35% | 28% | 10% | 1% |
| 31 | KWON Ava | 1% | 11% | 33% | 36% | 16% | 3% | - |
| 32 | MACKAY Katherine | 2% | 11% | 27% | 33% | 21% | 6% | - |
| 33 | DAMBAL Sasha | - | - | 1% | 8% | 27% | 42% | 22% |
| 33 | ZHANG Ashley | 1% | 6% | 20% | 33% | 28% | 11% | 1% |
| 35 | LEOU Korina | - | - | - | 3% | 15% | 41% | 41% |
| 35 | FUNG Iris | - | 1% | 8% | 25% | 37% | 24% | 5% |
| 37 | WANG Callie | - | 1% | 9% | 28% | 40% | 22% | |
| 38 | LOO Kaitlyn | - | - | 2% | 15% | 42% | 41% | |
| 39 | FAN Alexandria | - | 1% | 7% | 24% | 38% | 25% | 5% |
| 40 | LONG Jessie | 1% | 5% | 18% | 33% | 30% | 12% | 1% |
| 41 | SHEN Emily | 2% | 15% | 34% | 32% | 14% | 3% | - |
| 42 | GONG Joy | - | 2% | 10% | 28% | 35% | 20% | 4% |
| 43 | CHANG Norah | 2% | 13% | 32% | 35% | 16% | 3% | - |
| 44 | TA-ZHOU Emma | - | - | 2% | 14% | 35% | 36% | 13% |
| 45 | LEE Alyson | 1% | 9% | 28% | 37% | 21% | 4% | |
| 46 | YU Stella | 1% | 14% | 41% | 33% | 9% | 1% | |
| 47 | CONG Anne | 1% | 6% | 21% | 37% | 28% | 8% | |
| 48 | GONZALEZ Veronika | - | 1% | 9% | 25% | 36% | 24% | 5% |
| 49 | MARAGH Farrah E. | 1% | 6% | 20% | 33% | 28% | 11% | 1% |
| 49 | ZHU Elaine | - | 2% | 15% | 34% | 34% | 14% | 2% |
| 49 | HEATH Isabella | 13% | 33% | 33% | 16% | 4% | 1% | - |
| 52 | YAN Angela | - | 4% | 22% | 38% | 27% | 8% | 1% |
| 53 | NIU Jessica | 1% | 8% | 24% | 33% | 24% | 8% | 1% |
| 54 | BIBLER Anna | 1% | 13% | 34% | 34% | 15% | 3% | - |
| 55 | CASTELO Soleil | 2% | 12% | 30% | 33% | 18% | 5% | - |
| 56 | KIM Audrey | 1% | 8% | 24% | 34% | 24% | 8% | 1% |
| 57 | KU Alathea-Joy | - | 2% | 13% | 32% | 36% | 15% | 2% |
| 58 | CHOI Charlotte | - | 7% | 26% | 37% | 23% | 6% | 1% |
| 59 | WONG Charlene | 6% | 24% | 35% | 25% | 9% | 2% | - |
| 60 | CROOKS Riley | - | 1% | 11% | 36% | 40% | 12% | |
| 61 | BLAKE Anna | - | - | 5% | 19% | 37% | 30% | 8% |
| 61 | ZHU Avril | - | - | 4% | 20% | 40% | 30% | 6% |
| 63 | MAO Elsa | 6% | 26% | 38% | 23% | 6% | 1% | - |
| 64 | SEBASTIAN Ava | - | 5% | 21% | 38% | 28% | 8% | 1% |
| 65 | BORGUETA Madison | - | 1% | 7% | 28% | 39% | 22% | 4% |
| 66 | MERMEGAS Olivia | - | 3% | 15% | 34% | 34% | 12% | 1% |
| 67 | NADKARNI Marisa | - | 5% | 19% | 33% | 29% | 12% | 2% |
| 68 | SHMULER Fiona | 1% | 8% | 25% | 35% | 24% | 7% | 1% |
| 69 | WANG JiaQi | - | 1% | 5% | 21% | 38% | 29% | 7% |
| 70 | GUHA Surabhi | 3% | 17% | 32% | 30% | 14% | 3% | - |
| 71 | MEYERSON Michelle | 3% | 17% | 35% | 31% | 13% | 2% | |
| 72 | DHAR Rana | - | 1% | 11% | 33% | 36% | 16% | 2% |
| 72 | SEVASTOPULO Sahra | 2% | 15% | 35% | 33% | 13% | 2% | - |
| 74 | KIM Grace | 1% | 10% | 30% | 37% | 19% | 3% | - |
| 75 | LEE Kaitlin | 1% | 6% | 26% | 39% | 23% | 5% | - |
| 76 | FABRICANT Kioka R. | - | 5% | 22% | 37% | 26% | 8% | 1% |
| 77 | AWAD Royce | - | 1% | 5% | 18% | 36% | 32% | 10% |
| 78 | YU Skylar | 1% | 11% | 31% | 35% | 18% | 4% | - |
| 79 | YE Isabella | - | 4% | 16% | 31% | 31% | 15% | 3% |
| 80 | HUANG Neila | 1% | 8% | 24% | 35% | 24% | 7% | 1% |
| 80 | CHERON Helene | 2% | 12% | 29% | 33% | 19% | 5% | - |
| 82 | HU Heidi | 1% | 9% | 27% | 35% | 21% | 6% | 1% |
| 83 | PALMIERI Giuliana M. | 1% | 11% | 31% | 36% | 17% | 3% | - |
| 84 | SEO Kaitlyn | 3% | 25% | 39% | 25% | 7% | 1% | - |
| 85 | LAI Karen | 10% | 47% | 33% | 8% | 1% | - | |
| 86 | WANG Keira | 24% | 47% | 24% | 5% | - | - | - |
| 87 | CHOWDHERY Myra | 3% | 20% | 37% | 29% | 10% | 1% | - |
| 88 | LIU Chelsea | 5% | 33% | 41% | 17% | 3% | - | - |
| 89 | FLEEGER Sophia | 29% | 41% | 23% | 6% | 1% | - | - |
| 90 | OSMINKINA-JONES Kai | 5% | 22% | 34% | 26% | 10% | 2% | - |
| 91 | ALMEDA Galina | 3% | 17% | 34% | 31% | 13% | 2% | - |
| 92 | ZHAO Selena | 44% | 43% | 12% | 1% | - | - | - |
| 93 | NAKATA Gwyneth | 25% | 44% | 24% | 6% | 1% | - | - |
| 94 | MCCARTHY Nora Louisa Abrous | 18% | 38% | 30% | 11% | 2% | - | - |
| 95 | LI Tiffany | - | 6% | 27% | 38% | 22% | 5% | - |
| 96 | PITRUN Viktorie | 11% | 33% | 35% | 17% | 4% | - | - |
| 97 | VISWANATHAN Nishka | 28% | 42% | 23% | 6% | 1% | - | |
| 98 | IANNUZZI Lucy | 8% | 29% | 37% | 21% | 5% | 1% | |
| 99 | GENTILE Vittoria | 2% | 12% | 28% | 33% | 19% | 5% | 1% |
| 100 | ELLINGWOOD Sophia | 24% | 43% | 26% | 7% | 1% | - | - |
| 101 | KIM Grace | 10% | 42% | 35% | 11% | 2% | - | - |
| 102 | PARK Haylie | 1% | 12% | 33% | 35% | 16% | 3% | - |
| 103 | MAO anna | 7% | 27% | 35% | 22% | 7% | 1% | - |
| 104 | XU Elaine | 1% | 10% | 33% | 36% | 16% | 3% | - |
| 105 | ZONG Eliane | 5% | 24% | 38% | 25% | 7% | 1% | - |
| 106 | PARKER Mrinali | 57% | 35% | 7% | 1% | - | - | - |
| 107 | WANG Emily | 3% | 17% | 34% | 31% | 13% | 2% | - |
| 107 | WANG MONA | 7% | 26% | 36% | 23% | 7% | 1% | - |
| 109 | HILD Anya | 4% | 22% | 36% | 27% | 10% | 2% | - |
| 110 | LAFFY Lily | 4% | 24% | 38% | 25% | 8% | 1% | - |
| 110 | FANG Elena | 71% | 25% | 3% | - | - | - | - |
| 112 | TA-ZHOU Sophia | 5% | 22% | 34% | 27% | 10% | 2% | - |
| 112 | WILFRET Katerina | 20% | 47% | 27% | 6% | 1% | - | - |
| 114 | WANG Selina | 47% | 39% | 12% | 2% | - | - | - |
| 115 | HUANG Pierra | 27% | 42% | 24% | 6% | 1% | - | - |
| 116 | YE Madeleine | 5% | 25% | 39% | 24% | 7% | 1% | - |
| 117 | CONVERSO-PARSONS Maia | 53% | 37% | 9% | 1% | - | - | - |
| 118 | MUTHAPPAN Sahana | 4% | 19% | 33% | 29% | 13% | 2% | - |
| 119 | ZHANG Allison | 2% | 16% | 35% | 32% | 12% | 2% | - |
| 120 | LIANG Claire | 6% | 26% | 36% | 23% | 7% | 1% | - |
| 121 | LIAO Amber | 26% | 45% | 23% | 5% | 1% | - | - |
| 122 | SMITH Genevieve | 65% | 30% | 5% | - | - | - | - |
| 123 | ENG Madeleine | 13% | 36% | 34% | 14% | 3% | - | - |
| 124 | HO Sophia | 10% | 29% | 34% | 21% | 6% | 1% | - |
| 125 | FANG Darcy | 66% | 29% | 4% | - | - | - | |
| 126 | GALLAGHER Isabella | 4% | 29% | 42% | 20% | 4% | - | - |
| 127 | MANSPERGER Gia | 5% | 22% | 34% | 27% | 10% | 2% | - |
| 128 | BARNES Sarah | 11% | 31% | 34% | 19% | 5% | 1% | - |
| 129 | STEVENS Sabine | 4% | 20% | 36% | 29% | 11% | 1% | - |
| 130 | CLAIANU Adriana | 31% | 42% | 21% | 5% | - | - | - |
| 131 | IORDANOVA Vela | 26% | 43% | 24% | 6% | 1% | - | - |
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.