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 | WILLIAMS Jadeyn E. | - | - | - | 1% | 10% | 37% | 51% |
2 | KIM Zoe | - | - | - | 1% | 11% | 39% | 48% |
3 | SKARBONKIEWICZ Magda | - | - | - | - | 3% | 24% | 73% |
3 | OISHI Megumi | - | - | - | 5% | 23% | 44% | 27% |
5 | TZOU Alexandra | - | - | 1% | 9% | 29% | 41% | 21% |
6 | DUNGEY Amelia S. | - | - | 2% | 11% | 32% | 40% | 16% |
7 | CHIN Erika J. | - | - | 1% | 9% | 30% | 41% | 18% |
8 | POSSICK Lola P. | - | - | - | 1% | 7% | 35% | 58% |
9 | GUTHIKONDA Nithya | - | - | 1% | 6% | 24% | 43% | 26% |
10 | LEE Alexandra B. | - | - | - | 1% | 9% | 36% | 53% |
11 | WILLIAMS Chloe C. | - | - | 1% | 4% | 19% | 41% | 35% |
12 | TONG Kunling | - | - | 1% | 7% | 26% | 42% | 24% |
13 | NAZLYMOV Tatiana F. | - | 2% | 12% | 27% | 33% | 20% | 5% |
14 | TUCKER Iman R. | 1% | 7% | 25% | 37% | 24% | 6% | |
15 | BOIS Adele | 1% | 7% | 23% | 35% | 26% | 7% | |
16 | LI Victoria J. | - | 3% | 14% | 30% | 32% | 17% | 3% |
17 | DI PERNA Chiara I. | - | - | - | - | 1% | 14% | 85% |
18 | PAK Kaitlyn | - | - | 1% | 8% | 27% | 43% | 22% |
19 | FOUR-GARCIA Madison | - | - | 1% | 8% | 27% | 42% | 23% |
20 | CHANG Josephine S. | - | - | 1% | 9% | 29% | 41% | 20% |
21 | WILSON Isley N. | - | 2% | 11% | 29% | 36% | 19% | 3% |
22 | WIGGERS Susan Q. | - | 1% | 5% | 18% | 34% | 32% | 11% |
23 | FLOREZ Melissa | 1% | 5% | 19% | 33% | 28% | 12% | 2% |
24 | HULSEBURG Kaitlyn | - | 2% | 10% | 30% | 39% | 19% | |
25 | FREEDMAN Janna N. | - | - | 3% | 19% | 44% | 33% | |
26 | SATHYANATH Kailing | - | 1% | 9% | 25% | 37% | 24% | 4% |
27 | WEBER Juliana I. | - | 6% | 24% | 38% | 25% | 7% | - |
28 | NEWELL Alexia C. | - | 1% | 9% | 25% | 35% | 24% | 6% |
29 | CHING Sapphira S. | - | 1% | 7% | 24% | 38% | 25% | 6% |
29 | KALINICHENKO Alexandra (Sasha) | - | 4% | 21% | 37% | 28% | 8% | 1% |
31 | KOBOZEVA Tamara V. | - | 3% | 15% | 34% | 34% | 12% | 1% |
32 | FERRARI-BRIDGERS Marinella O. | - | 1% | 10% | 32% | 37% | 17% | 3% |
33 | CHEEMA Sophia | - | 1% | 7% | 23% | 36% | 26% | 7% |
34 | SULLIVAN Siobhan R. | - | - | - | 4% | 17% | 41% | 38% |
35 | WU Cici | - | 10% | 34% | 37% | 16% | 2% | < 1% |
36 | KATZ Anat | 1% | 10% | 27% | 35% | 21% | 5% | |
37 | SHOMAN Jenna | - | - | 1% | 7% | 26% | 42% | 24% |
38 | BEALE Zoe M. | - | 1% | 5% | 19% | 35% | 31% | 10% |
39 | TAO Hannah J. | - | - | 5% | 23% | 39% | 26% | 6% |
40 | CHIOLDI Mina | - | 2% | 12% | 28% | 34% | 20% | 4% |
41 | LU Vivian Y. | - | - | - | 5% | 22% | 45% | 28% |
42 | YANG Ashley M. | - | 2% | 13% | 31% | 36% | 16% | 1% |
43 | GORMAN Victoria M. | - | 4% | 16% | 32% | 31% | 14% | 2% |
44 | SCALAMONI-GOLDSTEIN Charlotte S. | - | 3% | 14% | 30% | 32% | 17% | 4% |
44 | CHERNOMORSKY Maria | - | - | 1% | 7% | 27% | 43% | 23% |
46 | TANG Annie L. | - | 3% | 17% | 35% | 33% | 11% | |
47 | TIMOFEYEV Nicole | - | - | 1% | 9% | 30% | 42% | 18% |
48 | SHIN Andrea Y. | - | 8% | 26% | 36% | 23% | 7% | 1% |
49 | BUHAY Rachel T. | - | - | 2% | 13% | 34% | 37% | 14% |
50 | ENGELMAN Madeline A. | - | - | 4% | 18% | 38% | 33% | 7% |
51 | LI Amanda C. | - | 2% | 14% | 34% | 34% | 14% | 2% |
52 | OXENSTIERNA Carolina | - | 4% | 18% | 36% | 32% | 10% | - |
53 | DELSOIN Chelsea C. | - | 2% | 10% | 26% | 34% | 22% | 6% |
54 | LACSON Sarah | - | 1% | 6% | 20% | 34% | 29% | 10% |
55 | KONG Isabel | - | 2% | 9% | 25% | 35% | 23% | 6% |
56 | DARINGA Arianna | 1% | 8% | 26% | 37% | 23% | 6% | 1% |
57 | HURST Kennedy | 34% | 41% | 20% | 5% | 1% | - | - |
58 | CASHMAN Natalie | - | 5% | 18% | 34% | 32% | 11% | |
59 | CHANG Emily | - | 1% | 10% | 30% | 38% | 18% | 3% |
60 | CHAN Audrey | - | 2% | 13% | 32% | 35% | 15% | 2% |
61 | GIRARDI Aemilia | 17% | 43% | 30% | 9% | 1% | - | - |
62 | CARVALHO Isabela A. | - | - | - | 5% | 23% | 45% | 26% |
63 | REDDY Shreya | - | 1% | 8% | 23% | 34% | 26% | 8% |
64 | LARIMER Katherine E. | - | 5% | 25% | 39% | 24% | 6% | 1% |
65 | YONG Erika E. | - | 1% | 9% | 31% | 42% | 17% | |
66 | BAKER Audrey C. | 1% | 7% | 22% | 34% | 26% | 9% | 1% |
67 | YAP Madeline | - | - | 3% | 13% | 31% | 36% | 16% |
68 | LIN Audrey J. | - | 2% | 11% | 30% | 37% | 18% | 2% |
69 | VESTEL Mira B. | - | 1% | 6% | 24% | 40% | 26% | 2% |
70 | CANNON Sophia E. | 1% | 6% | 22% | 35% | 27% | 9% | 1% |
71 | KOO Samantha | - | 1% | 7% | 24% | 37% | 25% | 5% |
72 | MOZHAEVA MARIA | 1% | 12% | 36% | 36% | 14% | 2% | |
73 | D'ORAZIO Isabella | 1% | 9% | 29% | 37% | 20% | 4% | - |
74 | LUKASHENKO Angelina | - | 3% | 15% | 33% | 33% | 15% | 2% |
75 | SIMONIAN Olivia A. | 2% | 32% | 42% | 20% | 4% | - | - |
76 | BLUM Leah I. | - | - | 2% | 11% | 32% | 39% | 16% |
77 | XI Shining | - | 4% | 20% | 38% | 29% | 8% | 1% |
78 | ANDRES Charmaine G. | 5% | 24% | 36% | 25% | 8% | 1% | - |
78 | MARSEE Samantha | - | 3% | 16% | 36% | 33% | 12% | 1% |
80 | FEARNS Zara A. | - | 6% | 23% | 36% | 26% | 8% | 1% |
81 | ROGERS Pauline E. | 10% | 32% | 35% | 18% | 5% | 1% | - |
82 | SUN Alyssa | 14% | 36% | 33% | 14% | 3% | - | - |
83 | JULIEN Michelle | 1% | 6% | 22% | 35% | 27% | 9% | 1% |
84 | LIGH Erenei J. | 1% | 11% | 28% | 34% | 20% | 6% | 1% |
85 | BALMASEDA Sabrina F. | 4% | 19% | 33% | 28% | 12% | 3% | - |
86 | MATAIEV Natalie S. | 1% | 9% | 26% | 36% | 22% | 5% | - |
86 | LU Amy | 25% | 40% | 26% | 8% | 2% | - | - |
88 | YANG Angelina | 2% | 15% | 32% | 33% | 15% | 3% | - |
89 | ATLURI Sara V. | - | 3% | 14% | 31% | 34% | 16% | 2% |
89 | ANDRES Katherine A. | - | 3% | 14% | 32% | 34% | 15% | 2% |
91 | IQBAL Sulphia | 21% | 40% | 28% | 9% | 1% | - | - |
92 | OLSEN Natalie J. | 1% | 6% | 22% | 35% | 26% | 8% | 1% |
93 | PATEL Riya | 2% | 15% | 35% | 33% | 13% | 2% | - |
94 | JIN Olivia P. | 1% | 9% | 30% | 37% | 19% | 4% | - |
95 | ULIBARRI Nevaeh L. | 11% | 45% | 34% | 10% | 1% | - | - |
96 | KIM Sujin | 14% | 36% | 34% | 14% | 3% | - | - |
97 | SU Emma | 9% | 33% | 36% | 17% | 4% | - | - |
98 | YUAN Greta | 1% | 8% | 31% | 37% | 19% | 4% | - |
99 | BALAKUMARAN Maya | 16% | 36% | 31% | 13% | 3% | - | |
100 | LIN Angela | 6% | 26% | 37% | 23% | 7% | 1% | |
101 | KITTLE Lauren | 75% | 23% | 2% | - | - | - | |
102 | WU Erica L. | - | 1% | 7% | 22% | 34% | 27% | 8% |
103 | CALVERT Sarah-Jane E. | 1% | 6% | 20% | 33% | 27% | 11% | 2% |
104 | ZINNI Kaylyn M. | 1% | 9% | 27% | 35% | 21% | 5% | - |
104 | DHAR Aamina | 12% | 33% | 35% | 16% | 4% | - | - |
106 | ZIELINSKI Isabella G. | 1% | 7% | 24% | 35% | 25% | 8% | 1% |
107 | STONE Hava S. | - | 2% | 16% | 35% | 33% | 12% | 2% |
108 | HOVERMAN Hannah A. | 1% | 8% | 25% | 34% | 23% | 7% | 1% |
108 | WANG Elsabella Y. | 5% | 22% | 34% | 26% | 10% | 2% | - |
110 | KALRA Himani V. | - | - | 3% | 16% | 37% | 35% | 8% |
111 | GREENBAUM Ella K. | - | - | 3% | 15% | 32% | 35% | 14% |
111 | SATHE Mehek S. | 3% | 18% | 35% | 30% | 12% | 2% | - |
113 | BENOIT Adelaide L. | - | 5% | 18% | 33% | 30% | 12% | 2% |
114 | CHIN Sophia J. | - | 2% | 11% | 27% | 33% | 21% | 5% |
115 | TODD Phoebe | 24% | 41% | 26% | 8% | 1% | - | - |
115 | BENTOLILA Thalia | 32% | 48% | 17% | 3% | - | - | - |
117 | NYSTROM Sofia C. | 18% | 38% | 30% | 12% | 2% | - | - |
118 | XU Ellen | - | 4% | 16% | 32% | 32% | 14% | 2% |
119 | MERRIAM Katherine I. | 3% | 15% | 31% | 31% | 16% | 4% | - |
119 | CODY Alexandra C. | - | 6% | 27% | 38% | 22% | 6% | 1% |
121 | SADOVA Olga | 1% | 11% | 30% | 36% | 18% | 3% | - |
121 | SINHA Anika | 1% | 11% | 27% | 33% | 21% | 7% | 1% |
121 | CHIANG Emily | 13% | 35% | 34% | 15% | 3% | - | - |
121 | LEVITIS Danielle | 2% | 14% | 32% | 33% | 16% | 3% | - |
125 | ALFARACHE Gabriella C. | 4% | 22% | 37% | 26% | 9% | 2% | - |
126 | SUN Jialing | 45% | 39% | 13% | 2% | - | - | - |
127 | CALLAHAN Chase J. | 4% | 18% | 34% | 30% | 13% | 2% | |
128 | KRYLOVA Valery | 4% | 20% | 36% | 28% | 10% | 2% | - |
129 | KOLL-BRAVMANN Ryder S. | 47% | 42% | 10% | 1% | - | - | - |
130 | SUBRAMANIAN Nitika | 3% | 33% | 41% | 19% | 3% | - | |
131 | YUN Maya | 5% | 24% | 37% | 25% | 8% | 1% | |
132 | NOVICK Mia J. | 15% | 36% | 32% | 14% | 3% | - | - |
132 | FANG Victoria W. | - | 3% | 19% | 38% | 30% | 9% | 1% |
134 | SCHIKORE Anna M. | 2% | 16% | 44% | 29% | 8% | 1% | - |
135 | PRIEUR Lauren | 3% | 17% | 32% | 30% | 14% | 3% | - |
135 | LIAO Siwen | 1% | 11% | 30% | 34% | 18% | 5% | - |
137 | NEIBART Fiona | 15% | 35% | 32% | 14% | 3% | - | - |
138 | WANG Jianning | 22% | 42% | 27% | 8% | 1% | - | - |
139 | OWENS Celine A. | 1% | 9% | 26% | 36% | 22% | 6% | 1% |
140 | MADA Skye | 23% | 51% | 22% | 3% | - | - | - |
140 | DEPEW Charlotte R. | 12% | 34% | 34% | 16% | 3% | - | - |
142 | YERRAMILLI Kavya | 11% | 32% | 34% | 17% | 5% | 1% | - |
143 | HILD Nisha | 2% | 12% | 31% | 34% | 17% | 4% | - |
144 | CHEN Xinyan | 6% | 26% | 37% | 23% | 7% | 1% | - |
145 | SHI Cathleen | 3% | 17% | 33% | 30% | 14% | 3% | - |
146 | JENKINS Scotland | 21% | 42% | 27% | 8% | 1% | - | - |
147 | NI Sharon | 5% | 22% | 36% | 27% | 9% | 1% | - |
148 | JAVERI Amaya | 32% | 43% | 20% | 4% | - | - | - |
149 | BAKER Amelia M. | 41% | 41% | 15% | 2% | - | - | - |
150 | ZHIZHIN Jeanette | 67% | 28% | 4% | - | - | - | - |
151 | GRINBERG Aliya | 18% | 38% | 30% | 12% | 2% | - | - |
152 | SHOMAN Miriam | 1% | 11% | 35% | 37% | 14% | 2% | |
153 | FU Linqian (Helen) | 11% | 37% | 35% | 14% | 2% | - | - |
153 | PANIGRAHI Sophia | 21% | 41% | 28% | 8% | 1% | - | - |
155 | BHATTACHARJEE Rhea | 6% | 24% | 35% | 25% | 8% | 1% | |
156 | BIAS Lailah N. | 4% | 28% | 39% | 23% | 6% | 1% | - |
157 | PLONKA Kaley V. | 15% | 37% | 33% | 13% | 2% | - | - |
158 | SLOBODSKY Sasha L. | 31% | 42% | 21% | 5% | 1% | - | |
159 | WEI Vivian W. | 3% | 17% | 35% | 31% | 12% | 2% | - |
159 | PANIGRAHI Kingsley | 43% | 43% | 13% | 2% | - | - | - |
159 | LIGH Karis | 63% | 32% | 5% | - | - | - | - |
162 | ENDO Miyuki N. | 19% | 38% | 30% | 11% | 2% | - | - |
162 | LIN Selena | 35% | 42% | 19% | 4% | - | - | - |
164 | SHANNON Sara | 91% | 9% | - | - | - | - | - |
164 | HAN Lauren | 35% | 48% | 15% | 2% | - | - | - |
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.