October NAC

Div II Men's Foil

Sunday, October 20, 2019 at 2:00 PM

Kansas City, MO - Kansas City, MO, USA

Probability density of pool victories

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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 BESSIRE Nolan S. - - - 1% 8% 35% 56%
2 SUN Jinfeng - - 1% 9% 28% 41% 22%
3 ZHENG Alan H. - 1% 6% 21% 36% 29% 9%
3 WU Michael - 1% 9% 27% 36% 22% 5%
5 CHOI Ethan L. - - - 3% 16% 40% 40%
6 JOSEPH Dominic (Dom) - - 2% 12% 31% 38% 16%
7 ZHANG Henry C. - 1% 4% 16% 33% 33% 13%
8 GUPTA Eashan - 2% 16% 37% 33% 11% 1%
9 CHAN Tyler - 2% 13% 31% 34% 17% 3%
10 OTAKE Jared K. - 4% 15% 29% 31% 17% 4%
11 MURUHIN Yaroslav 1% 7% 22% 34% 26% 10% 1%
12 ZHOU TIMMY - - 4% 18% 35% 31% 11%
13 SANTULLI Tristan 4% 22% 37% 27% 9% 1% -
14 KUMBLA Samarth - 1% 5% 19% 35% 30% 10%
15 SCHULTES Evans - 1% 6% 21% 35% 28% 9%
16 MITCHELL Philip D. - 1% 6% 21% 36% 28% 8%
17 SCHENCK Koen M. - - 2% 10% 28% 39% 21%
18 DESHMUKH Ayush - 5% 18% 32% 29% 13% 2%
19 FOGELSON Frederick J. - 2% 12% 31% 35% 18% 3%
20 SHIBU Pranav - 1% 7% 25% 37% 25% 6%
21 CATLIN Adam - - 3% 15% 34% 35% 13%
22 TSANG Matthew K. - 3% 11% 26% 33% 21% 5%
23 WAN Jason - - 4% 16% 34% 34% 12%
24 AVRON Case B. 1% 7% 23% 35% 25% 9% 1%
25 CAI Jason Zhicheng - 6% 27% 37% 23% 6% 1%
26 VANNI Filippo A. - - 3% 16% 35% 34% 12%
27 ONIK Elijah T. - 2% 10% 25% 33% 22% 6%
28 WONG NICHOLAS A. 1% 7% 23% 35% 25% 9% 1%
29 QIAN Michael - 2% 17% 36% 32% 12% 1%
30 HOBSON Aaron K. 1% 10% 28% 35% 20% 5% 1%
31 DAVIS Christopher M. 5% 21% 33% 26% 11% 2% -
32 RINEHART Conner M. 3% 17% 32% 30% 14% 3% -
33 YI Stephen K. - - 3% 15% 34% 35% 13%
34 COSTELLO Chaissen F. - 1% 6% 19% 34% 30% 10%
35 LIM Ari - - 1% 7% 26% 42% 23%
36 ZHANG Luke T. - - 4% 18% 35% 32% 11%
37 HORSLEY Alexander - - 1% 9% 30% 41% 19%
38 MCCLAIN Bryce C. - - 2% 11% 29% 38% 19%
39 BREIER Matthew F. - 1% 4% 16% 33% 33% 13%
40 DIERKS Kian - 3% 19% 37% 30% 10% 1%
40 LI Richard - - 2% 12% 30% 38% 17%
42 LEVESQUE Louis 20% 40% 29% 10% 2% < 1% -
43 CHENG Matthew S. - 3% 22% 38% 27% 8% 1%
44 WU Nicholas - 2% 12% 29% 34% 19% 4%
45 SCHEMBRI MCCORD Kruz T. - 2% 9% 27% 37% 22% 3%
46 NGUYEN Nish - 1% 10% 28% 35% 21% 4%
47 ANDERSON Colton J. - 5% 21% 34% 28% 11% 2%
48 CHIN Jason Y. - - 2% 12% 32% 38% 16%
49 RAMIREZ David 1% 7% 22% 34% 26% 9% 1%
50 TRAUGOT Braden (Brady) C. - 1% 6% 22% 37% 27% 7%
51 NUNNINK Phillip W. - - 4% 18% 36% 32% 10%
52 MAO Connor - 4% 16% 32% 31% 15% 3%
53 YU Anders - 1% 8% 25% 36% 24% 6%
54 DROUTMAN Ryan - 5% 20% 35% 28% 10% 1%
55 KIM Aaron J. 2% 12% 30% 35% 18% 4% -
56 GATZA Logan 4% 20% 33% 28% 12% 3% -
57 MURRAY Maximo - 4% 18% 35% 30% 12% 2%
58 MAGIDSON Gabriel - 4% 16% 30% 30% 15% 3%
59 ROUNTREE Rob - 3% 14% 31% 33% 16% 3%
60 TSAY Jeremy M. - 2% 13% 29% 33% 19% 4%
61 XU Max - - 4% 15% 33% 34% 14%
62 SONG Aiden S. - - 1% 7% 26% 43% 24%
63 DANKAR Neel - 4% 17% 34% 31% 12% 2%
64 STEPHENS Maximilian A. 2% 14% 34% 32% 14% 3% -
65 BAE Kevin - 2% 9% 25% 35% 23% 6%
66 CRALEY Thomas M. - 1% 7% 25% 38% 24% 5%
67 KLEIN Caleb R. - 1% 5% 19% 34% 31% 11%
68 YEROKHIN Michael N. - - 4% 16% 34% 34% 12%
69 JAUME Andrei - 7% 30% 38% 19% 4% -
70 BERGER Noe A. - - 2% 12% 31% 38% 17%
71 XIAO Anthony 2% 13% 29% 31% 18% 5% 1%
72 BERGEN Thomas R. 4% 20% 34% 28% 12% 2% -
73 FREEDMAN Samuel E. - 1% 9% 26% 37% 22% 5%
74 NEWHARD Noah A. 1% 5% 19% 33% 29% 12% 2%
75 PYO Michael M. - 2% 11% 30% 35% 19% 4%
76 BANERJEE ANUP - - 2% 12% 31% 37% 17%
77 PAI Dong-Ying 4% 20% 34% 28% 11% 2% -
78 WU Jerry - 5% 19% 33% 28% 12% 2%
79 FEDONCHIK Henry J. 1% 7% 23% 34% 25% 9% 1%
80 DOCTOR Aidan L. - - 3% 15% 33% 34% 13%
81 WITTENBERG Jackson H. 1% 10% 31% 35% 18% 4% -
81 DARIANO Noah G. - 1% 8% 26% 37% 23% 5%
83 SONG Dylan S. - 4% 17% 34% 31% 12% 2%
84 HSIUNG Richie 2% 13% 31% 33% 17% 4% -
85 BOOTSMA Shane-Anson 26% 42% 24% 6% 1% - -
86 MILLER Duncan R. 2% 13% 31% 33% 17% 4% -
87 WANG Michael 1% 10% 25% 33% 22% 7% 1%
88 MAHDI Mahdi - 3% 17% 33% 31% 13% 2%
89 PIESNER Joshua C. 4% 22% 37% 27% 9% 1% -
90 KITAGAWA Eric S. 1% 8% 26% 36% 22% 6% 1%
91 LE Vyn A. 1% 6% 21% 34% 27% 10% 2%
92 PHAM-CHANG Duke A. 7% 27% 36% 22% 6% 1% -
93 KIM Ian M. - 4% 21% 36% 28% 10% 1%
94 RYAN Francis D. 5% 23% 37% 26% 8% 1% -
95 WERWA Griffith 7% 33% 38% 18% 4% - -
96 LARGAESPADA LUIS V. 16% 36% 32% 13% 3% - -
96 CHIN Julian S. - 2% 10% 28% 38% 20% 2%
98 MILLIAN Matthew 16% 39% 31% 11% 2% - -
99 PIERCE Logan 40% 41% 16% 3% - - -
100 JEON Caleb A. - - 2% 10% 29% 40% 20%
101 KIM Derek A. 14% 33% 32% 16% 4% 1% -
101 GOGUEN-COMPAGNONI Nicholas - 1% 5% 17% 33% 32% 12%
103 UPTON Craig 18% 54% 24% 4% - - -
104 GILLIAM Jason E. 13% 32% 32% 17% 5% 1% -
104 CHOI Samuel 1% 6% 19% 33% 29% 12% 2%
106 HAINES Ethan 1% 5% 19% 33% 28% 12% 2%
107 PRASANNA Advaith 33% 42% 20% 5% 1% - -
108 SKYWARK Andrew 7% 34% 37% 17% 4% - -
109 GAO William 35% 44% 18% 3% - - -
110 LI Ryan Z. 15% 38% 32% 13% 3% - -
111 GLOVER James 5% 24% 37% 25% 8% 1% -
112 IVARSSON Oliver 3% 16% 31% 30% 15% 4% -
113 RIOS Ethan 16% 38% 31% 12% 2% - -
114 LANG Dong Lin - 5% 19% 33% 29% 12% 2%
115 KAZA Nitish - 5% 18% 32% 29% 13% 2%
116 KIM BANSEOK 2% 37% 40% 17% 3% - -
117 SHIKHMAN Robert 1% 8% 24% 33% 24% 8% 1%
118 SWEENEY Quinn 15% 36% 32% 13% 3% - -
118 GHAZALI Omer 9% 33% 36% 18% 4% 1% -
120 OAKLAND Brennan D. 1% 13% 32% 33% 17% 4% -
121 SELIVANOV Adam 1% 13% 34% 33% 15% 3% -
122 CHIRASHNYA Adam - 1% 5% 19% 36% 31% 9%
123 ARANA Massimo 61% 33% 6% - - - -
124 CHEN Felix 22% 45% 26% 7% 1% - -
125 KUO Evan 12% 33% 34% 16% 4% - -
126 JEFFERY Jakob 41% 41% 15% 3% - - -
127 DECKER Evan M. 20% 38% 29% 11% 2% - -
128 FORTUNE Alexander J. 18% 43% 29% 8% 1% - -
129 BARTEL Jacob L. 1% 10% 31% 35% 18% 4% -
130 TANG Adrian 44% 40% 13% 2% - - -
131 MCLAUGHLIN Lloyd I. 5% 21% 33% 26% 12% 3% -
132 BOUSSY Luciano 67% 29% 4% - - - -
133 STONE Henry J. 5% 34% 38% 18% 4% - -
134 WOODALL Ian L. 62% 33% 4% - - - -
134 SANTOS Carlos R. 38% 41% 17% 4% - - -
136 FLYNN Ian 3% 17% 35% 31% 13% 2% -
137 GNEUHS Sam 60% 35% 4% - - - -
138 BERNHARDT Hank 89% 10% - - - - -
138 KHIEW Jaren 25% 43% 25% 6% 1% - -
140 COLLUM Thomas 58% 35% 7% 1% - - -

Explanation

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.