The future of US Fencing is at stake!

For transparency, fairness, and athlete support, VOTE NOW for:
(1) Maria Panyi, (2) Andrey Geva, (3) Igor Chirashnya, and (4) Sue Moheb.

Take Action

Laurence Schiller 3-weapon ROC (Region 6)

Veteran Men's Épée

Saturday, February 22, 2020 at 8:00 AM

East Point, GA - East Point, GA, USA

Probability density of pool victories

Birth Year

Reset

Explore the pool victory probability density for each fencer, with their actual victories highlighted in a box. Learn more.

#	Name	Number of victories
#	Name	0	1	2	3	4	5	6	7	8
1	SEAMAN C. Scott (Scott)	-	-	3%	11%	24%	30%	22%	8%	1%
2	SAYLOR David A.	-	3%	13%	28%	31%	18%	6%	1%	-
3	VAUGHN David	-	-	-	1%	6%	20%	33%	29%	10%
3	KIM Jeff	7%	29%	36%	21%	6%	1%	-	-	-
5	DEFORREST Dan	-	-	1%	5%	18%	31%	30%	13%	2%
6	THOMAS Jr. Robert D.	-	2%	10%	23%	31%	23%	9%	2%	-
7	DILLE Brice	-	-	4%	14%	28%	30%	18%	5%	1%
8	SCHARF David	-	4%	15%	27%	29%	18%	6%	1%	-
9	SHOAF Franz	10%	30%	34%	19%	6%	1%	-	-	-

Explanation

The heatmap in this table provides a visual representation of the victory probability distribution for each fencer in their respective pools:

Each cell in a fencer's row corresponds to a specific number of victories, starting from the left with no victories and increasing to the right, indicating victories in all bouts.
The shading of each cell represents the probability of that particular victory outcome for the fencer. Darker shades indicate higher probabilities, suggesting that the outcome is more likely based on past performances. On the other hand, lighter shades point towards less probable outcomes.
The boxed number in a cell represents the actual number of victories the fencer achieved in the pool, making it easy to compare predicted probabilities with actual outcomes at a glance.
By examining the gradient from lighter to darker cells, you can get an intuitive sense of where a fencer's victories are more or less expected based on their historical performance.

This heatmap visualization offers an immediate understanding of each fencer's expected performance compared to their actual results.