Win percentage — full ATP & WTA ranking

Leader

Ekaterina Khayrutdinova

80.5% of matches won

Average: 50.6%
Std. dev.: 10.8
Leader sits at: 2.8σ
Range: 2.6 … 80.5

1317 players

#	Player	Value	Pctl	Sample
1	EK Ekaterina Khayrutdinova	80.5%	100.0	41
2	DE Daria Egorova	80.2%	99.9	81
3	LA Lucciana Perez Alarcon	79.5%	99.8	78
4	VY Valeriya Yushchenko	77.8%	99.8	72
5	AS Anastasiya Konstantinovna Soboleva	77.8%	99.7	36
6	AO Alisa Oktiabreva	77.6%	99.6	58
7	Janice Tjen#36	77.2%	99.5	162
8	PC Patcharin Cheapchandej	77.0%	99.5	87
9	KK Kristina Kroitor	75.9%	99.4	83
10	Luisina Giovannini	75.8%	99.3	124
11	Tereza Valentova#67	75.7%	99.2	140
12	Alexandra Shubladze	75.6%	99.2	127
13	ET Eliska Tichackova	75.0%	99.1	40
14	Kristina Liutova#126	74.3%	99.0	35
15	Victoria Mboko#12	74.2%	98.9	155
16	AT Alice Tubello	73.6%	98.9	140
17	AH Amelia Honer	73.3%	98.8	45
18	NS Natalija Senic	72.7%	98.7	128
19	Jeline Vandromme#132	72.5%	98.6	91
20	DK Daria Khomutsianskaya	72.4%	98.6	98
21	Darja Vidmanova#92	72.2%	98.5	126
22	MS Maria Sholokhova	72.2%	98.4	36
23	JK Jana Kovackova	72.1%	98.3	43
24	JG Joanna Garland	71.3%	98.3	108
25	SR Sofia Camila Rojas	71.1%	98.2	38
26	CH Caijsa Wilda Hennemann	70.9%	98.1	117
27	AG Anastasia Gasanova	70.9%	98.0	158
28	POCCarol Young Suh Lee	70.9%	97.9	127
29	Francesca Jones#107	70.6%	97.9	136
30	JS Joelle Lilly Sophie Steur	70.1%	97.8	107
31	Oleksandra Oliynykova#44	69.9%	97.7	176
32	Dayeon Back	69.6%	97.6	168
33	CB Carson Branstine	69.6%	97.6	102
34	Mia Pohankova	69.6%	97.5	46
35	KK Katarina Kuzmova	69.5%	97.4	197
36	Alina Korneeva#89	69.3%	97.3	114
37	EM Edda Mamedova	69.2%	97.3	52
38	AH Ava Hrastar	69.2%	97.2	39
39	LA Lamis Alhussein Abdel Aziz	69.1%	97.1	181
40	VB Victoria Bosio	69.0%	97.0	129
41	Vendula Valdmannova	68.9%	97.0	90
42	Laura Samson#123	68.9%	96.9	122
43	LE Lidia Encheva	68.8%	96.8	128
44	AO Angella Okutoyi	68.8%	96.7	64
45	KH Katharina Hobgarski	68.6%	96.7	102
46	RD Rositsa Dencheva	68.6%	96.6	102
47	AC Anchisa Chanta	68.6%	96.5	70
48	MG Maria Aran Teixido Garcia	68.6%	96.4	70
49	Lois Boisson	68.5%	96.4	89
50	EV Eliessa Vanlangendonck	68.5%	96.3	73

How this is calculated

Minimum 30 matches with a recorded score. Below that the figure is noise and publishing it would be faking precision. Each family of metrics carries its own counter — 200 matches is not 200 tiebreaks.
Window. Five years of results. These rows need only the scoreline, which exists far further back than serve statistics do.
One division at a time. A player belongs to the Challenger/ITF division when more than half of their matches since 2024 are played there. Mixing the two ranks schedules rather than players: the raw list of closers was headed by an ITF player at 100% over twenty matches.
Not a betting signal. It describes a player, not a price. Our own prediction engine is measured against the market and loses: 0.632 log loss against 0.593.

Leader

Ekaterina Khayrutdinova

80.5% of matches won

Average: 50.6%
Std. dev.: 10.8
Leader sits at: 2.8σ
Range: 2.6 … 80.5

1317 players

#	Player	Value	Pctl	Sample
1	EK Ekaterina Khayrutdinova	80.5%	100.0	41
2	DE Daria Egorova	80.2%	99.9	81
3	LA Lucciana Perez Alarcon	79.5%	99.8	78
4	VY Valeriya Yushchenko	77.8%	99.8	72
5	AS Anastasiya Konstantinovna Soboleva	77.8%	99.7	36
6	AO Alisa Oktiabreva	77.6%	99.6	58
7	Janice Tjen#36	77.2%	99.5	162
8	PC Patcharin Cheapchandej	77.0%	99.5	87
9	KK Kristina Kroitor	75.9%	99.4	83
10	Luisina Giovannini	75.8%	99.3	124
11	Tereza Valentova#67	75.7%	99.2	140
12	Alexandra Shubladze	75.6%	99.2	127
13	ET Eliska Tichackova	75.0%	99.1	40
14	Kristina Liutova#126	74.3%	99.0	35
15	Victoria Mboko#12	74.2%	98.9	155
16	AT Alice Tubello	73.6%	98.9	140
17	AH Amelia Honer	73.3%	98.8	45
18	NS Natalija Senic	72.7%	98.7	128
19	Jeline Vandromme#132	72.5%	98.6	91
20	DK Daria Khomutsianskaya	72.4%	98.6	98
21	Darja Vidmanova#92	72.2%	98.5	126
22	MS Maria Sholokhova	72.2%	98.4	36
23	JK Jana Kovackova	72.1%	98.3	43
24	JG Joanna Garland	71.3%	98.3	108
25	SR Sofia Camila Rojas	71.1%	98.2	38
26	CH Caijsa Wilda Hennemann	70.9%	98.1	117
27	AG Anastasia Gasanova	70.9%	98.0	158
28	POCCarol Young Suh Lee	70.9%	97.9	127
29	Francesca Jones#107	70.6%	97.9	136
30	JS Joelle Lilly Sophie Steur	70.1%	97.8	107
31	Oleksandra Oliynykova#44	69.9%	97.7	176
32	Dayeon Back	69.6%	97.6	168
33	CB Carson Branstine	69.6%	97.6	102
34	Mia Pohankova	69.6%	97.5	46
35	KK Katarina Kuzmova	69.5%	97.4	197
36	Alina Korneeva#89	69.3%	97.3	114
37	EM Edda Mamedova	69.2%	97.3	52
38	AH Ava Hrastar	69.2%	97.2	39
39	LA Lamis Alhussein Abdel Aziz	69.1%	97.1	181
40	VB Victoria Bosio	69.0%	97.0	129
41	Vendula Valdmannova	68.9%	97.0	90
42	Laura Samson#123	68.9%	96.9	122
43	LE Lidia Encheva	68.8%	96.8	128
44	AO Angella Okutoyi	68.8%	96.7	64
45	KH Katharina Hobgarski	68.6%	96.7	102
46	RD Rositsa Dencheva	68.6%	96.6	102
47	AC Anchisa Chanta	68.6%	96.5	70
48	MG Maria Aran Teixido Garcia	68.6%	96.4	70
49	Lois Boisson	68.5%	96.4	89
50	EV Eliessa Vanlangendonck	68.5%	96.3	73

How this is calculated

Minimum 30 matches with a recorded score. Below that the figure is noise and publishing it would be faking precision. Each family of metrics carries its own counter — 200 matches is not 200 tiebreaks.
Window. Five years of results. These rows need only the scoreline, which exists far further back than serve statistics do.
One division at a time. A player belongs to the Challenger/ITF division when more than half of their matches since 2024 are played there. Mixing the two ranks schedules rather than players: the raw list of closers was headed by an ITF player at 100% over twenty matches.
Not a betting signal. It describes a player, not a price. Our own prediction engine is measured against the market and loses: 0.632 log loss against 0.593.