Closing out — full ATP & WTA ranking

Leader

Mia Pohankova

100.0% of matches closed out after winning the first set

Average: 85.3%
Std. dev.: 6.1
Leader sits at: 2.4σ
Range: 62.5 … 100.0

1015 players

#	Player	Value	Pctl	Sample
1	Mia Pohankova	100.0%	100.0	27
2	SS Sebastianna Scilipoti	100.0%	99.9	25
3	AO Akiko Omae	100.0%	99.8	24
4	JX Jiayu Xu	100.0%	99.7	24
5	PP Pauline Payet	100.0%	99.6	22
6	MG Maria Aran Teixido Garcia	97.8%	99.5	46
7	SD Sara Dols	97.5%	99.4	80
8	MR Malaika Rapolu	97.4%	99.3	39
9	LM Luciana Moyano	97.1%	99.2	35
10	VM Victoria Milovanova	97.1%	99.1	34
11	JG Joanna Garland	96.9%	99.0	65
12	Victoria Mboko#12	96.9%	98.9	96
13	AS Ayline Esina Samardzic	96.8%	98.8	31
14	CB Clarissa Blomqvist	96.8%	98.7	31
15	IH India Houghton	96.8%	98.6	31
16	HK Hannah Klugman	96.7%	98.5	30
17	JF Jizel Matos Sequeira Fernandes	96.7%	98.4	30
18	Luisina Giovannini	96.3%	98.3	81
19	IK Irem Kurt	96.3%	98.2	27
20	OG Oana Gavrila	96.3%	98.1	27
21	SZ Sonja Zhiyenbayeva	96.3%	98.0	27
22	XZ Xichen Zhao	96.2%	97.9	26
23	KB Kamilla Bartone	96.1%	97.8	51
24	ZR Zi Ying Ruan	96.0%	97.7	25
25	AG Alina Granwehr	95.9%	97.6	73
26	LE Lidia Encheva	95.8%	97.5	72
27	MK Melany Solange Krywoj	95.8%	97.4	24
28	DK Daria Kuczer	95.7%	97.3	47
29	BP Berta Passola	95.7%	97.2	23
30	GP Giulia Safina Popa	95.7%	97.1	23
31	MW Meiling Wang	95.6%	97.0	45
32	BE Basak Eraydin	95.5%	96.9	22
33	PC Paula Cembranos	95.5%	96.8	22
34	JD Josy Daems	95.3%	96.7	43
35	DE Daria Egorova	95.3%	96.6	64
36	LA Lucciana Perez Alarcon	95.2%	96.5	63
37	EL Evialina Laskevich	95.2%	96.4	42
38	JS Jana Stojanova	95.2%	96.4	21
39	KE Ksenia Efremova	95.2%	96.3	21
40	NW Nellie Taraba Wallberg	95.2%	96.2	21
41	OS Oliwia Szymczuch	95.2%	96.1	21
42	SB Savannah Broadus	95.2%	96.0	21
43	AO Alisa Oktiabreva	95.0%	95.9	40
44	ID Iveta Dapkute	95.0%	95.8	40
45	KP Krystyna Pochtovyk	95.0%	95.7	40
46	AP Alessia Popescu	95.0%	95.6	20
47	AC Anastasija Cvetkovic	95.0%	95.5	20
48	IV Ingrid Vojcinakova	95.0%	95.4	20
49	NH Nagomi Higashitani	95.0%	95.3	20
50	AL Adelina Lachinova	94.9%	95.2	39

How this is calculated

Minimum 20 matches after winning the first set. 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

Mia Pohankova

100.0% of matches closed out after winning the first set

Average: 85.3%
Std. dev.: 6.1
Leader sits at: 2.4σ
Range: 62.5 … 100.0

1015 players

#	Player	Value	Pctl	Sample
1	Mia Pohankova	100.0%	100.0	27
2	SS Sebastianna Scilipoti	100.0%	99.9	25
3	AO Akiko Omae	100.0%	99.8	24
4	JX Jiayu Xu	100.0%	99.7	24
5	PP Pauline Payet	100.0%	99.6	22
6	MG Maria Aran Teixido Garcia	97.8%	99.5	46
7	SD Sara Dols	97.5%	99.4	80
8	MR Malaika Rapolu	97.4%	99.3	39
9	LM Luciana Moyano	97.1%	99.2	35
10	VM Victoria Milovanova	97.1%	99.1	34
11	JG Joanna Garland	96.9%	99.0	65
12	Victoria Mboko#12	96.9%	98.9	96
13	AS Ayline Esina Samardzic	96.8%	98.8	31
14	CB Clarissa Blomqvist	96.8%	98.7	31
15	IH India Houghton	96.8%	98.6	31
16	HK Hannah Klugman	96.7%	98.5	30
17	JF Jizel Matos Sequeira Fernandes	96.7%	98.4	30
18	Luisina Giovannini	96.3%	98.3	81
19	IK Irem Kurt	96.3%	98.2	27
20	OG Oana Gavrila	96.3%	98.1	27
21	SZ Sonja Zhiyenbayeva	96.3%	98.0	27
22	XZ Xichen Zhao	96.2%	97.9	26
23	KB Kamilla Bartone	96.1%	97.8	51
24	ZR Zi Ying Ruan	96.0%	97.7	25
25	AG Alina Granwehr	95.9%	97.6	73
26	LE Lidia Encheva	95.8%	97.5	72
27	MK Melany Solange Krywoj	95.8%	97.4	24
28	DK Daria Kuczer	95.7%	97.3	47
29	BP Berta Passola	95.7%	97.2	23
30	GP Giulia Safina Popa	95.7%	97.1	23
31	MW Meiling Wang	95.6%	97.0	45
32	BE Basak Eraydin	95.5%	96.9	22
33	PC Paula Cembranos	95.5%	96.8	22
34	JD Josy Daems	95.3%	96.7	43
35	DE Daria Egorova	95.3%	96.6	64
36	LA Lucciana Perez Alarcon	95.2%	96.5	63
37	EL Evialina Laskevich	95.2%	96.4	42
38	JS Jana Stojanova	95.2%	96.4	21
39	KE Ksenia Efremova	95.2%	96.3	21
40	NW Nellie Taraba Wallberg	95.2%	96.2	21
41	OS Oliwia Szymczuch	95.2%	96.1	21
42	SB Savannah Broadus	95.2%	96.0	21
43	AO Alisa Oktiabreva	95.0%	95.9	40
44	ID Iveta Dapkute	95.0%	95.8	40
45	KP Krystyna Pochtovyk	95.0%	95.7	40
46	AP Alessia Popescu	95.0%	95.6	20
47	AC Anastasija Cvetkovic	95.0%	95.5	20
48	IV Ingrid Vojcinakova	95.0%	95.4	20
49	NH Nagomi Higashitani	95.0%	95.3	20
50	AL Adelina Lachinova	94.9%	95.2	39

How this is calculated

Minimum 20 matches after winning the first set. 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.