Straight-set wins — full ATP & WTA ranking

Leader

Iga Swiatek

81.0% of their wins came in straight sets

Average: 66.6%
Std. dev.: 6.3
Leader sits at: 2.3σ
Range: 52.6 … 81.0

145 players

#	Player	Value	Pctl	Sample
1	Iga Swiatek#8	81.0%	100.0	295
2	SH Simona Halep	80.8%	99.3	52
3	Emma Raducanu#49	80.2%	98.6	91
4	BF Brenda Fruhvirtova	80.0%	97.9	20
5	Lin Zhu	79.5%	97.2	83
6	Sonay Kartal#124	78.6%	96.5	84
7	CG Camila Giorgi	78.6%	95.8	42
8	Shuai Zhang	78.5%	95.1	107
9	Aryna Sabalenka#1	77.8%	94.4	252
10	SV Sachia Vickery	77.4%	93.8	31
11	VZ Vera Zvonareva	76.2%	93.1	21
12	Danielle Collins	75.5%	92.4	106
13	Tatjana Maria#80	75.2%	91.7	125
14	Mirra Andreeva#5	75.0%	91.0	128
15	Sara Bejlek#38	75.0%	90.3	80
16	Coco Gauff#4	74.6%	89.6	228
17	Liudmila Samsonova#55	74.5%	88.9	145
18	Katerina Siniakova#37	74.4%	88.2	125
19	Anna Bondar#78	74.3%	87.5	136
20	Marie Bouzkova#25	73.5%	86.8	136
21	MV Marketa Vondrousova#140	73.5%	86.1	98
22	Elise Mertens#24	73.1%	85.4	145
23	Madison Keys#23	72.9%	84.7	155
24	PK Petra Kvitova	72.6%	84.0	62
25	Iva Jovic#16	72.4%	83.3	98
26	IB Irina Camelia Begu	72.2%	82.6	54
27	Sara Sorribes Tormo	72.1%	81.9	104
28	Maria Sakkari#33	72.1%	81.3	154
29	Ekaterina Alexandrova#19	71.8%	80.6	156
30	Dalma Galfi	71.7%	79.9	92
31	Barbora Krejcikova#26	71.4%	79.2	119
32	Lulu Sun#117	71.4%	78.5	77
33	Elena Rybakina#2	71.4%	77.8	227
34	Elina Svitolina#9	71.3%	77.1	143
35	XW Xiyu Wang	71.2%	76.4	111
36	Alexandra Eala#20	71.1%	75.7	114
37	Naomi Osaka#13	70.8%	75.0	96
38	ZB Zhuoxuan Bai	70.8%	74.3	24
39	OD Olga Danilovic	70.4%	73.6	71
40	Clara Tauson#30	70.3%	72.9	111
41	Sorana Cirstea#18	70.1%	72.2	127
42	Eva Lys#85	70.0%	71.5	80
43	Yuliia Starodubtseva#65	69.7%	70.8	89
44	Elisabetta Cocciaretto#59	69.2%	70.1	104
45	OJ Ons Jabeur	69.2%	69.4	120
46	Taylor Townsend#110	69.1%	68.8	68
47	Amanda Anisimova#10	69.1%	68.1	123
48	Belinda Bencic#14	69.0%	67.4	158
49	Jessica Pegula#3	68.8%	66.7	234
50	Aliaksandra Sasnovich#141	68.8%	66.0	125

How this is calculated

Minimum 20 wins. 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

Iga Swiatek

81.0% of their wins came in straight sets

Average: 66.6%
Std. dev.: 6.3
Leader sits at: 2.3σ
Range: 52.6 … 81.0

145 players

#	Player	Value	Pctl	Sample
1	Iga Swiatek#8	81.0%	100.0	295
2	SH Simona Halep	80.8%	99.3	52
3	Emma Raducanu#49	80.2%	98.6	91
4	BF Brenda Fruhvirtova	80.0%	97.9	20
5	Lin Zhu	79.5%	97.2	83
6	Sonay Kartal#124	78.6%	96.5	84
7	CG Camila Giorgi	78.6%	95.8	42
8	Shuai Zhang	78.5%	95.1	107
9	Aryna Sabalenka#1	77.8%	94.4	252
10	SV Sachia Vickery	77.4%	93.8	31
11	VZ Vera Zvonareva	76.2%	93.1	21
12	Danielle Collins	75.5%	92.4	106
13	Tatjana Maria#80	75.2%	91.7	125
14	Mirra Andreeva#5	75.0%	91.0	128
15	Sara Bejlek#38	75.0%	90.3	80
16	Coco Gauff#4	74.6%	89.6	228
17	Liudmila Samsonova#55	74.5%	88.9	145
18	Katerina Siniakova#37	74.4%	88.2	125
19	Anna Bondar#78	74.3%	87.5	136
20	Marie Bouzkova#25	73.5%	86.8	136
21	MV Marketa Vondrousova#140	73.5%	86.1	98
22	Elise Mertens#24	73.1%	85.4	145
23	Madison Keys#23	72.9%	84.7	155
24	PK Petra Kvitova	72.6%	84.0	62
25	Iva Jovic#16	72.4%	83.3	98
26	IB Irina Camelia Begu	72.2%	82.6	54
27	Sara Sorribes Tormo	72.1%	81.9	104
28	Maria Sakkari#33	72.1%	81.3	154
29	Ekaterina Alexandrova#19	71.8%	80.6	156
30	Dalma Galfi	71.7%	79.9	92
31	Barbora Krejcikova#26	71.4%	79.2	119
32	Lulu Sun#117	71.4%	78.5	77
33	Elena Rybakina#2	71.4%	77.8	227
34	Elina Svitolina#9	71.3%	77.1	143
35	XW Xiyu Wang	71.2%	76.4	111
36	Alexandra Eala#20	71.1%	75.7	114
37	Naomi Osaka#13	70.8%	75.0	96
38	ZB Zhuoxuan Bai	70.8%	74.3	24
39	OD Olga Danilovic	70.4%	73.6	71
40	Clara Tauson#30	70.3%	72.9	111
41	Sorana Cirstea#18	70.1%	72.2	127
42	Eva Lys#85	70.0%	71.5	80
43	Yuliia Starodubtseva#65	69.7%	70.8	89
44	Elisabetta Cocciaretto#59	69.2%	70.1	104
45	OJ Ons Jabeur	69.2%	69.4	120
46	Taylor Townsend#110	69.1%	68.8	68
47	Amanda Anisimova#10	69.1%	68.1	123
48	Belinda Bencic#14	69.0%	67.4	158
49	Jessica Pegula#3	68.8%	66.7	234
50	Aliaksandra Sasnovich#141	68.8%	66.0	125

How this is calculated

Minimum 20 wins. 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.