Bagels handed out — full ATP & WTA ranking

Leader

Maria Lourdes Carle

33.3% of the sets they win are 6-0

Average: 18.3%
Std. dev.: 4.5
Leader sits at: 3.3σ
Range: 2.8 … 33.3

153 players

#	Player	Value	Pctl	Sample
1	Maria Lourdes Carle	33.3%	100.0	39
2	Iga Swiatek#8	33.3%	99.3	357
3	Sara Bejlek#38	28.3%	98.7	125
4	Maya Joint#75	27.1%	98.0	193
5	ER Elena Ruse	27.0%	97.4	73
6	GM Greet Minnen	26.7%	96.7	175
7	CW Caroline Wozniacki	26.7%	96.1	33
8	Iva Jovic#16	25.6%	95.4	145
9	Sonay Kartal#124	24.9%	94.7	123
10	Yuliia Starodubtseva#65	24.6%	94.1	173
11	ZB Zhuoxuan Bai	24.6%	93.4	54
12	SH Simona Halep	24.5%	92.8	70
13	Sara Sorribes Tormo	24.2%	92.1	188
14	Mirra Andreeva#5	23.9%	91.4	181
15	MV Marketa Vondrousova#140	23.9%	90.8	145
16	Caty McNally	23.7%	90.1	154
17	Coco Gauff#4	23.6%	89.5	316
18	Cristina Bucsa#40	23.6%	88.8	186
19	Diana Shnaider#17	23.3%	88.2	202
20	Emma Navarro#28	23.2%	87.5	210
21	Anastasia Zakharova#99	23.1%	86.8	177
22	Elise Mertens#24	23.1%	86.2	250
23	Suzan Lamens#148	22.8%	85.5	165
24	VA Victoria Azarenka	22.4%	84.9	150
25	AP Anastasia Pavlyuchenkova	22.4%	84.2	125
26	Erika Andreeva	22.2%	83.6	136
27	MB Mirjam Bjorklund	22.2%	82.9	33
28	Daria Kasatkina#61	21.7%	82.2	276
29	Heather Watson	21.7%	81.6	130
30	Tatjana Maria#80	21.6%	80.9	254
31	JN Jule Niemeier	21.5%	80.3	172
32	Katie Volynets#91	21.3%	79.6	206
33	SE Sara Errani	21.3%	78.9	84
34	Sorana Cirstea#18	21.0%	78.3	221
35	BF Brenda Fruhvirtova	20.9%	77.6	41
36	Nao Hibino	20.8%	77.0	172
37	Marie Bouzkova#25	20.8%	76.3	235
38	Emma Raducanu#49	20.8%	75.7	156
39	Madison Keys#23	20.7%	75.0	228
40	Zeynep Sonmez#52	20.6%	74.3	161
41	Renata Zarazua#73	20.3%	73.7	186
42	Dalma Galfi	20.3%	73.0	181
43	Jessica Bouzas Maneiro#63	20.3%	72.4	170
44	VT Viktoriya Tomova	20.1%	71.7	166
45	MS Marina Stakusic#145	20.0%	71.1	112
46	Yulia Putintseva#82	19.8%	70.4	254
47	Jelena Ostapenko#29	19.8%	69.7	241
48	Emiliana Arango#97	19.8%	69.1	156
49	Harriet Dart#144	19.7%	68.4	198
50	Qinwen Zheng	19.7%	67.8	213

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.
The denominator is sets, not matches. It is 6-0 sets over sets WON, so it does not reward whoever plays more. The minimum is applied to matches with a recorded score, because the count of sets won is not stored as its own column.
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

Maria Lourdes Carle

33.3% of the sets they win are 6-0

Average: 18.3%
Std. dev.: 4.5
Leader sits at: 3.3σ
Range: 2.8 … 33.3

153 players

#	Player	Value	Pctl	Sample
1	Maria Lourdes Carle	33.3%	100.0	39
2	Iga Swiatek#8	33.3%	99.3	357
3	Sara Bejlek#38	28.3%	98.7	125
4	Maya Joint#75	27.1%	98.0	193
5	ER Elena Ruse	27.0%	97.4	73
6	GM Greet Minnen	26.7%	96.7	175
7	CW Caroline Wozniacki	26.7%	96.1	33
8	Iva Jovic#16	25.6%	95.4	145
9	Sonay Kartal#124	24.9%	94.7	123
10	Yuliia Starodubtseva#65	24.6%	94.1	173
11	ZB Zhuoxuan Bai	24.6%	93.4	54
12	SH Simona Halep	24.5%	92.8	70
13	Sara Sorribes Tormo	24.2%	92.1	188
14	Mirra Andreeva#5	23.9%	91.4	181
15	MV Marketa Vondrousova#140	23.9%	90.8	145
16	Caty McNally	23.7%	90.1	154
17	Coco Gauff#4	23.6%	89.5	316
18	Cristina Bucsa#40	23.6%	88.8	186
19	Diana Shnaider#17	23.3%	88.2	202
20	Emma Navarro#28	23.2%	87.5	210
21	Anastasia Zakharova#99	23.1%	86.8	177
22	Elise Mertens#24	23.1%	86.2	250
23	Suzan Lamens#148	22.8%	85.5	165
24	VA Victoria Azarenka	22.4%	84.9	150
25	AP Anastasia Pavlyuchenkova	22.4%	84.2	125
26	Erika Andreeva	22.2%	83.6	136
27	MB Mirjam Bjorklund	22.2%	82.9	33
28	Daria Kasatkina#61	21.7%	82.2	276
29	Heather Watson	21.7%	81.6	130
30	Tatjana Maria#80	21.6%	80.9	254
31	JN Jule Niemeier	21.5%	80.3	172
32	Katie Volynets#91	21.3%	79.6	206
33	SE Sara Errani	21.3%	78.9	84
34	Sorana Cirstea#18	21.0%	78.3	221
35	BF Brenda Fruhvirtova	20.9%	77.6	41
36	Nao Hibino	20.8%	77.0	172
37	Marie Bouzkova#25	20.8%	76.3	235
38	Emma Raducanu#49	20.8%	75.7	156
39	Madison Keys#23	20.7%	75.0	228
40	Zeynep Sonmez#52	20.6%	74.3	161
41	Renata Zarazua#73	20.3%	73.7	186
42	Dalma Galfi	20.3%	73.0	181
43	Jessica Bouzas Maneiro#63	20.3%	72.4	170
44	VT Viktoriya Tomova	20.1%	71.7	166
45	MS Marina Stakusic#145	20.0%	71.1	112
46	Yulia Putintseva#82	19.8%	70.4	254
47	Jelena Ostapenko#29	19.8%	69.7	241
48	Emiliana Arango#97	19.8%	69.1	156
49	Harriet Dart#144	19.7%	68.4	198
50	Qinwen Zheng	19.7%	67.8	213

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.
The denominator is sets, not matches. It is 6-0 sets over sets WON, so it does not reward whoever plays more. The minimum is applied to matches with a recorded score, because the count of sets won is not stored as its own column.
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.