Break percentage — full ATP & WTA ranking

Leader

Mariano Navone

33.7% of return games broken

Average: 23.3%
Std. dev.: 3.7
Leader sits at: 2.8σ
Range: 12.4 … 33.7

121 players

#	Player	Value	Pctl	Sample
1	Mariano Navone#44	33.7%	100.0	114
2	Jannik Sinner#1	32.5%	99.2	98
3	Carlos Alcaraz#2	31.0%	98.3	102
4	Francisco Cerundolo#23	30.1%	97.5	89
5	Cristian Garin#136	29.8%	96.7	112
6	KN Kei Nishikori	29.7%	95.8	43
7	Vit Kopriva#71	29.6%	95.0	156
8	Damir Dzumhur#104	29.4%	94.2	152
9	FF Fabio Fognini	29.0%	93.3	54
10	Camilo Ugo Carabelli#76	28.9%	92.5	161
11	Wu Yibing#116	28.4%	91.7	67
12	Sebastian Baez#48	28.2%	90.8	75
13	Alex de Minaur#7	28.0%	90.0	103
14	Daniil Medvedev#6	27.8%	89.2	95
15	Roberto Carballes Baena	27.3%	88.3	75
16	Learner Tien#19	27.3%	87.5	137
17	Jesper de Jong#105	26.8%	86.7	146
18	Jacob Fearnley#110	26.8%	85.8	110
19	Marton Fucsovics#83	26.7%	85.0	85
20	Pablo Carreno Busta#68	26.6%	84.2	94
21	SERNovak Djokovic#5	26.6%	83.3	58
22	YN Yoshihito Nishioka	26.6%	82.5	57
23	Tommy Paul#21	26.6%	81.7	73
24	Corentin Moutet#59	26.3%	80.8	109
25	DG David Goffin	26.3%	80.0	88
26	Luciano Darderi#22	26.3%	79.2	113
27	Hugo Gaston#96	26.2%	78.3	110
28	Lorenzo Musetti#13	26.1%	77.5	88
29	RG Richard Gasquet	26.1%	76.7	60
30	Pedro Martinez#148	26.0%	75.8	94
31	Alejandro Davidovich Fokina#25	25.8%	75.0	88
32	SERDusan Lajovic#149	25.7%	74.2	94
33	Zachary Svajda#87	25.6%	73.3	138
34	DE Daniel Evans	25.6%	72.5	60
35	Jaume Munar#45	25.5%	71.7	93
36	Botic Van De Zandschulp#70	25.5%	70.8	98
37	Jack Draper#143	25.5%	70.0	43
38	Juncheng Shang	25.1%	69.2	41
39	Luca Nardi	25.1%	68.3	117
40	Denis Shapovalov#43	24.9%	67.5	72
41	BC Borna Coric	24.8%	66.7	56
42	SERHamad Medjedovic#73	24.6%	65.8	106
43	Arthur Fils#24	24.5%	65.0	60
44	Rinky Hijikata#93	24.4%	64.2	126
45	Valentin Vacherot#18	24.4%	63.3	127
46	Mackenzie McDonald#144	24.4%	62.5	118
47	Casper Ruud#14	24.3%	61.7	79
48	HR Holger Rune#99	24.2%	60.8	49
49	Joao Fonseca#27	24.2%	60.0	111
50	Thiago Seyboth Wild	24.1%	59.2	75

How this is calculated

Minimum 30 matches with serve statistics. 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. Every match since 2024 — that is where serve statistics begin in this database; before that there are none.
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

Mariano Navone

33.7% of return games broken

Average: 23.3%
Std. dev.: 3.7
Leader sits at: 2.8σ
Range: 12.4 … 33.7

121 players

#	Player	Value	Pctl	Sample
1	Mariano Navone#44	33.7%	100.0	114
2	Jannik Sinner#1	32.5%	99.2	98
3	Carlos Alcaraz#2	31.0%	98.3	102
4	Francisco Cerundolo#23	30.1%	97.5	89
5	Cristian Garin#136	29.8%	96.7	112
6	KN Kei Nishikori	29.7%	95.8	43
7	Vit Kopriva#71	29.6%	95.0	156
8	Damir Dzumhur#104	29.4%	94.2	152
9	FF Fabio Fognini	29.0%	93.3	54
10	Camilo Ugo Carabelli#76	28.9%	92.5	161
11	Wu Yibing#116	28.4%	91.7	67
12	Sebastian Baez#48	28.2%	90.8	75
13	Alex de Minaur#7	28.0%	90.0	103
14	Daniil Medvedev#6	27.8%	89.2	95
15	Roberto Carballes Baena	27.3%	88.3	75
16	Learner Tien#19	27.3%	87.5	137
17	Jesper de Jong#105	26.8%	86.7	146
18	Jacob Fearnley#110	26.8%	85.8	110
19	Marton Fucsovics#83	26.7%	85.0	85
20	Pablo Carreno Busta#68	26.6%	84.2	94
21	SERNovak Djokovic#5	26.6%	83.3	58
22	YN Yoshihito Nishioka	26.6%	82.5	57
23	Tommy Paul#21	26.6%	81.7	73
24	Corentin Moutet#59	26.3%	80.8	109
25	DG David Goffin	26.3%	80.0	88
26	Luciano Darderi#22	26.3%	79.2	113
27	Hugo Gaston#96	26.2%	78.3	110
28	Lorenzo Musetti#13	26.1%	77.5	88
29	RG Richard Gasquet	26.1%	76.7	60
30	Pedro Martinez#148	26.0%	75.8	94
31	Alejandro Davidovich Fokina#25	25.8%	75.0	88
32	SERDusan Lajovic#149	25.7%	74.2	94
33	Zachary Svajda#87	25.6%	73.3	138
34	DE Daniel Evans	25.6%	72.5	60
35	Jaume Munar#45	25.5%	71.7	93
36	Botic Van De Zandschulp#70	25.5%	70.8	98
37	Jack Draper#143	25.5%	70.0	43
38	Juncheng Shang	25.1%	69.2	41
39	Luca Nardi	25.1%	68.3	117
40	Denis Shapovalov#43	24.9%	67.5	72
41	BC Borna Coric	24.8%	66.7	56
42	SERHamad Medjedovic#73	24.6%	65.8	106
43	Arthur Fils#24	24.5%	65.0	60
44	Rinky Hijikata#93	24.4%	64.2	126
45	Valentin Vacherot#18	24.4%	63.3	127
46	Mackenzie McDonald#144	24.4%	62.5	118
47	Casper Ruud#14	24.3%	61.7	79
48	HR Holger Rune#99	24.2%	60.8	49
49	Joao Fonseca#27	24.2%	60.0	111
50	Thiago Seyboth Wild	24.1%	59.2	75

How this is calculated

Minimum 30 matches with serve statistics. 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. Every match since 2024 — that is where serve statistics begin in this database; before that there are none.
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.