Comebacks — full ATP & WTA ranking

Leader

Eliessa Vanlangendonck

47.8% of matches won after losing the first set

Average: 15.6%
Std. dev.: 8.1
Leader sits at: 4.0σ
Range: 0.0 … 47.8

1135 players

#	Player	Value	Pctl	Sample
1	EV Eliessa Vanlangendonck	47.8%	100.0	23
2	GC Georgia Andreea Craciun	47.6%	99.9	42
3	Elizara Yaneva	41.2%	99.8	34
4	NF Nada Fouad	40.0%	99.7	25
5	RJ Renáta Jamrichová	39.5%	99.6	38
6	Alina Korneeva#89	38.8%	99.6	49
7	Laura Samson#123	38.8%	99.5	49
8	DP Dasha Plekhanova	38.1%	99.4	21
9	PC Patcharin Cheapchandej	37.5%	99.3	24
10	Victoria Mboko#12	37.3%	99.2	59
11	Luisina Giovannini	37.2%	99.1	43
12	KK Kristina Kroitor	37.0%	99.0	27
13	AT Alice Tubello	37.0%	98.9	46
14	KN Kayo Nishimura	37.0%	98.9	46
15	DK Daria Khomutsianskaya	36.4%	98.8	33
16	Tyra Caterina Grant	35.9%	98.7	39
17	Oleksandra Oliynykova#44	35.8%	98.6	67
18	JD Jenny Duerst	35.7%	98.5	42
19	Tereza Valentova#67	35.6%	98.4	45
20	CN Clervie Ngounoue	35.0%	98.3	40
21	Darya Astakhova	34.5%	98.2	29
22	MB Marie Benoit	34.4%	98.1	32
23	KK Katarina Kuzmova	34.3%	98.1	70
24	Darja Vidmanova#92	34.3%	98.0	35
25	Julie Struplova	34.0%	97.9	53
26	LE Lidia Encheva	33.9%	97.8	56
27	Dayeon Back	33.9%	97.7	62
28	FC Fiona Crawley	33.3%	97.6	39
29	CH Caijsa Wilda Hennemann	33.3%	97.5	33
30	Jeline Vandromme#132	33.3%	97.4	27
31	Hanyu Guo	32.6%	97.4	46
32	JG Joanna Garland	32.6%	97.3	43
33	Mananchaya Sawangkaew#109	32.4%	97.2	68
34	KD Katy Dunne	32.3%	97.1	31
35	AF Anna Lena Friedsam	31.9%	97.0	69
36	AG Ariana Geerlings	31.8%	96.9	44
37	IB Irina Begu	31.8%	96.8	22
38	LB Linea Bajraliu	31.8%	96.7	22
39	AR Anna Sinclair Rogers	31.7%	96.6	82
40	POCCarol Young Suh Lee	31.7%	96.6	41
41	Lilli Tagger#46	31.7%	96.5	41
42	Kaitlin Quevedo#94	31.3%	96.4	67
43	LC Lourdes Carle	31.3%	96.3	64
44	Emerson Jones#134	31.3%	96.2	48
45	Lois Boisson	31.3%	96.1	32
46	Julia Riera	30.8%	96.0	65
47	RD Rositsa Dencheva	30.6%	95.9	36
48	AK Adithya Karunaratne	30.4%	95.9	23
49	Julieta Pareja	30.4%	95.8	23
50	ME Monika Ekstrand	30.4%	95.7	23

How this is calculated

Minimum 20 matches after losing 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

Eliessa Vanlangendonck

47.8% of matches won after losing the first set

Average: 15.6%
Std. dev.: 8.1
Leader sits at: 4.0σ
Range: 0.0 … 47.8

1135 players

#	Player	Value	Pctl	Sample
1	EV Eliessa Vanlangendonck	47.8%	100.0	23
2	GC Georgia Andreea Craciun	47.6%	99.9	42
3	Elizara Yaneva	41.2%	99.8	34
4	NF Nada Fouad	40.0%	99.7	25
5	RJ Renáta Jamrichová	39.5%	99.6	38
6	Alina Korneeva#89	38.8%	99.6	49
7	Laura Samson#123	38.8%	99.5	49
8	DP Dasha Plekhanova	38.1%	99.4	21
9	PC Patcharin Cheapchandej	37.5%	99.3	24
10	Victoria Mboko#12	37.3%	99.2	59
11	Luisina Giovannini	37.2%	99.1	43
12	KK Kristina Kroitor	37.0%	99.0	27
13	AT Alice Tubello	37.0%	98.9	46
14	KN Kayo Nishimura	37.0%	98.9	46
15	DK Daria Khomutsianskaya	36.4%	98.8	33
16	Tyra Caterina Grant	35.9%	98.7	39
17	Oleksandra Oliynykova#44	35.8%	98.6	67
18	JD Jenny Duerst	35.7%	98.5	42
19	Tereza Valentova#67	35.6%	98.4	45
20	CN Clervie Ngounoue	35.0%	98.3	40
21	Darya Astakhova	34.5%	98.2	29
22	MB Marie Benoit	34.4%	98.1	32
23	KK Katarina Kuzmova	34.3%	98.1	70
24	Darja Vidmanova#92	34.3%	98.0	35
25	Julie Struplova	34.0%	97.9	53
26	LE Lidia Encheva	33.9%	97.8	56
27	Dayeon Back	33.9%	97.7	62
28	FC Fiona Crawley	33.3%	97.6	39
29	CH Caijsa Wilda Hennemann	33.3%	97.5	33
30	Jeline Vandromme#132	33.3%	97.4	27
31	Hanyu Guo	32.6%	97.4	46
32	JG Joanna Garland	32.6%	97.3	43
33	Mananchaya Sawangkaew#109	32.4%	97.2	68
34	KD Katy Dunne	32.3%	97.1	31
35	AF Anna Lena Friedsam	31.9%	97.0	69
36	AG Ariana Geerlings	31.8%	96.9	44
37	IB Irina Begu	31.8%	96.8	22
38	LB Linea Bajraliu	31.8%	96.7	22
39	AR Anna Sinclair Rogers	31.7%	96.6	82
40	POCCarol Young Suh Lee	31.7%	96.6	41
41	Lilli Tagger#46	31.7%	96.5	41
42	Kaitlin Quevedo#94	31.3%	96.4	67
43	LC Lourdes Carle	31.3%	96.3	64
44	Emerson Jones#134	31.3%	96.2	48
45	Lois Boisson	31.3%	96.1	32
46	Julia Riera	30.8%	96.0	65
47	RD Rositsa Dencheva	30.6%	95.9	36
48	AK Adithya Karunaratne	30.4%	95.9	23
49	Julieta Pareja	30.4%	95.8	23
50	ME Monika Ekstrand	30.4%	95.7	23

How this is calculated

Minimum 20 matches after losing 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.