TennisRaptorTennisRaptor
HomeMatchesPlayersPredictionsEditorialModelRankingsStats
Compare Players
TennisRaptor

Professional tennis stats, rankings, and data.

Tennis

Live scoresPlayersRankingsTournamentsDrawsNews

Predictions

AI predictionsModel recordOddsCompare players

Statistics

All rankingsElo power rankingBest serversSurface kingsCourt speedMatch length

Site

AboutContactPrivacyTerms

© 2026 TennisRaptor.com. Data sourced from ATP and WTA official sources.

TennisRaptor.com is an independent statistics platform. Not affiliated with ATP or WTA.

Forecasts are statistical models, not betting advice. 18+. Gamble responsibly.

Home›Stats›Comebacks

Comebacks

Matches won after losing the first set. Counted only over matches where the first set was actually lost — the denominator nobody publishes.

ATPWTA
TourChallenger / ITF
Jannik Sinner
Leader

ITAJannik Sinner

56.1% of matches won after losing the first set

Average
23.9%
Std. dev.
8.0
Leader sits at
4.0σ
Range
8.3 … 56.1
132 players
#PlayerValuevs tour averagePctlSample
1
Jannik Sinner
ITAJannik Sinner#1
56.1%100.066
2
Novak Djokovic
SERNovak Djokovic#5
52.2%99.267
3
Carlos Alcaraz
ESPCarlos Alcaraz#2
50.0%98.574
4
Felix Auger-Aliassime
CANFelix Auger-Aliassime#4
41.3%97.746
5
NK
AUSNick Kyrgios
40.7%96.927
6
Valentin Vacherot
MONValentin Vacherot#18
38.5%96.265
7
Alexander Zverev
GERAlexander Zverev#3
38.3%95.4120
8
Matteo Berrettini
ITAMatteo Berrettini#40
38.2%94.776
9
Learner Tien
USALearner Tien#19
36.5%93.974
10
RN
ESPRafael Nadal
36.4%93.122
11
Ben Shelton
USABen Shelton#10
34.9%92.4109
12
Frances Tiafoe
USAFrances Tiafoe#20
33.9%91.6127
13
TK
AUSThanasi Kokkinakis
33.3%90.860
14
Daniil Medvedev
RUSDaniil Medvedev#6
32.7%90.1110
15
Hubert Hurkacz
POLHubert Hurkacz#72
32.7%89.398
16
Alejandro Tabilo
CHIAlejandro Tabilo#26
32.3%88.596
17
Taylor Fritz
USATaylor Fritz#8
32.2%87.8118
18
HR
DENHolger Rune#99
31.4%87.0105
19
GZ
ITAGiulio Zeppieri
31.3%86.348
20
Andrey Rublev
RUSAndrey Rublev#16
31.1%85.5132
21
Sebastian Ofner
AUTSebastian Ofner#126
30.2%84.786
22
KN
JPNKei Nishikori
30.0%84.030
23
Jacob Fearnley
GBRJacob Fearnley#110
29.6%83.271
24
Joao Fonseca
BRAJoao Fonseca#27
29.2%82.465
25
Jack Draper
GBRJack Draper#143
29.0%81.762
26
GM
FRAGael Monfils
29.0%80.969
27
Francisco Cerundolo
ARGFrancisco Cerundolo#23
28.7%80.2129
28
Karen Khachanov
RUSKaren Khachanov#39
28.6%79.4119
29
Tommy Paul
USATommy Paul#21
28.6%78.6112
30
Camilo Ugo Carabelli
ARGCamilo Ugo Carabelli#76
28.6%77.998
31
Cristian Garin
CHICristian Garin#136
27.9%77.1111
32
Juncheng Shang
CHNJuncheng Shang
27.9%76.343
33
Matteo Arnaldi
ITAMatteo Arnaldi#35
27.7%75.683
34
Alex de Minaur
AUSAlex de Minaur#7
27.7%74.8130
35
Nuno Borges
PORNuno Borges#55
27.7%74.0130
36
AM
GBRAndy Murray
27.7%73.365
37
Tallon Griekspoor
NEDTallon Griekspoor#69
27.5%72.5120
38
Wu Yibing
CHNWu Yibing#116
27.3%71.855
39
Lorenzo Musetti
ITALorenzo Musetti#13
27.0%71.0141
40
Grigor Dimitrov
BULGrigor Dimitrov#137
26.9%70.293
41
Casper Ruud
NORCasper Ruud#14
26.7%69.5120
42
Mariano Navone
ARGMariano Navone#44
26.6%68.779
43
DT
AUTDominic Thiem
26.6%67.964
44
DK
GERDominik Koepfer
26.4%67.253
45
Arthur Fils
FRAArthur Fils#24
26.4%66.472
46
Ethan Quinn
USAEthan Quinn#51
26.3%65.695
47
Stefanos Tsitsipas
GREStefanos Tsitsipas#53
26.2%64.9122
48
Gabriel Diallo
CANGabriel Diallo#108
25.9%64.185
49
Alexander Bublik
KAZAlexander Bublik#11
25.7%63.4144
50
Quentin Halys
FRAQuentin Halys#54
25.7%62.6109

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.

Related rankings

Break points saved →Tiebreak record →Deciding sets →Closing out →