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›Deciding sets

Deciding sets

Final sets won. Fitness, nerve and the ability to keep serving at the end of a long afternoon.

ATPWTA
TourChallenger / ITF
Carlos Alcaraz
Leader

ESPCarlos Alcaraz

82.5% of deciding sets won

Average
53.4%
Std. dev.
9.3
Leader sits at
3.1σ
Range
36.4 … 82.5
132 players
#PlayerValuevs tour averagePctlSample
1
Carlos Alcaraz
ESPCarlos Alcaraz#2
82.5%100.0137
2
Jannik Sinner
ITAJannik Sinner#1
79.7%99.2148
3
Novak Djokovic
SERNovak Djokovic#5
77.5%98.5111
4
Felix Auger-Aliassime
CANFelix Auger-Aliassime#4
73.9%97.746
5
Learner Tien
USALearner Tien#19
72.0%96.982
6
RN
ESPRafael Nadal
71.9%96.232
7
Alexander Zverev
GERAlexander Zverev#3
70.8%95.4154
8
KN
JPNKei Nishikori
70.6%94.734
9
Grigor Dimitrov
BULGrigor Dimitrov#137
68.6%93.9102
10
Casper Ruud
NORCasper Ruud#14
68.2%93.1110
11
Stefanos Tsitsipas
GREStefanos Tsitsipas#53
66.1%92.4118
12
Camilo Ugo Carabelli
ARGCamilo Ugo Carabelli#76
65.7%91.670
13
NK
AUSNick Kyrgios
65.2%90.823
14
Jacob Fearnley
GBRJacob Fearnley#110
64.7%90.151
15
Taylor Fritz
USATaylor Fritz#8
64.6%89.3147
16
Daniil Medvedev
RUSDaniil Medvedev#6
64.6%88.5130
17
Flavio Cobolli
ITAFlavio Cobolli#9
64.3%87.884
18
Tommy Paul
USATommy Paul#21
63.1%87.0141
19
Cameron Norrie
GBRCameron Norrie#37
62.9%86.3143
20
Lorenzo Musetti
ITALorenzo Musetti#13
62.9%85.5116
21
Luciano Darderi
ITALuciano Darderi#22
62.7%84.767
22
Reilly Opelka
USAReilly Opelka#142
62.3%84.053
23
Alex de Minaur
AUSAlex de Minaur#7
62.1%83.2140
24
Frances Tiafoe
USAFrances Tiafoe#20
61.7%82.4133
25
Tomas Machac
CZETomas Machac#58
61.6%81.773
26
DS
ARGDiego Schwartzman
61.3%80.962
27
Matteo Berrettini
ITAMatteo Berrettini#40
61.3%80.280
28
Arthur Fils
FRAArthur Fils#24
61.1%79.454
29
Wu Yibing
CHNWu Yibing#116
60.5%78.643
30
Alexander Bublik
KAZAlexander Bublik#11
60.0%77.9120
31
Damir Dzumhur
BIHDamir Dzumhur#104
59.7%77.172
32
Andrey Rublev
RUSAndrey Rublev#16
59.2%76.3142
33
TK
AUSThanasi Kokkinakis
59.1%75.666
34
Valentin Vacherot
MONValentin Vacherot#18
59.0%74.861
35
Nuno Borges
PORNuno Borges#55
58.4%74.089
36
HR
DENHolger Rune#99
58.3%73.3108
37
Yannick Hanfmann
GERYannick Hanfmann#57
58.3%72.584
38
AV
ITAAndrea Vavassori
58.3%71.824
39
Ben Shelton
USABen Shelton#10
58.3%71.0115
40
Jakub Mensik
CZEJakub Mensik#17
58.0%70.281
41
Rinky Hijikata
AUSRinky Hijikata#93
58.0%69.581
42
Joao Fonseca
BRAJoao Fonseca#27
58.0%68.769
43
Ethan Quinn
USAEthan Quinn#51
57.9%67.976
44
Hubert Hurkacz
POLHubert Hurkacz#72
57.9%67.2140
45
Jack Draper
GBRJack Draper#143
57.6%66.466
46
Hamad Medjedovic
SERHamad Medjedovic#73
57.4%65.654
47
SK
USASebastian Korda#50
57.3%64.996
48
DT
AUTDominic Thiem
55.8%64.143
49
Marin Cilic
CROMarin Cilic#85
55.7%63.470
50
Arthur Cazaux
FRAArthur Cazaux#138
55.3%62.647

How this is calculated

  • Minimum 20 deciding sets played. 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 →Comebacks →Closing out →