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›Elo power ranking

Elo power ranking

Strength adjusted for who you beat, not for how many points a tournament happened to award. The rating our own predictions are built on.

ATPWTA
TourChallenger / ITF
Mirra Andreeva
Leader

RUSMirra Andreeva

2016 Elo points

Average
1623
Std. dev.
143
Leader sits at
2.7σ
Range
1379 … 2016
149 players
#PlayerValuevs tour averagePctlSample
1
Mirra Andreeva
RUSMirra Andreeva#5
2016100.0185
2
Marta Kostyuk
UKRMarta Kostyuk#11
201499.3287
3
Iga Swiatek
POLIga Swiatek#8
199498.6453
4
Aryna Sabalenka
BLRAryna Sabalenka#1
197598.0569
5
Elina Svitolina
UKRElina Svitolina#9
196997.3705
6
Linda Noskova
CZELinda Noskova#7
195996.6202
7
Karolina Muchova
CZEKarolina Muchova#6
195295.9271
8
Coco Gauff
USACoco Gauff#4
193795.3400
9
Elena Rybakina
KAZElena Rybakina#2
192694.6443
10
Jessica Pegula
USAJessica Pegula#3
191893.9447
11
Naomi Osaka
JPNNaomi Osaka#13
190093.2389
12
Belinda Bencic
SUIBelinda Bencic#14
188192.6541
13
Sorana Cirstea
ROMSorana Cirstea#18
186891.9750
14
Alexandra Eala
PHIAlexandra Eala#20
186591.2206
15
Diana Shnaider
RUSDiana Shnaider#17
186390.5205
16
Madison Keys
USAMadison Keys#23
184989.9599
17
Anna Kalinskaya
RUSAnna Kalinskaya#21
182389.2275
18
Amanda Anisimova
USAAmanda Anisimova#10
180688.5288
19
Iva Jovic
USAIva Jovic#16
180587.8146
20
Barbora Krejcikova
CZEBarbora Krejcikova#26
179487.2292
21
Marie Bouzkova
CZEMarie Bouzkova#25
177586.5320
22
Hailey Baptiste
USAHailey Baptiste#32
176485.8187
23
Elise Mertens
BELElise Mertens#24
176085.1538
24
Emma Navarro
USAEmma Navarro#28
175484.5220
25
MV
CZEMarketa Vondrousova#140
174883.8288
26
Jasmine Paolini
ITAJasmine Paolini#15
174083.1340
27
Anastasia Potapova
AUTAnastasia Potapova#27
173882.4310
28
Karolina Pliskova
CZEKarolina Pliskova#66
173581.8694
29
Maria Sakkari
GREMaria Sakkari#33
173481.1512
30
Caty McNally
USACaty McNally
173080.4191
31
XW
Xiyu Wang
171779.7245
32
Liudmila Samsonova
RUSLiudmila Samsonova#55
171579.1304
33
Sonay Kartal
GBRSonay Kartal#124
171478.4131
34
Paula Badosa
ESPPaula Badosa#84
170377.7306
35
Taylor Townsend
USATaylor Townsend#110
170177.0194
36
Ekaterina Alexandrova
RUSEkaterina Alexandrova#19
170076.4450
37
Diane Parry
FRADiane Parry#64
169575.7193
38
Viktorija Golubic
SUIViktorija Golubic#51
169475.0360
39
Sara Bejlek
CZESara Bejlek#38
168974.3128
40
Jaqueline Cristian
ROMJaqueline Cristian#39
167673.6217
41
Katerina Siniakova
CZEKaterina Siniakova#37
166973.0513
42
Jelena Ostapenko
LATJelena Ostapenko#29
166772.3544
43
Elena-Gabriela Ruse
ROMElena-Gabriela Ruse#77
166571.6145
44
Donna Vekic
CRODonna Vekic#35
166370.9520
45
Leylah Fernandez
CANLeylah Fernandez#34
166370.3300
46
Qinwen Zheng
CHNQinwen Zheng
166369.6224
47
Ashlyn Krueger
USAAshlyn Krueger#58
166368.9169
48
Zeynep Sonmez
TURZeynep Sonmez#52
165468.2164
49
Peyton Stearns
USAPeyton Stearns#57
165267.6163
50
Camila Osorio
COLCamila Osorio#60
165166.9256

How this is calculated

  • Minimum 20 rated matches. 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. The full match history with time decay, so a rating earned three years ago no longer counts as today. Retired players drop out: the list is built from those who have played since 2024.
  • 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.