⌘K
Log in
Home Tip of the day Bet Builder
Tournaments
ATP WTA Challenger ITF View all →
Progress How it works Blog Pricing
Odds Format
Log in Register

Wednesday, November 4

Tennis
Predictions

Tennis tips and predictions for today's full schedule, from ATP and WTA to Challenger and ITF: the AI model's pick, the odds and its confidence, with every pick graded after the match.

Tip of the day Progress
81% Bankers win rate From 2,555 graded picks
241 Matches predicted today ATP, WTA, Challenger, ITF
2/3 Free picks won yesterday graded on the final score
81%

Bankers win rate

From 2,555 graded picks

241 Matches predicted today

Sort by

Today's free picks

8
02:00 Finished 0200
KR B. Jeong
CN Y. Ma
2 0
4.4 1.14
2 1.14
2626
U20.5 ▾1.55
6.7/10
03:00 Upcoming 0300
CN H. Shi
JP S. Hosogi
–
▴1.11 ▾5.8
1 ▴1.11
6264
1 ▴1.11
7.0/10
S2 S2
RU Y. Demin
FR A. Muller
00 11
▾2.48 ▴1.53
1 ▾2.48
6463
O19.5 ▴1.47
1.0/10
04:30 Upcoming 0430
CN Y. Ren
KR Y. Ku
–
▾3.1 ▴1.33
2 ▴1.33
633626
O18.5 1.52
7.2/10
06:00 Upcoming 0600
HR A. Ružić
AM A. Charaeva
–
▾1.84 ▴1.97
2 ▴1.97
466326
U28.5 ▾1.26
5.1/10
12:20 Upcoming 1220
PE I. Buse
RU D. Medvedev (4)
–
▾6 ▴1.15
1 ▾6
266364
U26.5 ▴1.27
1.0/10
12:30 Upcoming 1230
DE A. Zverev (1)
IT L. Musetti
–
▴1.45 3.1
1 ▴1.45
7664
U29.5 1.28
4.0/10
16:10 Upcoming 1610
CA L. Draxl
PL M. Kaśnikowski
–
▴1.82 ▴1.95
2 ▴1.95
366436
O20.5 1.52
2.7/10

Predictions are locked without a subscription, but you can subscribe when you're ready!

Paris, France Hard ATP - Paris, France (Hard) 14
10:00 Upcoming 1000
IT M. Bellucci (Q)
FR A. Rinderknech
–
▾1.75 ▴2.16
4.7/10
10:00 Upcoming 1000
FR Q. Halys
US F. Tiafoe (7)
–
▴2.22 ▾1.68
4.8/10
11:10 Upcoming 1110
FR L. Van Assche
US L. Tien (15)
–
▾2.7 ▴1.52
4.5/10
11:30 Upcoming 1130
US T. Paul (12)
ES D. Mérida
–
▾1.25 ▴4.1
4.8/10
12:20 Upcoming 1220
PE I. Buse
RU D. Medvedev (4)
–
▾6 ▴1.15
1 ▾6
266364
U26.5 ▴1.27
1.0/10
12:30 Upcoming 1230
DE A. Zverev (1)
IT L. Musetti
–
▴1.45 3.1
1 ▴1.45
7664
U29.5 1.28
4.0/10
12:40 Upcoming 1240
AR T. Etcheverry
AU A. de Minaur (8)
–
▴4.6 ▾1.23
6.9/10
13:40 Upcoming 1340
RS N. Djokovic (10)
AU R. Hijikata (Q)
–
▴1.27 ▾4
5.1/10
13:50 Upcoming 1350
SK A. Molčan (Q)
US T. Fritz (11)
–
▴4.2 ▾1.24
3.3/10
14:30 Upcoming 1430
PT N. Borges (LL)
RU K. Khachanov
–
2.77 1.5
4.2/10
15:00 Upcoming 1500
AR T. Tirante
DE J. Struff
–
▴2.8 ▾1.45
5.1/10
15:40 Upcoming 1540
IT M. Berrettini
FR U. Humbert
–
2.06 1.85
4.5/10
18:00 Upcoming 1800
US A. Michelsen
ES C. Alcaraz (2)
–
▴5.2 ▾1.17
9.1/10
19:30 Upcoming 1930
FR A. Fils (6)
CZ T. Machač (Q)
–
▴1.54 ▾2.6
8.9/10
Cali, Colombia Clay WTA - Cali, Colombia (Clay) 2
16:00 Upcoming 1600
FR L. Jeanjean (1)
BR C. Alves (Q)
–
▾1.23 ▴4
4.6/10
19:10 Upcoming 1910
ES L. Romero
AR S. Sierra (3)
–
▴1.9 ▾1.87
1.5/10
Chennai, India Hard WTA - Chennai, India (Hard) 4
09:30 Upcoming 0930
ES O. Selekhmeteva
UZ P. Kudermetova (6)
–
▾2.22 ▴1.68
3.8/10
09:30 Upcoming 0930
US R. Montgomery
BE J. Vandromme
–
▴1.7 ▾2.27
3.9/10
10:40 Upcoming 1040
ID J. Tjen (1)
TW J. Garland
–
▾1.42 ▴2.92
3.8/10
11:50 Upcoming 1150
PL W. Falkowska (Q)
IN M. R. Revathi (WC)
–
▴1.58 ▾2.55
7.4/10
Hong Kong, Hong Kong Hard WTA - Hong Kong, Hong Kong (Hard) 5
06:00 Upcoming 0600
HR A. Ružić
AM A. Charaeva
–
▾1.84 ▴1.97
2 ▴1.97
466326
U28.5 ▾1.26
5.1/10
06:00 Upcoming 0600
CA L. Fernandez
US S. Kenin
–
▾1.3 ▴3.6
10.0/10
07:10 Upcoming 0710
US C. Liu
GB K. Boulter (8)
–
2.38 1.7
1.3/10
07:10 Upcoming 0710
AU T. Gibson (5)
BY A. Sasnovich (Q)
–
▴2.55 ▾1.52
2.1/10
10:30 Upcoming 1030
AU M. Joint
GR M. Sakkari (4)
–
▴2.75 ▴1.55
6.5/10
Luanda, Angola Hard WTA - Luanda, Angola (Hard) 6
09:00 Upcoming 0900
RU S. Lansere (8)
SI K. Novak
–
▾1.1 ▴6.25
10.0/10
10:10 Upcoming 1010
NL S. Lamens
RU K. Kroitor
–
▴1.11 ▾6.1
5.2/10
10:10 Upcoming 1010
ZA W. Mdlulwa
DE N. Noha Akugue
–
▴15 ▾1.03
1.5/10
11:20 Upcoming 1120
DE F. Sziedat (Q)
PL M. Kubka (3)
–
▴13 ▾1.03
8.0/10
11:20 Upcoming 1120
BG I. Shinikova
PL G. Feistel
–
▴2.7 ▾1.45
4.6/10
15:30 Upcoming 1530
FR D. Martynov
MA Y. Kabbaj (6)
–
▾2.65 ▴1.45
5.5/10
Bratislava 2, Slovakia Hard Challenger - Bratislava 2, Slovakia (Hard) 7
10:00 Upcoming 1000
UA V. Sachko
FI O. Virtanen
–
▴3 ▾1.38
3.9/10
13:00 Upcoming 1300
US M. Damm Jr
DE T. Gentzsch
–
▴1.27 ▾3.6
10.0/10
14:10 Upcoming 1410
HR M. Dodig
SK M. Krajči
–
1.09 7
10.0/10
14:40 Upcoming 1440
FR S. Gueymard
HU Z. Piros (3)
–
▴1.87 ▾1.89
1.8/10
15:50 Upcoming 1550
CH J. Kym
FR L. Pavlović
–
▾1.24 ▴4
4.6/10
16:00 Upcoming 1600
SK L. Pokorny
GB T. Samuel
–
▴5 1.16
8.0/10
17:10 Upcoming 1710
US N. Basavareddy (9)
CH M. Brunold (A)
–
▾1.43 ▴2.88
2.9/10
Charlottesville, USA Hard Challenger - Charlottesville, USA (Hard) 5
16:10 Upcoming 1610
CA L. Draxl
PL M. Kaśnikowski
–
▴1.82 ▴1.95
2 ▴1.95
366436
O20.5 1.52
2.7/10
16:10 Upcoming 1610
US M. Cassone
US S. Kozlov
–
1.75 1.97
3.1/10
17:20 Upcoming 1720
US B. Shick
US D. Blanch (6)
–
▴2.57 ▾1.44
6.0/10
18:30 Upcoming 1830
US M. Giron (1)
CA J. Boulais (Q)
–
1.25 3.5
2.8/10
19:40 Upcoming 1940
US J. Kennedy
FR C. Chidekh (5)
–
▴5.1 ▾1.13
5.2/10
Costa do Sauipe Clay Challenger - Costa do Sauipe (Clay) 3
00:15 Finished 0015
BR T. Wild
BR F. Meligeni
2 0
▴1.33 ▾3.2
1 ▴1.33
6264
1 ▴1.33
3.8/10
19:30 Upcoming 1930
AR L. Midon
CL T. Barrios Vera
–
2.12 1.65
2.3/10
22:00 Upcoming 2200
BR G. Heide (5)
BO J. Prado Angelo
–
1.5 ▴2.55
6.2/10
Taipei, Chinese Taipei Hard Challenger - Taipei, Chinese Taipei (Hard) 6
02:00 Finished 0200
GB C. Broom
GB L. Broady
2 0
▴1.8 ▾2.05
1 ▴1.8
7664
O20.5 ▴1.55
2.5/10
02:00 Finished 0200
FR H. Mayot
RU P. Bar Biryukov
2 0
▾1.15 ▴4.8
1 ▾1.15
6364
1 ▾1.15
3.6/10
S1 S1
DK C. E. Overbeck
TW C. Tseng
06 06
▴2.7 ▾1.46
1.9/10
S2 S2
RU Y. Demin
FR A. Muller
00 11
▾2.48 ▴1.53
1 ▾2.48
6463
O19.5 ▴1.47
1.0/10
05:45 Upcoming 0545
CZ J. Kumstat
GB B. Harris
–
1.83 1.95
2.4/10
08:05 Upcoming 0805
JP Y. Shimizu (Q)
DK A. Holmgren
–
▾2.32 ▴1.6
2.5/10
Taranto, Italy Hard Challenger - Taranto, Italy (Hard) 5
09:00 Upcoming 0900
BG A. Andreev
IT J. Vasamì
–
▾1.68 ▴2.14
2.4/10
09:00 Upcoming 0900
GB F. Gill (6)
GB M. Walters
–
▾1.22 ▴4.8
2.5/10
09:00 Upcoming 0900
IT L. Rossi
CH R. Bertola
–
▾3.85 ▴1.26
3.4/10
09:00 Upcoming 0900
FR L. Massard
FR T. Faurel
–
▾3.75 ▴1.28
10.0/10
10:10 Upcoming 1010
IT F. Romano (WC)
HU P. Makk
–
▾1.59 ▴2.3
2.9/10
Villa Maria, Argentina Clay Challenger - Villa Maria, Argentina (Clay) 7
00:20 Finished 0020
AR F. Coria
AR I. Dreycopp
2 0
▾1.26 ▴3.8
2 ▴3.8
3646
U22.5 ▾1.6
5.1/10
14:00 Upcoming 1400
IT F. Agamenone
AR I. Monzon
–
▴1.24 ▾3.6
4.3/10
14:00 Upcoming 1400
UY J. Aguilar
AR J. Ficovich
–
▾1.32 ▴3.25
8.9/10
16:00 Upcoming 1600
AR J. La Serna (1)
AR H. Casanova
–
▾1.34 ▴2.95
10.0/10
17:10 Upcoming 1710
UY F. A. Cardozo (Q)
AR N. Kicker (8)
–
▾4.3 ▴1.2
3.9/10
17:10 Upcoming 1710
ES O. Roca Batalla (4)
JP R. Tabata (Q)
–
▾1.16 ▴5
4.2/10
22:00 Upcoming 2200
AR L. Ratti
AR C. Zarate
–
1.92 1.86
2.9/10
M15 Antalya Clay ITF Men - M15 Antalya (Clay) 11
06:30 Upcoming 0630
IT D. Augenti
AT A. Wagner
–
▴10.5 ▾1.03
5.8/10
06:30 Upcoming 0630
BE D. Tixhon
PL A. Wazny
–
▴4.8 ▾1.15
2.7/10
06:30 Upcoming 0630
DE F. Yunis
RU A. Chepelev
–
▴5.5 ▾1.12
4.8/10
06:30 Upcoming 0630
BE M. Van der
TR B. Tan
–
▴1.02 9.4
1.8/10
06:30 Upcoming 0630
RO S. H. Haita
BE A. Basile
–
▴1.58 ▾2.28
1.8/10
07:00 Upcoming 0700
IT T. Baragiola
IT M. Nannelli
–
▾1.46 ▴2.62
7.7/10
07:00 Upcoming 0700
RS V. Rađenović
RU E. Khotchenkov
–
▴1.2 ▾4.1
6.8/10
08:30 Upcoming 0830
TR C. Kucukhuseyin
FR A. Fabre
–
6.5 1.06
5.9/10
08:30 Upcoming 0830
RU D. Stepanov
IT N. Toffanin
–
▾2.62 ▴1.38
1.4/10
08:30 Upcoming 0830
DE L. Mietusch
IR A. Yazdani
–
▾3.25 ▴1.26
3.3/10
09:00 Upcoming 0900
RO F. Jianu
IT V. Dell'Elba
–
1.02 ▴9.2
6.4/10
M15 Fergana Hard ITF Men - M15 Fergana (Hard) 4
04:30 Upcoming 0430
IN D. P. Singh
BY U. Tarasevich
–
1.04 9
1.4/10
04:30 Upcoming 0430
UZ I. Ignatov
IN A. Lakshmanan
–
▾8 ▴1.05
5.6/10
06:30 Upcoming 0630
IN M. Kamath
DE D. Eichenseher
–
▾2.42 ▴1.47
4.4/10
06:30 Upcoming 0630
RU O. Kolninov
KZ G. Lomakin
–
▴4.4 ▾1.19
2.9/10
M15 Maanshan Hard ITF Men - M15 Maanshan (Hard) 12
02:00 Finished 0200
CN X. Zhou
RS B. Butulija
2 0
▴2.6 ▾1.74
2 ▾1.74
467567
2 ▾1.74
2.1/10
S2 S2
CN Y. Xia
CN W. Kong
15 02
▾1.44 ▴2.55
5.5/10
S2 S2
RU M. Zhukov
AU S. Storch
15 02
▾1.07 ▴6.9
2.6/10
S1 S1
US J. Chiu
EE K. Tamm
01 01
▾3.65 ▴1.29
6.3/10
S1 S1
IT L. Lorusso
CN T. Zhang
03 03
▴3.55 ▾1.25
7.9/10
04:30 Upcoming 0430
CN T. Rigele
JP Y. Kikuchi
–
▾1.36 2.93
6.7/10
04:30 Upcoming 0430
CN X. Yang
PL F. Peliwo
–
6.1 1.1
9.3/10
04:30 Upcoming 0430
CN Z. Yang
CN Z. Zhao
–
▾4.6 ▴1.26
3.7/10
06:21 Upcoming 0621
CN H. Ye
CN X. Han
–
▾2.35 ▴1.54
3.4/10
06:30 Upcoming 0630
RU A. Kozlov
CN Q. Sun
–
▾8 1.05
4.3/10
06:30 Upcoming 0630
CN L. Zhao
GB J. Connel
–
▾2 ▴1.75
7.1/10
06:30 Upcoming 0630
GB M. Hurrion
RU A. Aleshchev
–
▾1.02 ▴14
9.2/10
M15 Monastir Hard ITF Men - M15 Monastir (Hard) 9
08:30 Upcoming 0830
CN C. Chen
FR C. Bouchelaghem
–
▴5.2 ▾1.1
8.0/10
08:30 Upcoming 0830
HR D. Ajduković
MC R. Piatti
–
▴1.1 ▾5.2
4.9/10
08:30 Upcoming 0830
IT G. Perego
TN A. Ouakaa
–
2.23 ▾1.66
6.2/10
08:30 Upcoming 0830
DE J. Penzlin
TN A. Dougaz
–
▴4.85 ▾1.12
7.2/10
08:30 Upcoming 0830
FR N. Tepmahc
ES J. Echeverria
–
▾2.65 ▴1.44
4.1/10
08:30 Upcoming 0830
FR S. Corbinais
IT A. Bacaloni
–
▾1.95 ▴1.82
2.9/10
10:30 Upcoming 1030
CN F. Nidunjianzan
FR M. Malige
–
▾2.35 ▴1.63
2.3/10
10:30 Upcoming 1030
FR M. Rivet
DE N. Barsukov
–
▾1.94 ▴1.95
3.4/10
10:30 Upcoming 1030
TR T. Duran
DE B. Sanchez
–
3.15 1.3
4.7/10
M15 San Gregorio di Clay ITF Men - M15 San Gregorio di (Clay) 12
09:00 Upcoming 0900
IT A. Battiston
CZ S. Baum
–
▾3.1 ▴1.32
4.9/10
09:00 Upcoming 0900
IT A. De Marchi
IT L. Primucci
–
▾1.22 ▴4.1
6.0/10
09:00 Upcoming 0900
IT F. Ferrari
IT L. Rottoli
–
2.85 ▾1.4
1.7/10
09:00 Upcoming 0900
RO V. Breazu
IT M. Mecarelli
–
▴1.95 ▾1.82
2.9/10
11:00 Upcoming 1100
IT J. Berrettini
IT R. Ciurnelli
–
▴1.58 ▾2.3
3.4/10
11:00 Upcoming 1100
DE J. Sperle
IT A. Fiorentini
–
▴1.14 ▾5
2.1/10
11:00 Upcoming 1100
IT M. Serafini
IT M. Gribaldo
–
▾2.57 ▴1.44
2.7/10
11:00 Upcoming 1100
SI N. Miković
DE A. Oetzbach
–
3.35 1.28
2.9/10
13:00 Upcoming 1300
IT D. Rapagnetta
AR J. Otegui
–
▴1.23 ▾3.7
2.7/10
13:00 Upcoming 1300
IT G. Misasi
IT M. Tammaro
–
▾1.41 ▴2.58
5.5/10
13:00 Upcoming 1300
IT L. Angeloni
IT S. Massucco
–
1.95 1.83
1.9/10
13:00 Upcoming 1300
IT S. Cocola
IT G. La Vela
–
▾3.45 ▴1.38
2.2/10
M15 Sharm El Sheikh Hard ITF Men - M15 Sharm El Sheikh (Hard) 12
08:00 Upcoming 0800
EG A. Elsayed
EG M. Ehab
–
1.12 5.3
1.1/10
08:00 Upcoming 0800
MA K. Bennani
TR M. Anavatan
–
1.1 5.4
1.1/10
08:00 Upcoming 0800
FI O. Eerola
TR K. Yilmaz
–
▴4.4 ▾1.14
8.0/10
10:00 Upcoming 1000
PL J. Wygona
LU L. Van Herck
–
▴2.5 ▾1.47
4.7/10
10:00 Upcoming 1000
EG K. Ibrahim
BE P. Bailly
–
3.75 1.2
3.4/10
10:00 Upcoming 1000
TR S. M. Ozdemir
EG O. Kandil
–
▾1.95 ▴1.75
1.1/10
10:30 Upcoming 1030
FR A. Gabet
BE N. Ifi
–
▴3.65 1.26
8.0/10
10:30 Upcoming 1030
CH A. Burdet
TH W. Trongcharoench
–
▾1.85 ▴1.94
2.3/10
10:30 Upcoming 1030
RU A. Kukasian
TR K. Kirci
–
▾1.9 ▴1.82
6.3/10
10:30 Upcoming 1030
ES J. Plans
AT N. Waldner
–
▴1.5 ▾2.6
3.0/10
11:30 Upcoming 1130
GB L. Hooper
GE A. Bakshi
–
▴3.3 ▾1.26
2.0/10
11:30 Upcoming 1130
GB O. Weightman
PL B. Zgola
–
▴1.29 ▾3.75
1.1/10
M15 Trois - Rivières Hard ITF Men - M15 Trois - Rivières (Hard) 6
15:00 Upcoming 1500
CA F. Roussel
CA J. Peck
–
1.48 2.68
3.3/10
15:00 Upcoming 1500
DE K. Niethammer
SE N. Slavić
–
▴6.5 ▾1.06
1.2/10
17:00 Upcoming 1700
PT R. Fernandes
US L. Hammond
–
▾1.02 ▴9.2
8.0/10
17:30 Upcoming 1730
NO J. O. Lien
PR J. Fellows
–
▾1.5 ▴2.5
3.7/10
17:30 Upcoming 1730
DE L. Wessels
US A. Tripathi
–
▴1.29 ▾3.35
4.9/10
19:30 Upcoming 1930
US D. Kliebhan
CA M. St-Hilaire
–
▾2 ▴1.75
2.9/10
M25 Guadalajara Clay ITF Men - M25 Guadalajara (Clay) 1
00:30 Finished 0030
MX P. Betancourt
US R. Jarvis
0 2
▾4.1 ▴1.16
1 ▾4.1
7663
1 ▾4.1
1.0/10
M25 Heraklion Hard ITF Men - M25 Heraklion (Hard) 3
07:30 Upcoming 0730
DE K. Wehnelt
FR B. Pietri
–
▾1.58 ▴2.19
4.1/10
07:30 Upcoming 0730
CY M. Efstathiou
GR P. Tsitsipas
–
▴1.29 ▾3.1
5.8/10
07:30 Upcoming 0730
US M. Jones
KZ Z. Nurlanuly
–
▴1.32 ▾3.2
3.1/10
M25 Valencia Clay ITF Men - M25 Valencia (Clay) 6
08:30 Upcoming 0830
ES C. Córdoba
RU I. Gakhov
–
▾2.82 ▴1.35
5.5/10
08:30 Upcoming 0830
ES C. Hernandez
PL M. Zielinski
–
▾1.97 ▴1.9
6.3/10
08:30 Upcoming 0830
IT S. Pieri
ES S. Planella
–
1.06 6.5
3.3/10
10:00 Upcoming 1000
VE I. Parisca
UA E. Vanshelboim
–
1.86 1.85
6.3/10
10:00 Upcoming 1000
ES I. Lopez
ES M. Damas
–
▴2.93 ▾1.36
8.3/10
12:00 Upcoming 1200
KZ D. Popko
ES S. Perez Contri
–
▾1.62 ▴2.12
6.3/10
W100 Incheon Hard ITF Women - W100 Incheon (Hard) 14
02:00 Finished 0200
KR B. Jeong
CN Y. Ma
2 0
4.4 1.14
2 1.14
2626
U20.5 ▾1.55
6.7/10
02:00 Finished 0200
KR D. Back
TR B. Cengiz
0 2
▾2.35 ▴1.58
1 ▾2.35
752661
O19.5 ▾1.62
6.7/10
02:00 Finished 0200
KR Y. Kim
KR E. Lee
2 0
▾2.8 ▴1.36
2 ▴1.36
3616
2 ▴1.36
5.7/10
S3 S3
CN Z. Bai
DE C. Werner
15 13
▴1.43 ▾2.7
4.1/10
S2 S2
RU K. Sidorova
ID P. Nugroho
01 13
2.01 ▾1.7
4.9/10
S1 S1
CN J. Wang
KR H. E. Lee
03 00
▾1.47 ▴2.93
5.0/10
S1 S1
CN X. Gao
JP N. Kawaguchi
02 02
▾1.18 ▴4.3
8.7/10
03:00 Upcoming 0300
CN H. Shi
JP S. Hosogi
–
▴1.11 ▾5.8
1 ▴1.11
6264
1 ▴1.11
7.0/10
04:30 Upcoming 0430
JP R. Saigo
JP M. Kuramochi
–
▾2.12 ▴1.71
1.9/10
04:30 Upcoming 0430
KR S. Park
CN H. Yujia
–
2.48 1.55
3.3/10
04:30 Upcoming 0430
CN Y. Ren
KR Y. Ku
–
▾3.1 ▴1.33
2 ▴1.33
633626
O18.5 1.52
7.2/10
04:30 Upcoming 0430
JP Y. Naito
JP S. Saito
–
1.7 2.12
4.6/10
06:30 Upcoming 0630
GB K. Swan
JP A. Ito
–
▴1.51 ▾2.48
6.3/10
06:30 Upcoming 0630
JP N. Sato
CN J. Lu
–
▴1.78 ▾1.98
3.2/10
W15 Antalya Clay ITF Women - W15 Antalya (Clay) 10
06:30 Upcoming 0630
RO D. Simionescu
HU G. Nemcsek
–
▾1.11 ▴5.4
8.0/10
06:30 Upcoming 0630
IT I. Pistola
TR S. Aksu
–
▾1.03 ▴12.5
3.9/10
06:30 Upcoming 0630
AT T. Stabauer
DE A. Wirges
–
▾2.8 ▴1.38
4.3/10
07:00 Upcoming 0700
RO A. Prisăcariu
TR S. Atay
–
▾1.03 ▴8.4
9.3/10
07:00 Upcoming 0700
TR I. Yoruk
TR A. Kumru
–
▾1.85 ▴1.94
7.8/10
09:00 Upcoming 0900
A. Kartseva
CH A. Gabriel
–
▾1.5 ▴2.35
2.9/10
09:00 Upcoming 0900
TR D. Cirpanli
LV A. Lachinova
–
11 1.02
2.7/10
09:00 Upcoming 0900
TR D. Turkmen
BG J. Stamatova
–
▾1.62 ▴2.12
3.1/10
09:00 Upcoming 0900
PL N. Affelt
RU V. Yushchenko
–
▾6.5 ▴1.04
6.0/10
09:00 Upcoming 0900
RU U. Lekomtseva
RU A. Lepskaya
–
▴2.27 ▾1.51
2.6/10
W15 Maanshan Hard ITF Women - W15 Maanshan (Hard) 8
02:00 Finished 0200
RU E. Khodzhaeva
CN R. Wu
0 2
▴4.55 ▾1.14
2 ▾1.14
1626
U20.5 ▴1.58
4.9/10
02:00 Finished 0200
CN J. Wang
CN Y. Chen
2 0
▾1.03 ▴11
1 ▾1.03
6162
1 ▾1.03
7.1/10
02:00 Finished 0200
CN Y. Shao
CN K. Ren
2 0
▾1.08 ▴7
1 ▾1.08
644662
1 ▾1.08
7.1/10
S1 S1
CN J. Sun
CN Y. Sun
02 02
▴3 ▾1.34
6.8/10
02:00 Upcoming 0200
RU A. Varaksina
TH T. Naklo
–
▴6.75 ▾1.1
6.7/10
02:00 Upcoming 0200
JP Y. Sugiyama
CN A. Yang
–
▴2.75 ▾1.47
5.2/10
04:30 Upcoming 0430
RU M. Shikhanova
CN S. Ye
–
▾3.5 ▴1.32
5.9/10
04:30 Upcoming 0430
CN Y. Cao
CN Z. Jiang
–
9 1.04
5.7/10
W15 Monastir Hard ITF Women - W15 Monastir (Hard) 6
08:30 Upcoming 0830
PT M. Sequeira
FR A. Cirotte
–
▴12 ▾1.01
10.0/10
09:00 Upcoming 0900
RU A. Lizunova
FR L. De Ezcurra
–
▾1.02 ▴12
1.5/10
09:00 Upcoming 0900
MX L. I. Fernandez
ES A. Garcia-P.
–
▴1.14 ▾4.55
9.5/10
09:00 Upcoming 0900
FR M. Komano
ES M. Soriano
–
▾4.4 ▴1.23
7.2/10
09:00 Upcoming 0900
IT S. Paris
PL S. Husar
–
▴3.1 ▾1.34
1.9/10
10:30 Upcoming 1030
DE P. Gloeckner
CZ S. Ehrenbergerova
–
▴2.42 ▾1.5
2.3/10
W15 Neuquén Clay ITF Women - W15 Neuquén (Clay) 3
15:00 Upcoming 1500
AR B. Bonardi
M. Madrid Rocca
–
▾1.24 ▴3.7
4.0/10
15:00 Upcoming 1500
PY Z. Doldan
AR V. Abril Bruno
–
▴2.55 ▾1.45
2.5/10
16:00 Upcoming 1600
PY A. López
AR J. Gonzalez
–
12.5 1.01
8.8/10
W15 Sharm El Sheikh Hard ITF Women - W15 Sharm El Sheikh (Hard) 10
07:30 Upcoming 0730
PL M. Hedrzak
CN Y. Shan
–
▴1.26 ▾3.25
2.3/10
07:30 Upcoming 0730
RU M. Medvedeva
HR K. Popović
–
▴7.3 ▾1.08
4.7/10
09:30 Upcoming 0930
EG H. Abouelsaad
RU S. Martianova
–
▴1.47 ▾2.42
3.7/10
09:30 Upcoming 0930
TW M. Tzeng
IN S. Pahwa
–
▾1.57 ▴2.5
2.9/10
10:00 Upcoming 1000
LT I. Dapkutė
IN T. Kashyap
–
▾1.12 ▴4.8
5.7/10
10:00 Upcoming 1000
EG Y. Ezzat
RU K. Belkova
–
▾1.18 ▴4.35
3.2/10
12:00 Upcoming 1200
RU A. Efremova
PL Z. Kolonus
–
▾4.3 ▴1.26
6.0/10
12:00 Upcoming 1200
EE C. Plakk
RS V. Suvirdjonkova
–
▴1.26 ▾3.25
2.8/10
13:00 Upcoming 1300
M. Mylnikova
TR I. Kurt
–
7.5 1.05
3.4/10
13:00 Upcoming 1300
BY P. Kuharenko
BE C. Lopez
–
▾1.14 ▴6.5
4.6/10
W15 Szabolcsveresmart Hard ITF Women - W15 Szabolcsveresmart (Hard) 8
09:00 Upcoming 0900
SK K. Kužmová
PL M. Pawelska
–
▾1.02 ▴10
9.0/10
09:00 Upcoming 0900
AT L. Rabl
HU K. Molnar
–
▾2.25 ▴1.58
6.6/10
09:00 Upcoming 0900
SK T. Gross
BE R. Longueville
–
▾7 ▴1.06
1.7/10
10:30 Upcoming 1030
AT L. Rothensteiner
HU A. K. Toth
–
▴6.6 ▾1.06
3.1/10
10:30 Upcoming 1030
NO M. Burylo
UZ M. Maslenkova
–
▴1.35 ▾3.1
3.1/10
10:30 Upcoming 1030
HU M. Biró
SK M. Chudejova
–
▾1.23 ▴4
6.4/10
12:00 Upcoming 1200
GB A. Boron
DE L. Fojčik
–
▴1.82 ▾2.07
1.5/10
12:00 Upcoming 1200
SK T. Šramková
HU V. Varga
–
▾4.35 ▴1.2
1.7/10
W35 Hamamatsu ITF Women - W35 Hamamatsu 8
01:00 Finished 0100
JP N. Arakawa
JP Y. Kitahara
0 2
▾4.9 1.16
2 1.16
3616
2 1.16
3.7/10
01:00 Finished 0100
SE T. T. Deng
CN M. Y. Chen
2 1
1.35 3.1
1 1.35
6463
1 1.35
4.7/10
01:00 Finished 0100
JP Y. Hosoki
JP F. Kozaki
1 2
▾3.9 ▴1.27
2 ▴1.27
2646
2 ▴1.27
3.0/10
03:00 Finished 0300
TH K. Yodpetch
JP S. Tsujioka
0 2
2.18 1.62
1 2.18
6264
U21.5 ▴1.68
2.5/10
S1 S1
JP H. Arakawa
JP Y. Negishi
00 00
▴1.06 ▾7
7.0/10
S2 S2
JP H. Abe
JP M. Uchijima
05 16
▾1.02 ▴15
6.6/10
S1 S1
JP K. Sawashiro
JP N. Suzuki
05 05
▴1.35 ▾2.9
7.6/10
04:00 Upcoming 0400
JP H. Sato
JP M. Mushika
–
▾3.45 ▴1.32
7.8/10
W35 Liberec Hard ITF Women - W35 Liberec (Hard) 8
09:00 Upcoming 0900
DE M. Guth
IT F. Urgesi
–
▾3.4 ▴1.27
6.4/10
09:00 Upcoming 0900
CH V. Ryser
PL A. Kmiecik
–
1.1 ▴7.8
5.7/10
10:00 Upcoming 1000
CZ L. Munzarova
IT V. Paganetti
–
▾2.93 ▴1.32
1.2/10
10:00 Upcoming 1000
CZ T. Krejčova
PL D. Gorska
–
▾1.33 ▴3.1
7.8/10
11:30 Upcoming 1130
ME D. Kovinić
DE J. Stusek
–
▾1.8 ▴1.9
5.3/10
11:30 Upcoming 1130
SI P. Lovrič
HR T. Lukas
–
▴1.54 ▾2.43
2.5/10
13:00 Upcoming 1300
DE I. Wobker
PL W. Ewald
–
▾1.65 ▴2.22
4.8/10
13:00 Upcoming 1300
HR I. Primorac
DE E. M. Voraček
–
▾1.39 ▴2.8
5.0/10
W50 Heraklion Clay ITF Women - W50 Heraklion (Clay) 16
07:00 Upcoming 0700
NL A. Stoyanov
CZ A. Oktiabreva
–
▾3.25 ▴1.32
2.3/10
07:00 Upcoming 0700
FR A. Lew Yan Foon
FR L. Nguyen Tan
–
▾1.87 ▴1.9
7.5/10
07:00 Upcoming 0700
ES L. Cortez
SE C. W. Hennemann
–
▾2.42 ▴1.5
3.0/10
07:00 Upcoming 0700
RU M. Golovina
IT M. Lombardini
–
2.26 ▾1.58
2.7/10
09:00 Upcoming 0900
IT D. Chiesa
NL S. Van Emst
–
▴1.55 ▾2.45
8.1/10
09:00 Upcoming 0900
CZ E. Tichackova
IT A. Mazzola
–
▴1.89 ▾1.92
4.5/10
09:00 Upcoming 0900
IT G. Pedone
CY R. Serban
–
▾1.98 ▴1.78
3.4/10
09:00 Upcoming 0900
DE J. Steur
GR E. Korokozidi
–
▴1.57 ▾2.33
2.7/10
10:00 Upcoming 1000
ES A. Geerlings
IT M. Paoletti
–
▾1.36 ▴2.9
10.0/10
10:00 Upcoming 1000
IT J. Ruggeri
RO C. N. Todoni
–
▾1.18 ▴4.4
1.6/10
10:00 Upcoming 1000
GR M. Argyrokastriti
GR M. Matoula
–
▾3.1 ▴1.32
4.8/10
10:00 Upcoming 1000
GB V. Allen
RO E. R. Bertea
–
▾4 ▴1.22
8.6/10
12:00 Upcoming 1200
ES A. Fita Boluda
IT A. Raggi
–
▾1.27 ▴3.25
2.5/10
12:00 Upcoming 1200
ES C. Martinez
UA D. Yesypchuk
–
▴2.12 ▾1.73
3.5/10
12:00 Upcoming 1200
RU F. Dorofeeva-R.
NL L. Ebeling
–
▾1.8 ▴1.94
2.5/10
12:00 Upcoming 1200
GR V. Grammatikopoul
IT N. Brancaccio
–
▾3 ▴1.44
2.2/10
W75 Petange Hard ITF Women - W75 Petange (Hard) 10
09:00 Upcoming 0900
HU D. Galfi
RU K. Pavlova
–
▴1.33 ▾2.93
4.4/10
09:00 Upcoming 0900
IT I. Serban
DE M. Hodžić
–
▴2.07 ▾1.7
4.1/10
11:00 Upcoming 1100
BE G. Minnen
NL B. Du Pree
–
▾1.35 ▴2.8
5.5/10
11:00 Upcoming 1100
IT L. Pigato
IT G. Maduzzi
–
1.16 4.5
5.0/10
13:00 Upcoming 1300
RU J. Avdeeva
SE L. Zaar
–
▾1.48 ▴2.5
2.0/10
14:00 Upcoming 1400
UA K. Zavatska
UA V. Podrez
–
▾3.45 ▴1.32
3.5/10
15:30 Upcoming 1530
SE L. Nilsson
FR N. Berecoechea
–
▾1.57 ▴2.34
4.9/10
16:30 Upcoming 1630
LU M. Weckerle
CZ A. Siskova
–
▾4.8 ▴1.12
8.0/10
17:30 Upcoming 1730
DK R. Munk
US F. Crawley
–
4.6 1.17
5.2/10
18:30 Upcoming 1830
FR O. Dodin
DE E. Bennemann
–
▴1.35 ▾3.15
1.6/10

18+ · Predictions are AI-generated for informational use · We never place bets on your behalf

TennisPredictions.ai

The model behind our AI tennis predictions

01

Every day, our model works through the full schedule, reading serve numbers, rally patterns and recent form to build that day's tennis predictions.

02

Learning from every match: Our system takes in every new result and keeps updating its tennis predictions across ATP and WTA events.

03

Grounded in the details: Form, surface and match context all feed into the model, and that is how it arrives at every tennis prediction it publishes.

04

Powered by artificial intelligence, machine learning, and mathematical modeling, our Java-based engine delivers tennis predictions for every match, built the same way each time.

05

AI that never rests: When hundreds of ATP, WTA and Challenger matches are on the schedule, manual analysis can’t keep up — our model highlights the highest-confidence picks.

06

Transparency matters to us, so nothing is hidden: our Progress page tracks how every prediction has turned out, match by match.

Smarter tennis predictions

Why choose our daily forecasts

Every ATP and WTA match leaves a trail of numbers behind it: serve percentages, break points saved, how a player holds up on clay or on a quick indoor court. Our AI model reads all of it and gives you a clear view of each match before the first ball is struck, which is where our daily tennis predictions come from.

ATPWTACHALLENGERITFGRAND SLAMS

SMARTER PICKS

The model does the analysis for you: every pick comes with its odds and a trust score, and every one is graded once the match ends.

WORLDWIDE COVERAGE

From Grand Slams to local qualifiers, our platform delivers tennis predictions for every match.

Verified results

How the model does across every tour

Today's board lists every match the model has an opinion on — ATP and WTA main draws, Challenger and ITF, qualifying included. For each one the model names the expected winner, an over/under on the number of games and a correct score, and the result stays on the row once the match is over.

Since 17 Nov 2025, 43,802 predictions have been settled here, about 124 on an average day, and 67.2% of the best tips have won. The table below breaks that record down by surface, one of the factors the model weighs most heavily.

Surface Settled Success
Hard 24,150 66.8%
Clay 18,331 67.2%
Grass 1,321 72.5%

The table counts the best tip of every match in the archive, including team events that are not part of any tour. Each circuit page shows the same table for its own tour.

THE SCIENCE OF PREDICTION

Inside our prediction engine

1

Advanced tennis data gathering

Every tennis prediction starts with data: our Java-based engine continuously collects match statistics from professional tennis feeds through secure APIs, cleaning and cross-checking every input before it reaches the model. Inputs range from serve accuracy, break points and aces to player fatigue, surface type and real-time performance metrics.

Designed specifically for high-frequency tennis analysis, our scalable data platform stores every piece of information it receives. From live scores to historical results, player rankings, and schedule updates, the system ensures nothing is missed when building each tournament's insights.

2

Making the data trustworthy

Raw tennis data arrives messy. A retirement mid-set, a walkover logged as a straight-sets win, the same player spelled two different ways across two feeds: all of it has to be caught before the model ever sees it. Every record is checked against the rest, corrected where it can be and discarded where it cannot.

This is the least visible stage of the process, and the one that determines the quality of everything after it. A model trained on unreliable numbers will still return a confident answer, only the wrong one. Anomalies and distorted records are filtered out, and anything we cannot verify is left out of the training data rather than passed on to the model.

3

From patterns to predictions

Once the raw data is processed, our proprietary engine — built on advanced deep neural networks and adaptive pattern recognition — produces each tennis prediction. It evaluates a broad range of contextual variables, including player momentum, recent performance trends, head-to-head matchups, serve-return efficiency, surface adaptability, and psychological resilience under tournament pressure. The model then combines these multidimensional factors into one forecast per market, and every forecast is graded once the match ends.

Membership options

Choose a plan

Nothing is held back on any plan — every tennis prediction, every stat, every tool is included. We value your trust: cancel anytime, in seconds, if we fall short of your expectations.

Basic
1 Month
16.99$/ month
Affordable
  • AccessFull Access
  • TechnologyNT Apex
  • Bankers Win Rate81%
Subscribe Now
Most Popular
Standard
3 Months
12.69$/ month
Save $13
  • AccessFull Access
  • TechnologyNT Apex
  • Bankers Win Rate81%
Subscribe Now
Best Deal
Premium
6 Months
10.19$/ month
Save $41
  • AccessFull Access
  • TechnologyNT Apex
  • Bankers Win Rate81%
Subscribe Now
Subscribe Now

Everything you should know

Frequently asked questions

support@tennispredictions.ai

Tennis predictions: the basics

What does TennisPredictions.ai do?

+

TennisPredictions.ai is an AI-powered tennis predictions platform developed by NerdyTips. It provides match forecasts for ATP, WTA, Challenger and ITF tournaments around the world. Each prediction is generated automatically by our AI model, which analyzes thousands of match variables — from player form and fatigue to surface compatibility and serving performance. Every match page also carries detailed player stats, the latest results and the head-to-head record, so you can follow the reasoning behind each forecast.

How does your tennis prediction algorithm work?

+

NT Apex, the proprietary AI engine NerdyTips built for our tennis predictions, follows a dual-layer model: a parametric core that stores and adjusts learned weight coefficients for key player metrics — such as serve efficiency, return points won, break conversion rate, and unforced error patterns — and a higher-level pattern recognition module that detects hidden performance trends over time. It runs across a distributed Java-based infrastructure built to scale. Each match result continuously retrains the system, allowing it to adapt dynamically to player form, fatigue, and evolving tour conditions. In addition to player-level modeling, NT Apex incorporates contextual layers like surface type (hard, clay, grass), tournament tier, and historical head-to-head performance. By combining structured data analysis with machine learning feedback loops, the system delivers consistent forecasts, never adjusted by hand, for every ATP, WTA, Challenger, and ITF event. The same core framework also powers the football version of NT Apex.

What makes TennisPredictions.ai different?

+

Most tennis previews come down to an opinion about who looks the stronger player on the day. TennisPredictions.ai works from the record instead: how each player performs on this surface, how heavy their schedule has been in recent weeks, what their current form shows, and what the head-to-head actually says rather than what it is remembered for. The model runs the match through repeated simulations and weighs the outcomes before settling on a prediction. And because every tennis prediction is published with its reasoning and the stats behind it, you can judge the case yourself instead of taking a number on trust.

What goes into every tennis prediction:

  • Our AI model analyzes serve quality, return efficiency, and surface-specific strengths.
  • Nobody touches the output: the process is entirely automated, running on verified statistical data alone — no human bias enters the forecast.
  • Detailed player statistics, recent form graphs, and head-to-head history appear on each match page for deeper insight.

Can I place bets on TennisPredictions.ai?

+

No — this is an analytics platform, not a sportsbook. There is no wagering of any kind here, and we do not promote or encourage gambling: all we offer is tennis analysis.

About our tennis forecasts

What do the different tennis prediction types mean?

+

Our platform generates several types of tennis predictions for each match, based on the available data and tournament context. Here’s what they mean:

  • 1: The first-listed player wins.
  • 2: The second-listed player wins.
  • Set score: Predicted outcome in sets, such as 2–0, 2–1, or 3–2, depending on the tournament format.
  • Total games: A pick on whether the match goes over or under a given number of games, counted across all sets.
  • Exact score: Exact scoreline prediction, including the games per set.

Which tennis tournaments does your AI model cover?

+

Our AI model covers every major professional tennis tournament: ATP, WTA, Challenger, ITF and Grand Slam events. Coverage widens continuously as new tournaments and players join the global schedule.

Can I view tennis statistics for players and matches?

+

Absolutely. Every match page on TennisPredictions.ai includes a complete set of player and match statistics to help users better understand each tennis prediction. These include:

  • Key player performance metrics such as aces, double faults, breaks converted, total points won, and first-serve percentage.
  • Recent form overview from the last 10 matches — showing wins, losses, winning and losing streaks, and unexpected results.
  • Head-to-head record between the two players, including outcomes and set scores from previous encounters.
  • Recent match history for each player, offering quick access to their latest performances and momentum before the match.

Do you provide fixed matches or insider tips?

+

No. TennisPredictions.ai does not provide or claim to offer fixed matches or insider tips. All insights are generated objectively using data analysis and AI-driven learning models.