ATP Tennis predictions Mon, Nov 9
Win probabilities, expected games and total games for every ATP match. Methodology →
6 tour-level matches on this slate · 130–87 since Oct 20 (model V4) →
49 Challenger matches · Challenger: 166–109 since Oct 27 (model V4) →
Games
Stockholm
#49
Hanfmann
#21
Michelsen
Biggest factor: Return edge · Michelsen
#47
Norrie
Biggest factor: Return edge · Norrie
#142
Gojo
#62
Machac
Biggest factor: Return edge · Machac
#36
Humbert
#101
Vallejo
Biggest factor: Serve edge · Humbert
#54
Etcheverry
Biggest factor: Serve edge · Etcheverry
#78
Samuel
Biggest factor: Return edge · Samuel
ATP Challenger 49 matches
Brisbane 4 Challenger
Biggest factor: Return edge · Moriya
Biggest factor: Serve edge · Palan
Biggest factor: Serve edge · Fancutt
Biggest factor: Serve edge · Langmo
Biggest factor: Return edge · Winter
#244
Tomic
Biggest factor: Return edge · Tomic
Hersonissos 5 Challenger
#306
Krutykh
Biggest factor: Return edge · Krutykh
Andreev
Biggest factor: Return edge · Andreev
Biggest factor: Serve edge · Reco
#307
Monday
Biggest factor: Serve edge · Monday
Biggest factor: Return edge · Forti
Biggest factor: Serve edge · Searle
Knoxville Challenger
Biggest factor: Return edge · Legout
#309
Svajda
Biggest factor: Serve edge · Rehberg
#177
Draxl
Biggest factor: Return edge · Draxl
Lima 3 Challenger
Biggest factor: Return edge · Nikles
Biggest factor: Return edge · Sanchez Jover
#329
Roncadelli
Biggest factor: Return edge · Roncadelli
#135
Jarry
Biggest factor: Serve edge · Jarry
#250
Misolic
Biggest factor: Serve edge · Misolic
#197
Boyer
#119
Dellien
Biggest factor: Return edge · Dellien
Biggest factor: Return edge · Alcala Gurri
Matsuyama Challenger
Biggest factor: Serve edge · Shiraishi
Biggest factor: Serve edge · Matsuda
Biggest factor: Return edge · Imamura
Biggest factor: Serve edge · Staeheli
#302
Schwaerzler
Biggest factor: Serve edge · Schwaerzler
Biggest factor: Return edge · Tokuda
Biggest factor: Return edge · Imai
#350
Hsu
Biggest factor: Serve edge · Smith
Broady
#261
Harris
Biggest factor: Return edge · Broady
Biggest factor: Return edge · Friend
Monastir Challenger
Biggest factor: Serve edge · Vives Marcos
Biggest factor: Serve edge · Djuric
Biggest factor: Serve edge · Dalmasso
Janvier
Biggest factor: Return edge · Pankin
Biggest factor: Return edge · Malige
Mikrut
Biggest factor: Return edge · Mikrut
#227
Dougaz
Biggest factor: Serve edge · Dougaz
#232
Kouame
Biggest factor: Return edge · Kouame
Orleans Challenger
#245
Blanchet
Biggest factor: Serve edge · Blanchet
#194
Butvilas
Biggest factor: Serve edge · Butvilas
#304
Grenier
Biggest factor: Return edge · Krumich
#151
Ritschard
#186
Nardi
Biggest factor: Serve edge · Nardi
#313
Hemery
Biggest factor: Return edge · Poullain
#196
Neumayer
#131
Tabur
Biggest factor: Serve edge · Tabur
#223
Gentzsch
Biggest factor: Serve edge · Gentzsch
#210
Pellegrino
#61
Bonzi
Biggest factor: Serve edge · Bonzi
#203
Budkov Kjaer
Biggest factor: Return edge · Budkov Kjaer
How we got this
Model vs market
- Model
- 56.2%
- First line
- –
- Latest
- 64.4%
Decimal odds 1.44 / 2.61, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Marinkov | Moriya | |
|---|---|---|
| Serve pts won, hard% | 56.5396th of 472 | 56.0 |
| Return pts won, hard% | 28.2443rd of 472 | 31.9 |
| Hard rating% pts vs avg | 42.36436th of 472 | 43.94 |
| All-surface rating% pts vs avg | 42.13511th of 570 | 43.71 |
| Wins, last 10 | 4 | – |
| Matches, 12 months | 22 | – |
| Matches rated | 47 | 727 |
Serve and return
| Marinkov | Moriya | |
|---|---|---|
| Serve pts wonthis match, hard | 60.2% | 61.7% |
| Return pts won | 38.3% | 39.8% |
| Hold servechance to win a service game | 73.9% | 76.9% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setMoriya 55%from both hold chances
- Match, set by setMoriya 58%set by set, before calibration; published 56% after tempering toward 50%
Conditions
- Days since last event Not in the modelMoriya 14, Marinkov 161counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 63.2%
- First line
- –
- Latest
- 71.7%
Decimal odds 3.29 / 1.30, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Shiraishi | Ogura | |
|---|---|---|
| Serve pts won, hard% | 54.5440th of 472 | 52.9 |
| Return pts won, hard% | 29.5406th of 472 | 28.0 |
| Hard rating% pts vs avg | 42.04444th of 472 | 40.42 |
| All-surface rating% pts vs avg | 41.81521st of 570 | 39.78 |
| Wins, last 10 | 3 | 4 |
| Matches, 12 months | 16 | 8 |
| Matches rated | 42 | 47 |
Serve and return
| Shiraishi | Ogura | |
|---|---|---|
| Serve pts wonthis match, hard | 62.1% | 58.9% |
| Return pts won | 41.1% | 37.9% |
| Hold servechance to win a service game | 77.8% | 71.2% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setShiraishi 61%from both hold chances
- Match, set by setShiraishi 66%set by set, before calibration; published 63% after tempering toward 50%
Conditions
- Days since last event Not in the modelOgura 266, Shiraishi 56counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 67.4%
- First line
- –
- Latest
- 65.5%
Decimal odds 1.41 / 2.68, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Dev | Matsuda | |
|---|---|---|
| Serve pts won, hard% | 53.4459th of 472 | 56.1409th of 472 |
| Return pts won, hard% | 27.8448th of 472 | 29.4410th of 472 |
| Hard rating% pts vs avg | 40.60465th of 472 | 42.78431st of 472 |
| All-surface rating% pts vs avg | 40.29554th of 570 | 42.49502nd of 570 |
| Wins, last 10 | 2 | 3 |
| Matches, 12 months | 11 | 24 |
| Matches rated | 53 | 47 |
Serve and return
| Dev | Matsuda | |
|---|---|---|
| Serve pts wonthis match, hard | 59.5% | 63.9% |
| Return pts won | 36.1% | 40.5% |
| Hold servechance to win a service game | 72.5% | 81.0% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setMatsuda 64%from both hold chances
- Match, set by setMatsuda 71%set by set, before calibration; published 67% after tempering toward 50%
Conditions
- Days since last event Not in the modelMatsuda 14, Dev 126counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 70.7%
- First line
- –
- Latest
- 66.7%
Decimal odds 1.39 / 2.79, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Matsuda | Imamura | |
|---|---|---|
| Serve pts won, hard% | 54.4444th of 472 | 56.3403rd of 472 |
| Return pts won, hard% | 28.0446th of 472 | 31.4334th of 472 |
| Hard rating% pts vs avg | 41.20459th of 472 | 43.81389th of 472 |
| All-surface rating% pts vs avg | 40.89547th of 570 | 43.47452nd of 570 |
| Wins, last 10 | 0 | 3 |
| Matches, 12 months | 15 | 43 |
| Matches rated | 73 | 109 |
Serve and return
| Matsuda | Imamura | |
|---|---|---|
| Serve pts wonthis match, hard | 58.6% | 63.8% |
| Return pts won | 36.2% | 41.4% |
| Hold servechance to win a service game | 70.5% | 80.9% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setImamura 67%from both hold chances
- Match, set by setImamura 75%set by set, before calibration; published 71% after tempering toward 50%
Conditions
- Days since last event Not in the modelImamura 7, Matsuda 56counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 59.4%
- First line
- –
- Latest
- 32.5%
Decimal odds 1.37 / 2.85, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Palan | Shepp | |
|---|---|---|
| Serve pts won, hard% | 58.9293rd of 472 | 55.2 |
| Return pts won, hard% | 27.5452nd of 472 | 28.9 |
| Hard rating% pts vs avg | 43.22413th of 472 | 42.03 |
| All-surface rating% pts vs avg | 42.75489th of 570 | 41.84 |
| Wins, last 10 | 2 | 1 |
| Matches, 12 months | 19 | 5 |
| Matches rated | 115 | 10 |
Serve and return
| Palan | Shepp | |
|---|---|---|
| Serve pts wonthis match, hard | 65.6% | 63.2% |
| Return pts won | 36.8% | 34.4% |
| Hold servechance to win a service game | 84.0% | 79.9% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setPalan 58%from both hold chances
- Match, set by setPalan 62%set by set, before calibration; published 59% after tempering toward 50%
Conditions
- Days since last event Not in the modelShepp 77, Palan 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 58.0%
- First line
- –
- Latest
- 54.9%
Decimal odds 1.69 / 2.06, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Sach | Fancutt | |
|---|---|---|
| Serve pts won, hard% | 53.1465th of 472 | 57.3 |
| Return pts won, hard% | 28.9425th of 472 | 27.6 |
| Hard rating% pts vs avg | 41.02461st of 472 | 42.44 |
| All-surface rating% pts vs avg | 40.74548th of 570 | 42.19 |
| Wins, last 10 | 2 | 1 |
| Matches, 12 months | 25 | 5 |
| Matches rated | 26 | 113 |
Serve and return
| Sach | Fancutt | |
|---|---|---|
| Serve pts wonthis match, hard | 61.1% | 63.0% |
| Return pts won | 37.0% | 38.9% |
| Hold servechance to win a service game | 75.8% | 79.6% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setFancutt 57%from both hold chances
- Match, set by setFancutt 60%set by set, before calibration; published 58% after tempering toward 50%
Conditions
- Days since last event Not in the modelFancutt 56, Sach 56counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 67.9%
- First line
- –
- Latest
- 53.7%
Decimal odds 1.73 / 2.01, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Kumasaka | Staeheli | |
|---|---|---|
| Serve pts won, hard% | 53.4458th of 472 | 56.2 |
| Return pts won, hard% | 30.6368th of 472 | 32.2 |
| Hard rating% pts vs avg | 42.03445th of 472 | 44.23 |
| All-surface rating% pts vs avg | 41.73524th of 570 | 44.49386th of 570 |
| Wins, last 10 | 1 | 3 |
| Matches, 12 months | 19 | 11 |
| Matches rated | 54 | 27 |
Serve and return
| Kumasaka | Staeheli | |
|---|---|---|
| Serve pts wonthis match, hard | 56.7% | 61.2% |
| Return pts won | 38.8% | 43.3% |
| Hold servechance to win a service game | 66.4% | 75.9% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setStaeheli 65%from both hold chances
- Match, set by setStaeheli 72%set by set, before calibration; published 68% after tempering toward 50%
Conditions
- Days since last event Not in the modelStaeheli 42, Kumasaka 91counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 64.3%
- First line
- –
- Latest
- 72.4%
Decimal odds 1.29 / 3.39, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Leong | Schwaerzler | |
|---|---|---|
| Serve pts won, hard% | 56.3400th of 472 | 61.1196th of 472 |
| Return pts won, hard% | 32.5268th of 472 | 30.2385th of 472 |
| Hard rating% pts vs avg | 44.39361st of 472 | 45.64289th of 472 |
| All-surface rating% pts vs avg | 44.00418th of 570 | 45.76302nd of 570 |
| Wins, last 10 | 4 | 5 |
| Matches, 12 months | 30 | 56 |
| Matches rated | 74 | 143 |
Serve and return
| Leong | Schwaerzler | |
|---|---|---|
| Serve pts wonthis match, hard | 61.7% | 65.3% |
| Return pts won | 34.7% | 38.3% |
| Hold servechance to win a service game | 77.0% | 83.4% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setSchwaerzler 62%from both hold chances
- Match, set by setSchwaerzler 67%set by set, before calibration; published 64% after tempering toward 50%
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 71.4%
- First line
- –
- Latest
- 42.7%
Decimal odds 1.62 / 2.17, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Tokuda | Saitoh | |
|---|---|---|
| Serve pts won, hard% | 58.1339th of 472 | 55.9 |
| Return pts won, hard% | 31.5323rd of 472 | 28.2 |
| Hard rating% pts vs avg | 44.77339th of 472 | 42.03 |
| All-surface rating% pts vs avg | 44.49384th of 570 | 41.80 |
| Wins, last 10 | 3 | 2 |
| Matches, 12 months | 13 | 0 |
| Matches rated | 121 | 25 |
Serve and return
| Tokuda | Saitoh | |
|---|---|---|
| Serve pts wonthis match, hard | 65.4% | 60.0% |
| Return pts won | 40.0% | 34.6% |
| Hold servechance to win a service game | 83.7% | 73.5% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setTokuda 68%from both hold chances
- Match, set by setTokuda 76%set by set, before calibration; published 71% after tempering toward 50%
Conditions
- Days since last event Not in the modelSaitoh 371, Tokuda 189counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 60.4%
- First line
- –
- Latest
- 66.1%
Decimal odds 1.40 / 2.73, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Isomura | Langmo | |
|---|---|---|
| Serve pts won, hard% | 55.8424th of 472 | 59.0291st of 472 |
| Return pts won, hard% | 30.0391st of 472 | 29.4411th of 472 |
| Hard rating% pts vs avg | 42.93425th of 472 | 44.22371st of 472 |
| All-surface rating% pts vs avg | 42.69491st of 570 | 44.13412th of 570 |
| Wins, last 10 | 3 | 2 |
| Matches, 12 months | 20 | 39 |
| Matches rated | 67 | 202 |
Serve and return
| Isomura | Langmo | |
|---|---|---|
| Serve pts wonthis match, hard | 61.9% | 64.5% |
| Return pts won | 35.5% | 38.1% |
| Hold servechance to win a service game | 77.4% | 82.2% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setLangmo 59%from both hold chances
- Match, set by setLangmo 63%set by set, before calibration; published 60% after tempering toward 50%
Conditions
- Days since last event Not in the modelLangmo 14, Isomura 91counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 77.7%
- First line
- –
- Latest
- 65.2%
Decimal odds 2.68 / 1.43, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Winter | Ayeni | |
|---|---|---|
| Serve pts won, hard% | 58.5320th of 472 | 55.8 |
| Return pts won, hard% | 32.8243rd of 472 | 29.0 |
| Hard rating% pts vs avg | 45.65288th of 472 | 42.40 |
| All-surface rating% pts vs avg | 45.34326th of 570 | 42.15 |
| Wins, last 10 | 2 | 1 |
| Matches, 12 months | 27 | 4 |
| Matches rated | 90 | 16 |
Serve and return
| Winter | Ayeni | |
|---|---|---|
| Serve pts wonthis match, hard | 65.9% | 58.5% |
| Return pts won | 41.5% | 34.1% |
| Hold servechance to win a service game | 84.4% | 70.5% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setWinter 73%from both hold chances
- Match, set by setWinter 82%set by set, before calibration; published 78% after tempering toward 50%
Conditions
- Days since last event Not in the modelAyeni 63, Winter 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 65.8%
- First line
- –
- Latest
- 62.7%
Decimal odds 1.49 / 2.50, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Ellis | Tomic | |
|---|---|---|
| Serve pts won, hard% | 59.9253rd of 472 | 61.6184th of 472 |
| Return pts won, hard% | 28.6431st of 472 | 32.3279th of 472 |
| Hard rating% pts vs avg | 44.23369th of 472 | 46.91217th of 472 |
| All-surface rating% pts vs avg | 43.90427th of 570 | 46.61244th of 570 |
| Wins, last 10 | 4 | 6 |
| Matches, 12 months | 30 | 48 |
| Matches rated | 154 | 691 |
Serve and return
| Ellis | Tomic | |
|---|---|---|
| Serve pts wonthis match, hard | 63.2% | 67.3% |
| Return pts won | 32.7% | 36.8% |
| Hold servechance to win a service game | 79.8% | 86.5% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setTomic 63%from both hold chances
- Match, set by setTomic 69%set by set, before calibration; published 66% after tempering toward 50%
Conditions
- Days since last event Not in the modelTomic 32, Ellis 56counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 80.5%
- First line
- –
- Latest
- 69.8%
Decimal odds 3.08 / 1.33, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Imai | Katayama | |
|---|---|---|
| Serve pts won, hard% | 58.4 | 54.7 |
| Return pts won, hard% | 31.0 | 26.3 |
| Hard rating% pts vs avg | 44.68 | 40.50 |
| All-surface rating% pts vs avg | 44.39 | 40.27 |
| Wins, last 10 | 6 | 0 |
| Matches, 12 months | 3 | 0 |
| Matches rated | 85 | 22 |
Serve and return
| Imai | Katayama | |
|---|---|---|
| Serve pts wonthis match, hard | 67.6% | 59.2% |
| Return pts won | 40.8% | 32.4% |
| Hold servechance to win a service game | 87.0% | 72.0% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setImai 76%from both hold chances
- Match, set by setImai 85%set by set, before calibration; published 80% after tempering toward 50%
Conditions
- Days since last event Not in the modelKatayama 371, Imai 14counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 57.1%
- First line
- –
- Latest
- 52.2%
Decimal odds 1.78 / 1.94, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Hsu | Smith | |
|---|---|---|
| Serve pts won, hard% | 57.6356th of 472 | 63.4111th of 472 |
| Return pts won, hard% | 33.2219th of 472 | 29.1420th of 472 |
| Hard rating% pts vs avg | 45.42297th of 472 | 46.26255th of 472 |
| All-surface rating% pts vs avg | 45.00350th of 570 | 46.03284th of 570 |
| Wins, last 10 | 3 | 5 |
| Matches, 12 months | 38 | 58 |
| Matches rated | 221 | 211 |
Serve and return
| Hsu | Smith | |
|---|---|---|
| Serve pts wonthis match, hard | 63.9% | 65.7% |
| Return pts won | 34.3% | 36.1% |
| Hold servechance to win a service game | 81.1% | 84.1% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setSmith 56%from both hold chances
- Match, set by setSmith 59%set by set, before calibration; published 57% after tempering toward 50%
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 56.2%
- First line
- –
- Latest
- 45.2%
Decimal odds 1.70 / 2.06, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Broady | Harris | |
|---|---|---|
| Serve pts won, hard% | 60.1 | 60.6222nd of 472 |
| Return pts won, hard% | 34.5 | 32.2280th of 472 |
| Hard rating% pts vs avg | 47.29 | 46.44245th of 472 |
| All-surface rating% pts vs avg | 46.92 | 46.43261st of 570 |
| Wins, last 10 | – | 4 |
| Matches, 12 months | – | 48 |
| Matches rated | 582 | 320 |
Serve and return
| Broady | Harris | |
|---|---|---|
| Serve pts wonthis match, hard | 62.3% | 60.8% |
| Return pts won | 39.2% | 37.7% |
| Hold servechance to win a service game | 78.2% | 75.2% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setBroady 55%from both hold chances
- Match, set by setBroady 58%set by set, before calibration; published 56% after tempering toward 50%
Conditions
- AgeHarris 31.8, Broady 32.8small age adjustment to serve
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 97.0%
- First line
- –
- Latest
- 89.3%
Decimal odds 1.05 / 8.77, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Kusuhara | Friend | |
|---|---|---|
| Serve pts won, hard% | 52.6466th of 472 | 61.1198th of 472 |
| Return pts won, hard% | 24.1470th of 472 | 33.5203rd of 472 |
| Hard rating% pts vs avg | 38.36471st of 472 | 47.27195th of 472 |
| All-surface rating% pts vs avg | 38.08568th of 570 | 47.01217th of 570 |
| Wins, last 10 | 3 | 6 |
| Matches, 12 months | 10 | 40 |
| Matches rated | 15 | 57 |
Serve and return
| Kusuhara | Friend | |
|---|---|---|
| Serve pts wonthis match, hard | 54.7% | 72.5% |
| Return pts won | 27.5% | 45.3% |
| Hold servechance to win a service game | 61.6% | 92.8% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setFriend 93%from both hold chances
- Match, set by setFriend 99%set by set, before calibration; published 97% after tempering toward 50%
Conditions
- Days since last event Not in the modelFriend 14, Kusuhara 196counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 80.3%
- First line
- –
- Latest
- 55.6%
Decimal odds 1.67 / 2.09, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Paldanius | Krutykh | |
|---|---|---|
| Serve pts won, hard% | 56.4 | 59.4 |
| Return pts won, hard% | 28.2 | 33.5 |
| Hard rating% pts vs avg | 42.31 | 46.42 |
| All-surface rating% pts vs avg | 41.84 | 45.72306th of 570 |
| Wins, last 10 | 0 | 5 |
| Matches, 12 months | 4 | 18 |
| Matches rated | 14 | 216 |
Serve and return
| Paldanius | Krutykh | |
|---|---|---|
| Serve pts wonthis match, hard | 58.5% | 66.8% |
| Return pts won | 33.2% | 41.5% |
| Hold servechance to win a service game | 70.4% | 85.7% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setKrutykh 76%from both hold chances
- Match, set by setKrutykh 85%set by set, before calibration; published 80% after tempering toward 50%
Conditions
- Days since last event Not in the modelKrutykh 35, Paldanius 112counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 59.2%
- First line
- –
- Latest
- 73.9%
Decimal odds 3.54 / 1.25, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Andreev | Mashtakov | |
|---|---|---|
| Serve pts won, hard% | 57.4 | 58.1 |
| Return pts won, hard% | 33.5 | 30.8 |
| Hard rating% pts vs avg | 45.44 | 44.44 |
| All-surface rating% pts vs avg | 45.52 | 44.40 |
| Wins, last 10 | 5 | 1 |
| Matches, 12 months | 8 | 0 |
| Matches rated | 240 | 16 |
Serve and return
| Andreev | Mashtakov | |
|---|---|---|
| Serve pts wonthis match, hard | 62.3% | 60.1% |
| Return pts won | 39.9% | 37.7% |
| Hold servechance to win a service game | 78.3% | 73.8% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setAndreev 58%from both hold chances
- Match, set by setAndreev 61%set by set, before calibration; published 59% after tempering toward 50%
Conditions
- Days since last event Not in the modelMashtakov 420, Andreev 49counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 57.3%
- First line
- –
- Latest
- 36.2%
Decimal odds 2.56 / 1.45, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Carboni | Reco | |
|---|---|---|
| Serve pts won, hard% | 54.2447th of 472 | 58.2 |
| Return pts won, hard% | 32.0295th of 472 | 29.7 |
| Hard rating% pts vs avg | 43.06420th of 472 | 43.94 |
| All-surface rating% pts vs avg | 43.11472nd of 570 | 43.36 |
| Wins, last 10 | 4 | 0 |
| Matches, 12 months | 29 | 2 |
| Matches rated | 65 | 15 |
Serve and return
| Carboni | Reco | |
|---|---|---|
| Serve pts wonthis match, hard | 60.0% | 61.8% |
| Return pts won | 38.2% | 40.0% |
| Hold servechance to win a service game | 73.6% | 77.1% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setReco 56%from both hold chances
- Match, set by setReco 59%set by set, before calibration; published 57% after tempering toward 50%
Conditions
- Days since last event Not in the modelReco 42, Carboni 28counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 55.3%
- First line
- –
- Latest
- 63.1%
Decimal odds 2.51 / 1.47, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Blanchet | Gadamauri | |
|---|---|---|
| Serve pts won, hard% | 62.0162nd of 472 | 59.9250th of 472 |
| Return pts won, hard% | 31.9297th of 472 | 32.5267th of 472 |
| Hard rating% pts vs avg | 46.95212th of 472 | 46.21257th of 472 |
| All-surface rating% pts vs avg | 46.61245th of 570 | 45.92288th of 570 |
| Wins, last 10 | 4 | 5 |
| Matches, 12 months | 40 | 51 |
| Matches rated | 224 | 102 |
Serve and return
| Blanchet | Gadamauri | |
|---|---|---|
| Serve pts wonthis match, hard | 64.9% | 63.6% |
| Return pts won | 36.4% | 35.1% |
| Hold servechance to win a service game | 82.8% | 80.5% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setBlanchet 54%from both hold chances
- Match, set by setBlanchet 57%set by set, before calibration; published 55% after tempering toward 50%
Conditions
- Days since last event Not in the modelGadamauri 28, Blanchet 14counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 55.6%
- First line
- –
- Latest
- 43.4%
Decimal odds 2.14 / 1.64, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Kravchenko | Monday | |
|---|---|---|
| Serve pts won, hard% | 59.1 | 63.6106th of 472 |
| Return pts won, hard% | 32.0 | 28.5434th of 472 |
| Hard rating% pts vs avg | 45.51 | 46.04269th of 472 |
| All-surface rating% pts vs avg | 45.16335th of 570 | 45.67307th of 570 |
| Wins, last 10 | 6 | 6 |
| Matches, 12 months | 22 | 24 |
| Matches rated | 99 | 94 |
Serve and return
| Kravchenko | Monday | |
|---|---|---|
| Serve pts wonthis match, hard | 66.1% | 67.5% |
| Return pts won | 32.5% | 33.9% |
| Hold servechance to win a service game | 84.7% | 86.9% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setMonday 55%from both hold chances
- Match, set by setMonday 57%set by set, before calibration; published 56% after tempering toward 50%
Conditions
- Days since last event Not in the modelMonday 77, Kravchenko 28counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 53.5%
- First line
- –
- Latest
- 43.8%
Decimal odds 1.65 / 2.12, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Forti | Giunta | |
|---|---|---|
| Serve pts won, hard% | 60.6 | 60.3237th of 472 |
| Return pts won, hard% | 30.1 | 29.4409th of 472 |
| Hard rating% pts vs avg | 45.32 | 44.87331st of 472 |
| All-surface rating% pts vs avg | 45.32328th of 570 | 44.86357th of 570 |
| Wins, last 10 | 5 | 6 |
| Matches, 12 months | 38 | 25 |
| Matches rated | 201 | 52 |
Serve and return
| Forti | Giunta | |
|---|---|---|
| Serve pts wonthis match, hard | 66.7% | 65.8% |
| Return pts won | 34.2% | 33.3% |
| Hold servechance to win a service game | 85.7% | 84.3% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setForti 53%from both hold chances
- Match, set by setForti 54%set by set, before calibration; published 54% after tempering toward 50%
Conditions
- Days since last event Not in the modelGiunta 21, Forti 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 69.5%
- First line
- –
- Latest
- 56.3%
Decimal odds 1.65 / 2.13, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Rolland De Ravel | Butvilas | |
|---|---|---|
| Serve pts won, hard% | 58.9 | 61.3192nd of 472 |
| Return pts won, hard% | 32.4 | 34.1167th of 472 |
| Hard rating% pts vs avg | 45.64 | 47.72167th of 472 |
| All-surface rating% pts vs avg | 45.17 | 47.28194th of 570 |
| Wins, last 10 | 6 | 4 |
| Matches, 12 months | 8 | 59 |
| Matches rated | 13 | 178 |
Serve and return
| Rolland De Ravel | Butvilas | |
|---|---|---|
| Serve pts wonthis match, hard | 60.3% | 65.3% |
| Return pts won | 34.7% | 39.7% |
| Hold servechance to win a service game | 74.2% | 83.4% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setButvilas 66%from both hold chances
- Match, set by setButvilas 73%set by set, before calibration; published 69% after tempering toward 50%
Conditions
- Days since last event Not in the modelButvilas 7, Rolland De Ravel 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 75.0%
- First line
- –
- Latest
- 72.7%
Decimal odds 1.30 / 3.46, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Hanfmann | Michelsen | |
|---|---|---|
| Serve pts won, hard% | 66.440th of 472 | 66.738th of 472 |
| Return pts won, hard% | 34.6139th of 472 | 38.713th of 472 |
| Hard rating% pts vs avg | 50.4955th of 472 | 52.6920th of 472 |
| All-surface rating% pts vs avg | 50.6849th of 570 | 52.4321st of 570 |
| Wins, last 10 | 4 | 4 |
| Matches, 12 months | 51 | 64 |
| Matches rated | 571 | 262 |
Serve and return
| Hanfmann | Michelsen | |
|---|---|---|
| Serve pts wonthis match, hard | 61.9% | 68.6% |
| Return pts won | 31.4% | 38.1% |
| Hold servechance to win a service game | 77.3% | 88.3% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelTour
- DrawMain draw
- Chance to win a setMichelsen 71%from both hold chances
- Match, set by setMichelsen 80%set by set, before calibration; published 75% after tempering toward 50%
Conditions
- AgeMichelsen 22.2, Hanfmann 35.0small age adjustment to serve
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 54.5%
- First line
- –
- Latest
- 49.2%
Decimal odds 1.82 / 1.88, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Krumich | Grenier | |
|---|---|---|
| Serve pts won, hard% | 58.5322nd of 472 | 59.6268th of 472 |
| Return pts won, hard% | 33.5200th of 472 | 32.6259th of 472 |
| Hard rating% pts vs avg | 46.01272nd of 472 | 46.08266th of 472 |
| All-surface rating% pts vs avg | 46.30268th of 570 | 45.74304th of 570 |
| Wins, last 10 | 4 | 3 |
| Matches, 12 months | 62 | 28 |
| Matches rated | 160 | 507 |
Serve and return
| Krumich | Grenier | |
|---|---|---|
| Serve pts wonthis match, hard | 62.0% | 60.9% |
| Return pts won | 39.1% | 38.0% |
| Hold servechance to win a service game | 77.6% | 75.4% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setKrumich 54%from both hold chances
- Match, set by setKrumich 56%set by set, before calibration; published 55% after tempering toward 50%
Conditions
- AgeGrenier 30.6, Krumich 23.9small age adjustment to serve
- Surface switchKrumich from claygames projection only, not the win chance
- Days since last event Not in the modelGrenier 14, Krumich 7counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 69.5%
- First line
- –
- Latest
- 68.0%
Decimal odds 2.96 / 1.39, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Norrie | Duckworth | |
|---|---|---|
| Serve pts won, hard% | 64.875th of 472 | 64.971st of 472 |
| Return pts won, hard% | 37.135th of 472 | 32.6258th of 472 |
| Hard rating% pts vs avg | 50.9543rd of 472 | 48.75125th of 472 |
| All-surface rating% pts vs avg | 50.7547th of 570 | 48.53138th of 570 |
| Wins, last 10 | 3 | 5 |
| Matches, 12 months | 45 | 61 |
| Matches rated | 575 | 780 |
Serve and return
| Norrie | Duckworth | |
|---|---|---|
| Serve pts wonthis match, hard | 66.9% | 61.9% |
| Return pts won | 38.1% | 33.1% |
| Hold servechance to win a service game | 86.0% | 77.4% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelTour
- DrawMain draw
- Chance to win a setNorrie 66%from both hold chances
- Match, set by setNorrie 74%set by set, before calibration; published 70% after tempering toward 50%
Conditions
- AgeDuckworth 34.8, Norrie 31.2small age adjustment to serve
- Days since last event Not in the modelDuckworth 17, Norrie 6counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 81.2%
- First line
- –
- Latest
- 68.7%
Decimal odds 2.96 / 1.35, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Vives Marcos | Kelm | |
|---|---|---|
| Serve pts won, hard% | 58.9 | 54.6 |
| Return pts won, hard% | 33.4 | 29.3 |
| Hard rating% pts vs avg | 46.14 | 41.92 |
| All-surface rating% pts vs avg | 45.72 | 40.70 |
| Wins, last 10 | 5 | 0 |
| Matches, 12 months | 8 | 3 |
| Matches rated | 38 | 10 |
Serve and return
| Vives Marcos | Kelm | |
|---|---|---|
| Serve pts wonthis match, hard | 65.2% | 56.7% |
| Return pts won | 43.3% | 34.8% |
| Hold servechance to win a service game | 83.2% | 66.3% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setVives Marcos 76%from both hold chances
- Match, set by setVives Marcos 86%set by set, before calibration; published 81% after tempering toward 50%
Conditions
- Days since last event Not in the modelKelm 196, Vives Marcos 28counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 76.4%
- First line
- –
- Latest
- 63.9%
Decimal odds 1.45 / 2.57, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Tepmahc | Djuric | |
|---|---|---|
| Serve pts won, hard% | 54.4 | 59.9 |
| Return pts won, hard% | 27.5 | 28.3 |
| Hard rating% pts vs avg | 41.00 | 44.11 |
| All-surface rating% pts vs avg | 40.60 | 43.94 |
| Wins, last 10 | 1 | 5 |
| Matches, 12 months | 0 | 0 |
| Matches rated | 12 | 16 |
Serve and return
| Tepmahc | Djuric | |
|---|---|---|
| Serve pts wonthis match, hard | 61.7% | 68.8% |
| Return pts won | 31.2% | 38.3% |
| Hold servechance to win a service game | 76.9% | 88.6% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setDjuric 72%from both hold chances
- Match, set by setDjuric 81%set by set, before calibration; published 76% after tempering toward 50%
Conditions
- Days since last event Not in the modelDjuric 455, Tepmahc 427counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 56.3%
- First line
- –
- Latest
- 26.6%
Decimal odds 1.27 / 3.50, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Dalmasso | Echeverria | |
|---|---|---|
| Serve pts won, hard% | 56.1412th of 472 | 53.7 |
| Return pts won, hard% | 28.6432nd of 472 | 29.4 |
| Hard rating% pts vs avg | 42.30438th of 472 | 41.53 |
| All-surface rating% pts vs avg | 41.82520th of 570 | 41.44 |
| Wins, last 10 | 5 | 1 |
| Matches, 12 months | 19 | 1 |
| Matches rated | 29 | 31 |
Serve and return
| Dalmasso | Echeverria | |
|---|---|---|
| Serve pts wonthis match, hard | 62.2% | 60.7% |
| Return pts won | 39.3% | 37.8% |
| Hold servechance to win a service game | 78.0% | 75.0% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setDalmasso 55%from both hold chances
- Match, set by setDalmasso 58%set by set, before calibration; published 56% after tempering toward 50%
Conditions
- Days since last event Not in the modelEcheverria 84, Dalmasso 119counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 70.0%
- First line
- –
- Latest
- 71.0%
Decimal odds 3.21 / 1.31, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Searle | Peniston | |
|---|---|---|
| Serve pts won, hard% | 61.3193rd of 472 | 55.8 |
| Return pts won, hard% | 31.4332nd of 472 | 33.6 |
| Hard rating% pts vs avg | 46.33253rd of 472 | 44.73 |
| All-surface rating% pts vs avg | 46.59248th of 570 | 44.53 |
| Wins, last 10 | 4 | – |
| Matches, 12 months | 29 | – |
| Matches rated | 83 | 269 |
Serve and return
| Searle | Peniston | |
|---|---|---|
| Serve pts wonthis match, hard | 64.3% | 59.3% |
| Return pts won | 40.7% | 35.7% |
| Hold servechance to win a service game | 81.8% | 72.0% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setSearle 67%from both hold chances
- Match, set by setSearle 74%set by set, before calibration; published 70% after tempering toward 50%
Conditions
- AgePeniston 31.0, Searle 20.6small age adjustment to serve
- Days since last event Not in the modelPeniston 6, Searle 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 64.9%
- First line
- –
- Latest
- 71.3%
Decimal odds 1.33 / 3.31, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Gojo | Machac | |
|---|---|---|
| Serve pts won, hard% | 64.776th of 472 | 64.286th of 472 |
| Return pts won, hard% | 32.6256th of 472 | 36.562nd of 472 |
| Hard rating% pts vs avg | 48.66127th of 472 | 50.3559th of 472 |
| All-surface rating% pts vs avg | 48.47142nd of 570 | 50.2862nd of 570 |
| Wins, last 10 | 5 | 5 |
| Matches, 12 months | 42 | 37 |
| Matches rated | 385 | 359 |
Serve and return
| Gojo | Machac | |
|---|---|---|
| Serve pts wonthis match, hard | 63.5% | 67.3% |
| Return pts won | 32.7% | 36.5% |
| Hold servechance to win a service game | 80.4% | 86.6% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelTour
- DrawMain draw
- Chance to win a setMachac 62%from both hold chances
- Match, set by setMachac 68%set by set, before calibration; published 65% after tempering toward 50%
Conditions
- AgeMachac 26.1, Gojo 28.7small age adjustment to serve
- Days since last event Not in the modelMachac 5, Gojo 14counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 57.5%
- First line
- –
- Latest
- 53.4%
Decimal odds 1.74 / 1.99, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Ritschard | Nardi | |
|---|---|---|
| Serve pts won, hard% | 60.3239th of 472 | 60.9211th of 472 |
| Return pts won, hard% | 34.9127th of 472 | 34.4155th of 472 |
| Hard rating% pts vs avg | 47.58175th of 472 | 47.65170th of 472 |
| All-surface rating% pts vs avg | 48.29151st of 570 | 47.37186th of 570 |
| Wins, last 10 | 8 | 4 |
| Matches, 12 months | 14 | 31 |
| Matches rated | 344 | 303 |
Serve and return
| Ritschard | Nardi | |
|---|---|---|
| Serve pts wonthis match, hard | 60.5% | 62.3% |
| Return pts won | 37.7% | 39.5% |
| Hold servechance to win a service game | 74.5% | 78.2% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setNardi 56%from both hold chances
- Match, set by setNardi 59%set by set, before calibration; published 58% after tempering toward 50%
Conditions
- AgeNardi 23.3, Ritschard 32.6small age adjustment to serve
- Days since last event Not in the modelNardi 28, Ritschard 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 60.3%
- First line
- –
- Latest
- 52.5%
Decimal odds 1.91 / 1.73, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Poullain | Hemery | |
|---|---|---|
| Serve pts won, hard% | 58.3331st of 472 | 61.1197th of 472 |
| Return pts won, hard% | 34.5144th of 472 | 30.0392nd of 472 |
| Hard rating% pts vs avg | 46.38248th of 472 | 45.54293rd of 472 |
| All-surface rating% pts vs avg | 45.91291st of 570 | 45.60313th of 570 |
| Wins, last 10 | 5 | 4 |
| Matches, 12 months | 33 | 44 |
| Matches rated | 142 | 470 |
Serve and return
| Poullain | Hemery | |
|---|---|---|
| Serve pts wonthis match, hard | 63.8% | 61.3% |
| Return pts won | 38.7% | 36.2% |
| Hold servechance to win a service game | 81.0% | 76.2% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setPoullain 59%from both hold chances
- Match, set by setPoullain 63%set by set, before calibration; published 60% after tempering toward 50%
Conditions
- Days since last event Not in the modelHemery 21, Poullain 7counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 67.0%
- First line
- –
- Latest
- 67.4%
Decimal odds 2.90 / 1.40, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Humbert | Vallejo | |
|---|---|---|
| Serve pts won, hard% | 68.026th of 472 | 61.0208th of 472 |
| Return pts won, hard% | 35.586th of 472 | 37.137th of 472 |
| Hard rating% pts vs avg | 51.7434th of 472 | 49.04104th of 472 |
| All-surface rating% pts vs avg | 51.4936th of 570 | 49.34101st of 570 |
| Wins, last 10 | 2 | 4 |
| Matches, 12 months | 53 | 71 |
| Matches rated | 486 | 201 |
Serve and return
| Humbert | Vallejo | |
|---|---|---|
| Serve pts wonthis match, hard | 66.1% | 61.8% |
| Return pts won | 38.2% | 33.9% |
| Hold servechance to win a service game | 84.8% | 77.2% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelTour
- DrawMain draw
- Chance to win a setHumbert 64%from both hold chances
- Match, set by setHumbert 71%set by set, before calibration; published 67% after tempering toward 50%
Conditions
- AgeVallejo 22.5, Humbert 28.4small age adjustment to serve
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 52.4%
- First line
- –
- Latest
- 43.3%
Decimal odds 2.15 / 1.64, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Janvier | Pankin | |
|---|---|---|
| Serve pts won, hard% | 59.1 | 59.1287th of 472 |
| Return pts won, hard% | 30.2 | 30.2382nd of 472 |
| Hard rating% pts vs avg | 44.63 | 44.65343rd of 472 |
| All-surface rating% pts vs avg | 44.01 | 44.33398th of 570 |
| Wins, last 10 | – | 2 |
| Matches, 12 months | – | 19 |
| Matches rated | 579 | 27 |
Serve and return
| Janvier | Pankin | |
|---|---|---|
| Serve pts wonthis match, hard | 63.9% | 64.5% |
| Return pts won | 35.5% | 36.1% |
| Hold servechance to win a service game | 81.1% | 82.1% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setPankin 52%from both hold chances
- Match, set by setPankin 53%set by set, before calibration; published 52% after tempering toward 50%
Conditions
- Days since last event Not in the modelPankin 14, Janvier 29counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 73.8%
- First line
- –
- Latest
- 50.9%
Decimal odds 1.89 / 1.82, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Malige | Ehrenschneider | |
|---|---|---|
| Serve pts won, hard% | 52.1 | 54.3 |
| Return pts won, hard% | 31.7 | 23.3 |
| Hard rating% pts vs avg | 41.89 | 38.83 |
| All-surface rating% pts vs avg | 41.38 | 39.57 |
| Wins, last 10 | 1 | 1 |
| Matches, 12 months | 7 | 3 |
| Matches rated | 47 | 12 |
Serve and return
| Malige | Ehrenschneider | |
|---|---|---|
| Serve pts wonthis match, hard | 64.3% | 58.2% |
| Return pts won | 41.8% | 35.7% |
| Hold servechance to win a service game | 81.9% | 69.8% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setMalige 70%from both hold chances
- Match, set by setMalige 78%set by set, before calibration; published 74% after tempering toward 50%
Conditions
- Days since last event Not in the modelEhrenschneider 308, Malige 63counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 70.3%
- First line
- –
- Latest
- 72.5%
Decimal odds 3.37 / 1.28, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Mikrut | Kopp | |
|---|---|---|
| Serve pts won, hard% | 60.2 | 58.5316th of 472 |
| Return pts won, hard% | 33.3 | 30.5374th of 472 |
| Hard rating% pts vs avg | 46.72 | 44.50351st of 472 |
| All-surface rating% pts vs avg | 47.81 | 45.11339th of 570 |
| Wins, last 10 | – | 3 |
| Matches, 12 months | – | 47 |
| Matches rated | 111 | 129 |
Serve and return
| Mikrut | Kopp | |
|---|---|---|
| Serve pts wonthis match, hard | 66.1% | 60.8% |
| Return pts won | 39.2% | 33.9% |
| Hold servechance to win a service game | 84.7% | 75.3% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setMikrut 67%from both hold chances
- Match, set by setMikrut 74%set by set, before calibration; published 70% after tempering toward 50%
Conditions
- Days since last event Not in the modelKopp 21, Mikrut 28counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 82.8%
- First line
- –
- Latest
- 78.5%
Decimal odds 4.26 / 1.17, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Dougaz | Munk Mesa | |
|---|---|---|
| Serve pts won, hard% | 61.8173rd of 472 | 56.7 |
| Return pts won, hard% | 32.4271st of 472 | 27.6 |
| Hard rating% pts vs avg | 47.07206th of 472 | 42.17 |
| All-surface rating% pts vs avg | 46.89227th of 570 | 41.87 |
| Wins, last 10 | 5 | 0 |
| Matches, 12 months | 12 | 2 |
| Matches rated | 217 | 10 |
Serve and return
| Dougaz | Munk Mesa | |
|---|---|---|
| Serve pts wonthis match, hard | 69.2% | 59.9% |
| Return pts won | 40.1% | 30.8% |
| Hold servechance to win a service game | 89.1% | 73.4% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setDougaz 78%from both hold chances
- Match, set by setDougaz 88%set by set, before calibration; published 83% after tempering toward 50%
Conditions
- Days since last event Not in the modelMunk Mesa 28, Dougaz 28counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 63.6%
- First line
- –
- Latest
- 65.6%
Decimal odds 2.67 / 1.40, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Nikles | Tabata | |
|---|---|---|
| Serve pts won, clay% | 55.3 | 56.5 |
| Return pts won, clay% | 34.9 | 29.9 |
| Clay rating% pts vs avg | 45.11 | 43.21 |
| All-surface rating% pts vs avg | 44.65 | 42.02516th of 570 |
| Wins, last 10 | – | 3 |
| Matches, 12 months | – | 13 |
| Matches rated | 126 | 19 |
Serve and return
| Nikles | Tabata | |
|---|---|---|
| Serve pts wonthis match, clay | 61.1% | 57.8% |
| Return pts won | 42.2% | 38.9% |
| Hold servechance to win a service game | 75.8% | 68.8% |
What moves this game
- SurfaceClayratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setNikles 61%from both hold chances
- Match, set by setNikles 67%set by set, before calibration; published 64% after tempering toward 50%
Conditions
- Days since last event Not in the modelTabata 7, Nikles 35counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 75.1%
- First line
- –
- Latest
- 72.3%
Decimal odds 1.29 / 3.37, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| De La Fuente | Sanchez Jover | |
|---|---|---|
| Serve pts won, clay% | 52.1396th of 402 | 54.9360th of 402 |
| Return pts won, clay% | 32.0298th of 402 | 35.5126th of 402 |
| Clay rating% pts vs avg | 42.08379th of 402 | 45.21282nd of 402 |
| All-surface rating% pts vs avg | 41.55528th of 570 | 44.77368th of 570 |
| Wins, last 10 | 4 | 4 |
| Matches, 12 months | 22 | 44 |
| Matches rated | 63 | 189 |
Serve and return
| De La Fuente | Sanchez Jover | |
|---|---|---|
| Serve pts wonthis match, clay | 52.8% | 59.1% |
| Return pts won | 40.9% | 47.2% |
| Hold servechance to win a service game | 57.1% | 71.7% |
What moves this game
- SurfaceClayratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setSanchez Jover 71%from both hold chances
- Match, set by setSanchez Jover 80%set by set, before calibration; published 75% after tempering toward 50%
Conditions
- Days since last event Not in the modelSanchez Jover 21, De La Fuente 147counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 82.7%
- First line
- –
- Latest
- 81.4%
Decimal odds 1.13 / 4.93, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Gomez | Roncadelli | |
|---|---|---|
| Serve pts won, clay% | 51.4399th of 402 | 54.7365th of 402 |
| Return pts won, clay% | 31.7320th of 402 | 37.060th of 402 |
| Clay rating% pts vs avg | 41.55387th of 402 | 45.87250th of 402 |
| All-surface rating% pts vs avg | 40.92546th of 570 | 45.29329th of 570 |
| Wins, last 10 | 2 | 4 |
| Matches, 12 months | 15 | 54 |
| Matches rated | 109 | 128 |
Serve and return
| Gomez | Roncadelli | |
|---|---|---|
| Serve pts wonthis match, clay | 50.7% | 59.3% |
| Return pts won | 40.7% | 49.3% |
| Hold servechance to win a service game | 51.7% | 72.1% |
What moves this game
- SurfaceClayratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setRoncadelli 78%from both hold chances
- Match, set by setRoncadelli 87%set by set, before calibration; published 83% after tempering toward 50%
Conditions
- Days since last event Not in the modelRoncadelli 7, Gomez 126counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 63.2%
- First line
- –
- Latest
- 64.1%
Decimal odds 1.45 / 2.59, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Neumayer | Tabur | |
|---|---|---|
| Serve pts won, hard% | 60.3241st of 472 | 63.3118th of 472 |
| Return pts won, hard% | 33.6195th of 472 | 34.4153rd of 472 |
| Hard rating% pts vs avg | 46.92216th of 472 | 48.81120th of 472 |
| All-surface rating% pts vs avg | 47.27196th of 570 | 48.62131st of 570 |
| Wins, last 10 | 6 | 5 |
| Matches, 12 months | 50 | 55 |
| Matches rated | 247 | 223 |
Serve and return
| Neumayer | Tabur | |
|---|---|---|
| Serve pts wonthis match, hard | 62.0% | 65.3% |
| Return pts won | 34.7% | 38.0% |
| Hold servechance to win a service game | 77.5% | 83.4% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setTabur 61%from both hold chances
- Match, set by setTabur 66%set by set, before calibration; published 63% after tempering toward 50%
Conditions
- AgeTabur 26.8, Neumayer 24.2small age adjustment to serve
- Days since last event Not in the modelTabur 14, Neumayer 14counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 65.0%
- First line
- –
- Latest
- 73.2%
Decimal odds 3.44 / 1.26, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Gentzsch | Houkes | |
|---|---|---|
| Serve pts won, hard% | 61.1201st of 472 | 57.3 |
| Return pts won, hard% | 31.8306th of 472 | 32.4 |
| Hard rating% pts vs avg | 46.42246th of 472 | 44.87 |
| All-surface rating% pts vs avg | 46.94223rd of 570 | 45.73305th of 570 |
| Wins, last 10 | 6 | 5 |
| Matches, 12 months | 61 | 32 |
| Matches rated | 124 | 138 |
Serve and return
| Gentzsch | Houkes | |
|---|---|---|
| Serve pts wonthis match, hard | 64.9% | 61.1% |
| Return pts won | 38.9% | 35.1% |
| Hold servechance to win a service game | 82.8% | 75.8% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setGentzsch 62%from both hold chances
- Match, set by setGentzsch 68%set by set, before calibration; published 65% after tempering toward 50%
Conditions
- Days since last event Not in the modelHoukes 21, Gentzsch 7counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 83.5%
- First line
- –
- Latest
- 78.0%
Decimal odds 1.17 / 4.15, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Zeitune | Jarry | |
|---|---|---|
| Serve pts won, clay% | 58.1251st of 402 | 65.537th of 402 |
| Return pts won, clay% | 29.6378th of 402 | 32.7274th of 402 |
| Clay rating% pts vs avg | 43.85343rd of 402 | 49.1095th of 402 |
| All-surface rating% pts vs avg | 43.36460th of 570 | 48.57135th of 570 |
| Wins, last 10 | 2 | 4 |
| Matches, 12 months | 28 | 14 |
| Matches rated | 42 | 541 |
Serve and return
| Zeitune | Jarry | |
|---|---|---|
| Serve pts wonthis match, clay | 61.7% | 71.4% |
| Return pts won | 28.6% | 38.3% |
| Hold servechance to win a service game | 77.0% | 91.7% |
What moves this game
- SurfaceClayratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setJarry 79%from both hold chances
- Match, set by setJarry 88%set by set, before calibration; published 83% after tempering toward 50%
Conditions
- Days since last event Not in the modelJarry 14, Zeitune 7counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 75.7%
- First line
- –
- Latest
- 82.5%
Decimal odds 1.02 / 4.80, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Magadan | Misolic | |
|---|---|---|
| Serve pts won, clay% | 56.4320th of 402 | 59.9198th of 402 |
| Return pts won, clay% | 31.6324th of 402 | 34.8159th of 402 |
| Clay rating% pts vs avg | 43.99335th of 402 | 47.32177th of 402 |
| All-surface rating% pts vs avg | 44.16409th of 570 | 46.57250th of 570 |
| Wins, last 10 | 4 | 4 |
| Matches, 12 months | 27 | 13 |
| Matches rated | 51 | 252 |
Serve and return
| Magadan | Misolic | |
|---|---|---|
| Serve pts wonthis match, clay | 58.1% | 64.8% |
| Return pts won | 35.2% | 41.9% |
| Hold servechance to win a service game | 69.6% | 82.7% |
What moves this game
- SurfaceClayratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setMisolic 72%from both hold chances
- Match, set by setMisolic 80%set by set, before calibration; published 76% after tempering toward 50%
Conditions
- AgeMisolic 25.3, Magadan 25.5small age adjustment to serve
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 76.2%
- First line
- –
- Latest
- 83.2%
Decimal odds 1.12 / 5.55, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Hudd | Legout | |
|---|---|---|
| Serve pts won, hard% | 57.5362nd of 472 | 58.8301st of 472 |
| Return pts won, hard% | 30.2386th of 472 | 35.776th of 472 |
| Hard rating% pts vs avg | 43.85387th of 472 | 47.24197th of 472 |
| All-surface rating% pts vs avg | 43.50450th of 570 | 46.96219th of 570 |
| Wins, last 10 | 4 | 5 |
| Matches, 12 months | 16 | 19 |
| Matches rated | 29 | 45 |
Serve and return
| Hudd | Legout | |
|---|---|---|
| Serve pts wonthis match, hard | 57.4% | 64.2% |
| Return pts won | 35.8% | 42.6% |
| Hold servechance to win a service game | 67.8% | 81.5% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setLegout 72%from both hold chances
- Match, set by setLegout 81%set by set, before calibration; published 76% after tempering toward 50%
Conditions
- Days since last event Not in the modelLegout 14, Hudd 77counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 85.8%
- First line
- –
- Latest
- 74.9%
Decimal odds 1.26 / 3.76, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Dahlin | Etcheverry | |
|---|---|---|
| Serve pts won, hard% | 60.8 | 67.234th of 472 |
| Return pts won, hard% | 28.4 | 34.1168th of 472 |
| Hard rating% pts vs avg | 44.59 | 50.6748th of 472 |
| All-surface rating% pts vs avg | 45.04 | 50.5054th of 570 |
| Wins, last 10 | 3 | 3 |
| Matches, 12 months | 6 | 55 |
| Matches rated | 8 | 446 |
Serve and return
| Dahlin | Etcheverry | |
|---|---|---|
| Serve pts wonthis match, hard | 63.3% | 74.3% |
| Return pts won | 25.7% | 36.7% |
| Hold servechance to win a service game | 80.1% | 94.4% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelTour
- DrawMain draw
- Chance to win a setEtcheverry 81%from both hold chances
- Match, set by setEtcheverry 90%set by set, before calibration; published 86% after tempering toward 50%
Conditions
- AgeEtcheverry 27.3, Dahlin 20.9small age adjustment to serve
- Surface switchDahlin from claygames projection only, not the win chance
- Days since last event Not in the modelEtcheverry 4, Dahlin 84counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 78.9%
- First line
- –
- Latest
- 82.8%
Decimal odds 1.11 / 5.36, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Strombachs | Kouame | |
|---|---|---|
| Serve pts won, hard% | 58.9295th of 472 | 59.4274th of 472 |
| Return pts won, hard% | 28.8428th of 472 | 34.5143rd of 472 |
| Hard rating% pts vs avg | 43.86386th of 472 | 46.95213th of 472 |
| All-surface rating% pts vs avg | 43.58444th of 570 | 46.81232nd of 570 |
| Wins, last 10 | 3 | 6 |
| Matches, 12 months | 14 | 41 |
| Matches rated | 105 | 47 |
Serve and return
| Strombachs | Kouame | |
|---|---|---|
| Serve pts wonthis match, hard | 60.0% | 67.8% |
| Return pts won | 32.2% | 40.0% |
| Hold servechance to win a service game | 73.5% | 87.3% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setKouame 74%from both hold chances
- Match, set by setKouame 84%set by set, before calibration; published 79% after tempering toward 50%
Conditions
- Days since last event Not in the modelKouame 6, Strombachs 56counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 84.7%
- First line
- –
- Latest
- 87.3%
Decimal odds 1.07 / 7.36, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Pellegrino | Bonzi | |
|---|---|---|
| Serve pts won, hard% | 58.5 | 65.067th of 472 |
| Return pts won, hard% | 32.1 | 35.778th of 472 |
| Hard rating% pts vs avg | 45.34 | 50.3460th of 472 |
| All-surface rating% pts vs avg | 47.09210th of 570 | 50.2961st of 570 |
| Wins, last 10 | 3 | 4 |
| Matches, 12 months | 45 | 59 |
| Matches rated | 484 | 516 |
Serve and return
| Pellegrino | Bonzi | |
|---|---|---|
| Serve pts wonthis match, hard | 58.0% | 67.8% |
| Return pts won | 32.2% | 42.0% |
| Hold servechance to win a service game | 69.2% | 87.3% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setBonzi 80%from both hold chances
- Match, set by setBonzi 89%set by set, before calibration; published 85% after tempering toward 50%
Conditions
- AgeBonzi 30.4, Pellegrino 29.6small age adjustment to serve
- Surface switchPellegrino from claygames projection only, not the win chance
- Days since last event Not in the modelBonzi 6, Pellegrino 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 95.8%
- First line
- –
- Latest
- 87.6%
Decimal odds 7.60 / 1.08, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Samuel | Borg | |
|---|---|---|
| Serve pts won, hard% | 63.4112th of 472 | 55.3 |
| Return pts won, hard% | 37.136th of 472 | 28.8 |
| Hard rating% pts vs avg | 50.2662nd of 472 | 42.06 |
| All-surface rating% pts vs avg | 49.8478th of 570 | 41.78 |
| Wins, last 10 | 4 | 3 |
| Matches, 12 months | 61 | 3 |
| Matches rated | 94 | 49 |
Serve and return
| Samuel | Borg | |
|---|---|---|
| Serve pts wonthis match, hard | 70.6% | 54.3% |
| Return pts won | 45.7% | 29.4% |
| Hold servechance to win a service game | 90.8% | 60.8% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelTour
- DrawMain draw
- Chance to win a setSamuel 92%from both hold chances
- Match, set by setSamuel 98%set by set, before calibration; published 96% after tempering toward 50%
Conditions
- AgeBorg 23.5, Samuel 24.2small age adjustment to serve
- Days since last event Not in the modelBorg 350, Samuel 7counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 62.8%
- First line
- –
- Latest
- 64.7%
Decimal odds 1.42 / 2.60, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Boyer | Dellien | |
|---|---|---|
| Serve pts won, clay% | 59.9193rd of 402 | 61.5133rd of 402 |
| Return pts won, clay% | 34.7161st of 402 | 37.743rd of 402 |
| Clay rating% pts vs avg | 47.32176th of 402 | 49.5978th of 402 |
| All-surface rating% pts vs avg | 47.25197th of 570 | 48.92119th of 570 |
| Wins, last 10 | 5 | 8 |
| Matches, 12 months | 38 | 64 |
| Matches rated | 212 | 578 |
Serve and return
| Boyer | Dellien | |
|---|---|---|
| Serve pts wonthis match, clay | 58.7% | 61.9% |
| Return pts won | 38.1% | 41.3% |
| Hold servechance to win a service game | 70.8% | 77.3% |
What moves this game
- SurfaceClayratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setDellien 61%from both hold chances
- Match, set by setDellien 66%set by set, before calibration; published 63% after tempering toward 50%
Conditions
- AgeDellien 33.4, Boyer 25.6small age adjustment to serve
- Surface switchBoyer from hardgames projection only, not the win chance
- Days since last event Not in the modelDellien 14, Boyer 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 72.8%
- First line
- –
- Latest
- 68.7%
Decimal odds 2.92 / 1.33, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Alcala Gurri | Mena | |
|---|---|---|
| Serve pts won, clay% | 57.9258th of 402 | 59.9 |
| Return pts won, clay% | 39.217th of 402 | 32.8 |
| Clay rating% pts vs avg | 48.57119th of 402 | 46.37 |
| All-surface rating% pts vs avg | 48.05161st of 570 | 45.77 |
| Wins, last 10 | 7 | – |
| Matches, 12 months | 45 | – |
| Matches rated | 102 | 414 |
Serve and return
| Alcala Gurri | Mena | |
|---|---|---|
| Serve pts wonthis match, clay | 61.3% | 55.6% |
| Return pts won | 44.4% | 38.7% |
| Hold servechance to win a service game | 76.3% | 63.8% |
What moves this game
- SurfaceClayratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setAlcala Gurri 69%from both hold chances
- Match, set by setAlcala Gurri 77%set by set, before calibration; published 73% after tempering toward 50%
Conditions
- Days since last event Not in the modelMena 21, Alcala Gurri 21counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 53.9%
- First line
- –
- Latest
- 51.6%
Decimal odds 1.80 / 1.92, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Gueymard Wayenburg | Budkov Kjaer | |
|---|---|---|
| Serve pts won, hard% | 62.1154th of 472 | 61.1199th of 472 |
| Return pts won, hard% | 32.8241st of 472 | 33.7189th of 472 |
| Hard rating% pts vs avg | 47.47182nd of 472 | 47.36187th of 472 |
| All-surface rating% pts vs avg | 46.95221st of 570 | 47.20203rd of 570 |
| Wins, last 10 | 6 | 6 |
| Matches, 12 months | 56 | 53 |
| Matches rated | 164 | 135 |
Serve and return
| Gueymard Wayenburg | Budkov Kjaer | |
|---|---|---|
| Serve pts wonthis match, hard | 64.0% | 65.0% |
| Return pts won | 35.0% | 36.0% |
| Hold servechance to win a service game | 81.3% | 83.0% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setBudkov Kjaer 53%from both hold chances
- Match, set by setBudkov Kjaer 55%set by set, before calibration; published 54% after tempering toward 50%
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 56.8%
- First line
- –
- Latest
- 53.8%
Decimal odds 1.99 / 1.71, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Rehberg | Svajda | |
|---|---|---|
| Serve pts won, hard% | 61.4 | 58.1336th of 472 |
| Return pts won, hard% | 32.5 | 33.7187th of 472 |
| Hard rating% pts vs avg | 46.95 | 45.88278th of 472 |
| All-surface rating% pts vs avg | 46.97 | 45.64309th of 570 |
| Wins, last 10 | – | 2 |
| Matches, 12 months | – | 16 |
| Matches rated | 180 | 59 |
Serve and return
| Rehberg | Svajda | |
|---|---|---|
| Serve pts wonthis match, hard | 63.9% | 62.3% |
| Return pts won | 37.7% | 36.1% |
| Hold servechance to win a service game | 81.2% | 78.1% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setRehberg 56%from both hold chances
- Match, set by setRehberg 58%set by set, before calibration; published 57% after tempering toward 50%
Conditions
- AgeSvajda 20.6, Rehberg 23.2small age adjustment to serve
- Surface switchRehberg from claygames projection only, not the win chance
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →
How we got this
Model vs market
- Model
- 70.9%
- First line
- –
- Latest
- 74.6%
Decimal odds 1.24 / 3.64, bookmaker margin removed
- Latest
- Tennis Explorer odds when the prediction was made
Against closing lines in past seasons, these models showed no edge. Model vs market record →
Head to head
| Chan | Draxl | |
|---|---|---|
| Serve pts won, hard% | 58.5321st of 472 | 60.2244th of 472 |
| Return pts won, hard% | 31.2346th of 472 | 35.497th of 472 |
| Hard rating% pts vs avg | 44.82334th of 472 | 47.82162nd of 472 |
| All-surface rating% pts vs avg | 44.67373rd of 570 | 47.58177th of 570 |
| Wins, last 10 | 3 | 6 |
| Matches, 12 months | 12 | 56 |
| Matches rated | 24 | 223 |
Serve and return
| Chan | Draxl | |
|---|---|---|
| Serve pts wonthis match, hard | 59.6% | 65.0% |
| Return pts won | 35.0% | 40.4% |
| Hold servechance to win a service game | 72.8% | 82.9% |
What moves this game
- SurfaceHardratings blend this surface with all surfaces
- FormatBest of 3
- LevelATP Challenger
- Chance to win a setDraxl 67%from both hold chances
- Match, set by setDraxl 75%set by set, before calibration; published 71% after tempering toward 50%
Conditions
- AgeDraxl 24.9, Chan 21.3small age adjustment to serve
- Days since last event Not in the modelDraxl 7, Chan 42counted from event start dates
Model V4 · data as of · Sources: TennisMyLife (TML) match database, Jeff Sackmann ATP archive, tennisexplorer.com schedule. How the models work →