Grand Slam & Main Tour Tennis Picks — August 13, 2026

You’re reviewing a complete slate of 30 Grand Slam & Main Tour Tennis picks August 13, 2026. The board blends Grand Slam matches with WTA 1000 events and features clear model separation between favorites and underdogs. Five-star conviction plays stand out on Burcescu, Michelsen, Samsonova, Joint and Khachanov, each backed by at least 72% model probability. The overall lean favors the shorter-priced side in most contests, yet several plus-money opportunities still carry respectable model support. These Grand Slam & Main Tour Tennis picks today give you a data-driven framework for building your card around the highest-confidence edges.

Maia Ilinca Burcescu vs Patricia Georgiana Goina — Maia Ilinca Burcescu ML

Back Maia Ilinca Burcescu at -650. The five-star selection carries an 81% model rating, the highest on the board, and reflects a decisive edge in this Grand Slam matchup. The market price already prices in the heavy favoritism, yet the model still identifies meaningful value on the shorter side. Expect Burcescu to control the contest from the outset.

Jesper De Jong vs Alex Michelsen — Alex Michelsen ML

Take Alex Michelsen at -425. This five-star play shows a 78% model probability and stands out as one of the strongest leans of the day. Michelsen’s consistency and experience give him the clearer path in the Grand Slam setting. The price compresses value but the model edge remains firm.

Liudmila Samsonova vs Yulia Putintseva — Liudmila Samsonova ML

Play Liudmila Samsonova at -325. The five-star pick earns a 74% model rating and highlights a solid edge on the WTA 1000 surface. Samsonova’s recent form and serve metrics align with the model projection against Putintseva. The market line supports the lean without offering extreme value.

Tamara Korpatsch vs Maya Joint — Maya Joint ML

Back Maya Joint at -300. This five-star selection posts a 72% model probability in the WTA 1000 event. Joint’s aggressive baseline game creates a favorable matchup profile that the model quantifies clearly. The price remains reasonable relative to the projected win rate.

Karen Khachanov vs Aleksandar Kovacevic — Karen Khachanov ML

Take Karen Khachanov at -300. The five-star play registers a 72% model rating in this Grand Slam match. Khachanov’s experience and return game supply the primary edge the model identifies. The line reflects the favoritism while still leaving measurable value.

Jack Draper vs Martin Landaluce — Jack Draper ML

Play Jack Draper at -275. The four-star pick shows a 72% model probability in the Grand Slam. Draper’s all-court game and recent results drive the model edge against the younger Landaluce. The price sits at a level that still offers positive expected value.

Miomir Kecmanovic vs Camilo Ugo Carabelli — Miomir Kecmanovic ML

Back Miomir Kecmanovic at -275. This four-star selection carries a 71% model rating on the WTA 1000 surface. Kecmanovic’s steady baseline play aligns with the model projection. The market price supports the lean with modest but positive value.

Lois Boisson vs Ashlyn Krueger — Ashlyn Krueger ML

Take Ashlyn Krueger at -275. The four-star play earns a 71% model probability in the Grand Slam. Krueger’s power and recent form create the edge the model quantifies. The line compresses but still reflects a favorable projection.

Terence Atmane vs Marton Fucsovics — Terence Atmane ML

Play Terence Atmane at -220. This four-star selection posts a 67% model rating in the Grand Slam. Atmane’s current trajectory supplies the primary model edge. The price remains playable relative to the projected win probability.

Vincent Reisach vs Alessandro Spadola — Vincent Reisach ML

Back Vincent Reisach at -250. The four-star pick shows a 66% model probability in the Grand Slam. Reisach’s consistency drives the model lean against the plus-money opponent. The market line supports the directional bet.

Jakub Solarski vs Jan Chlodnicki — Jan Chlodnicki ML

Take Jan Chlodnicki at -250. This four-star selection registers a 66% model rating in the Grand Slam. Chlodnicki’s experience provides the edge the model identifies. The price offers a reasonable risk-reward profile.

Thanasi Kokkinakis vs Nuno Borges — Nuno Borges ML

Play Nuno Borges at -200. The three-star pick carries a 64% model probability in the Grand Slam. Borges’ recent results align with the model projection. The line reflects a modest but clear edge.

Dino Prizmic vs Cameron Norrie — Cameron Norrie ML

Back Cameron Norrie at -185. This three-star selection shows a 63% model rating in the Grand Slam. Norrie’s experience supplies the quantified edge. The price remains within acceptable value parameters.

Katerina Siniakova vs Maria Timofeeva — Katerina Siniakova ML

Take Katerina Siniakova at -185. The three-star play earns a 63% model probability in the Grand Slam. Siniakova’s veteran presence drives the model lean. The market line supports the directional preference.

Yuliia Starodubtseva vs Daria Snigur — Daria Snigur ML

Play Daria Snigur at -180. This three-star selection posts a 63% model rating in the Grand Slam. Snigur’s form metrics align with the model output. The price offers a workable edge.

Viktorija Golubic vs Alycia Parks — Viktorija Golubic ML

Back Viktorija Golubic at -175. The three-star pick registers a 62% model probability in the Grand Slam. Golubic’s consistency provides the model edge. The line reflects a modest favoritism.

Federico Cina vs Tristan Schoolkate — Federico Cina ML

Take Federico Cina at -180. This two-star selection shows a 61% model rating in the Grand Slam. Cina’s baseline game supplies the quantified lean. The price remains playable at current odds.

Mattia Bellucci vs Zachary Svajda — Zachary Svajda ML

Play Zachary Svajda at -170. The two-star pick carries a 60% model probability on the WTA 1000 surface. Svajda’s recent trajectory drives the model projection. The line offers limited but positive value.

Panna Udvardy vs Cristina Bucsa — Cristina Bucsa ML

Back Cristina Bucsa at -155. This two-star selection earns a 59% model rating in the Grand Slam. Bucsa’s experience aligns with the model edge. The price sits near the model’s implied probability.

Zeynep Sonmez vs Daria Kasatkina — Daria Kasatkina ML

Take Daria Kasatkina at -155. The two-star play posts a 59% model probability in the Grand Slam. Kasatkina’s consistency supplies the lean. The market line supports the directional bet.

Magdalena Frech vs Antonia Ruzic — Magdalena Frech ML

Play Magdalena Frech at -155. This two-star selection registers a 59% model rating in the Grand Slam. Frech’s form metrics align with the model output. The price reflects a modest edge.

Anna Bondar vs Jessica Bouzas Maneiro — Jessica Bouzas Maneiro ML

Back Jessica Bouzas Maneiro at -150. The two-star pick shows a 59% model probability in the Grand Slam. Maneiro’s recent results drive the projection. The line remains within value range.

Grigor Dimitrov vs Sebastian Baez — Grigor Dimitrov ML

Take Grigor Dimitrov at -150. This two-star selection carries a 58% model rating in the Grand Slam. Dimitrov’s experience provides the model edge. The price offers a reasonable lean.

Lorenzo Sonego vs Juncheng Shang — Juncheng Shang ML

Play Juncheng Shang at -155. The two-star pick earns a 58% model probability in the Grand Slam. Shang’s trajectory aligns with the model output. The line reflects modest favoritism.

Gael Monfils vs Rinky Hijikata — Gael Monfils ML

Back Gael Monfils at -155. This two-star selection posts a 58% model rating in the Grand Slam. Monfils’ veteran presence supplies the edge. The price sits near model expectations.

Magda Linette vs Elena-Gabriela Ruse — Elena-Gabriela Ruse ML

Take Elena-Gabriela Ruse at -145. The two-star play registers a 57% model probability in the Grand Slam. Ruse’s recent form drives the projection. The line offers limited value.

Raphael Collignon vs Mariano Navone — Raphael Collignon ML

Play Raphael Collignon at -145. This two-star selection shows a 57% model rating in the Grand Slam. Collignon’s consistency aligns with the model lean. The price remains playable.

Camila Osorio vs Taylor Townsend — Taylor Townsend ML

Back Taylor Townsend at -140. The two-star pick carries a 57% model probability in the Grand Slam. Townsend’s power game supplies the edge. The line reflects the model projection.

Petra Marcinko vs Simona Waltert — Petra Marcinko ML

Take Petra Marcinko at -140. This two-star selection earns a 56% model rating in the Grand Slam. Marcinko’s form metrics align with the model output. The price offers a narrow edge.

Mccartney Kessler vs Caty McNally — Caty McNally ML

Play Caty McNally at -145. The two-star pick posts a 56% model probability in the Grand Slam. McNally’s experience drives the lean. The line sits near the model’s implied probability.

The full board shows model edges between 56% and 81%, with the strongest conviction concentrated in the five-star tier. No outcome is guaranteed; these are probabilistic leans derived from available data. Size bets according to your bankroll and only risk amounts you can afford to lose. Review each line movement before placing wagers.