Grand Slam & Main Tour Tennis Picks — August 07, 2026

For Grand Slam & Main Tour Tennis picks August 07, 2026 you face a full slate of 20 matches spread across Grand Slams and main-tour events. The board shows a clear lean toward favorites, with five-star conviction clustered on the shortest prices and model edges above 70 percent. Standout plays include Felitsata Dorofeeva-Rybas at -1600 and Elena Rybakina at -650, both carrying the highest projected probabilities. Grand Slam & Main Tour Tennis picks today reward disciplined sizing on the top-rated selections while treating lower-confidence lines as smaller edges only.

Felitsata Dorofeeva-Rybas vs Charlotte Van Zonneveld — Felitsata Dorofeeva-Rybas ML

Take Felitsata Dorofeeva-Rybas at -1600. The model assigns her an 87 percent win probability in this Grand Slam match, reflecting a massive gap in current form and ranking. Charlotte Van Zonneveld has not shown the level needed to threaten at this price. The five-star rating and 87 percent model align on the heavy favorite.

Ann Li vs Elena Rybakina — Elena Rybakina ML

Back Elena Rybakina at -650. Her 83 percent model confidence in the Grand Slam underscores superior recent results and head-to-head dominance. Ann Li faces a steep climb against this level of serving and consistency. The five-star lean remains the clearest value on the board.

Maria Sakkari vs Coco Gauff — Coco Gauff ML

Play Coco Gauff at -425. The model edges her at 78 percent in this WTA match, driven by better movement and return metrics against Sakkari. Five-star status reflects the strong statistical mismatch on hard courts.

Mirra Andreeva vs Leylah Annie Fernandez — Mirra Andreeva ML

Take Mirra Andreeva at -325. The 74 percent model confidence in the Grand Slam stems from Andreeva’s superior ranking and recent surface results. Fernandez has struggled to close sets against top-20 opponents this season.

Zizou Bergs vs Ben Shelton — Ben Shelton ML

Back Ben Shelton at -300. His 73 percent model projection in the Grand Slam highlights a clear edge in power and first-serve percentage over Bergs. The five-star rating supports the market price.

Taylor Townsend vs Belinda Bencic — Belinda Bencic ML

Play Belinda Bencic at -300. The model gives her a 72 percent chance in the Grand Slam, citing stronger recent form and head-to-head history. Townsend’s variance makes the favorite the higher-probability side.

Daniel Merida Aguilar vs Alex Michelsen — Alex Michelsen ML

Take Alex Michelsen at -275. The 72 percent model confidence in the WTA 1000 event reflects Michelsen’s higher ranking and better hard-court metrics. Aguilar has yet to prove consistent at this level.

Elise Mertens vs Naomi Osaka — Naomi Osaka ML

Back Naomi Osaka at -260. Her 70 percent model edge in the Grand Slam is supported by superior power and experience against Mertens. The four-star rating aligns with the data.

Caty McNally vs Alexandra Eala — Alexandra Eala ML

Play Alexandra Eala at -250. The model projects 69 percent for Eala in the ATP 250, driven by recent ranking gains and surface comfort. McNally’s form has dipped against similar opponents.

Terence Atmane vs Jakub Mensik — Jakub Mensik ML

Take Jakub Mensik at -250. His 69 percent model confidence in the Grand Slam comes from better recent results and a favorable matchup against Atmane. The four-star lean is data-supported.

Botic van de Zandschulp vs Hubert Hurkacz — Hubert Hurkacz ML

Back Hubert Hurkacz at -240. The model assigns 68 percent probability in the Grand Slam, reflecting Hurkacz’s higher ranking and serve advantage. Van de Zandschulp has limited success in this matchup historically.

Maya Joint vs Liudmila Samsonova — Liudmila Samsonova ML

Play Liudmila Samsonova at -230. Her 68 percent model edge in the ATP 250 stems from stronger recent form and ranking. Joint remains an underdog on this surface.

Patrick Maloney vs Evan Zhu — Patrick Maloney ML

Take Patrick Maloney at -250. The 67 percent model confidence in the ATP event highlights Maloney’s ranking edge and recent results over Zhu. The four-star rating supports the lean.

Iva Jovic vs Alina Korneeva — Iva Jovic ML

Back Iva Jovic at -200. The model gives her 64 percent in the Grand Slam, citing better current form and head-to-head data. The three-star rating reflects a moderate but positive edge.

Ida Wobker vs Aurora Zantedeschi — Aurora Zantedeschi ML

Play Aurora Zantedeschi at -220. Her 64 percent model projection in the WTA match is based on ranking and recent surface performance. Wobker has shown limited success at this level.

Learner Tien vs Tommy Paul — Tommy Paul ML

Take Tommy Paul at -190. The 63 percent model confidence in the Grand Slam stems from Paul’s experience and head-to-head record. Tien remains a step below at this stage.

Tallon Griekspoor vs Matteo Arnaldi — Tallon Griekspoor ML

Back Tallon Griekspoor at -155. The model edges him at 59 percent in the Grand Slam due to slightly better recent results. The two-star rating indicates a modest lean only.

Carlos Taberner vs Elmer Moeller — Elmer Moeller ML

Play Elmer Moeller at -165. His 58 percent model projection in the Grand Slam reflects a narrow ranking advantage. The two-star rating keeps sizing small.

Casper Ruud vs Joao Fonseca — Joao Fonseca ML

Take Joao Fonseca at -145. The model gives him 57 percent in the Grand Slam, driven by recent momentum. The two-star lean is data-based but thin.

Alexei Popyrin vs Thiago Agustin Tirante — Alexei Popyrin ML

Back Alexei Popyrin at -135. His 56 percent model edge in the Grand Slam comes from a slight ranking and form advantage. The two-star rating signals limited conviction.

The overall board carries moderate-to-high conviction on the top 12 selections while the lower-rated matches offer smaller edges. Model probabilities remain estimates, not guarantees. Size bets according to your bankroll and only risk amounts you can afford to lose. Review each line independently before placing wagers.