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Medvedev vs Aguilar Prediction: Erste Bank Open 2026 Round of 32

Medvedev's Erste Bank Open history supports his favorite status, but his hard-court serving advantage is the stronger reason to pick him against Merida Aguilar.

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Daniil Medvedev's Erste Bank Open record strengthens his case against Daniel Merida Aguilar in the round of 32, but his serving advantage matters more. Court Shark's model gives Medvedev a 70% chance to win.

A title and a winning tournament record

On July 1, Daniil Medvedev beat Daniel Merida Aguilar at Wimbledon, giving him a direct result to support his broader record of success at the Erste Bank Open. Medvedev had gone 12-4 at this tournament in earlier seasons. That history matters. It establishes repeated success at the event rather than familiarity based on a single appearance, although the Wimbledon meeting came on grass.

Sunday's round of 32 brings Medvedev back to a tournament where he had won a title across six seasons of main-draw appearances. For Merida Aguilar, this is an opportunity to reverse their earlier result, now on hard courts. Medvedev's tournament record supports confidence that the setting suits him, but it cannot isolate the effect of the conditions from the opponents he faced. The more useful test is whether his current hard-court results support the same conclusion.

Two years of form

Article snapshot, Oct 24, 2026 · Not live

Each player's pre-match Elo rating since Oct 30, 2024. Latest: Daniil Medvedev 2112 (Oct 22, 2026), Daniel Merida Aguilar 1966 (Oct 8, 2026).

Pre-match Elo rating over the last two years
PlayerStart of windowTwo-year peakLatest
Daniel Merida Aguilar1500 (Nov 9, 2024)1978 (Sep 4, 2026)1966 (Oct 8, 2026)
Daniil Medvedev2160 (Oct 30, 2024)2160 (Oct 30, 2024)2112 (Oct 22, 2026)
Source: Court Shark model and match data.

The serve gives the history present relevance

Over the last 52 weeks on hard courts, Medvedev held 86% of his service games. Merida Aguilar held 76% over the same window. The gap is substantial.

Their return records were identical: each broke in 29% of return games. That makes service protection the clearer distinction in this matchup, rather than an assumption that Medvedev will create markedly more chances against serve. Recent hard-court results also favored him: he won eight of his last 10, while Merida Aguilar won six over that span. My reading is that the tournament history reinforces this evidence, rather than supplying the main argument. Merida Aguilar's return record gives him a credible way into the match, but his own service games appear more vulnerable.

Return pressure and an uneven schedule

Merida Aguilar's route to an upset starts with making his return strength count while protecting serve better than his recent surface record suggests. He has beaten strong opposition. His US Open win over Andrey Rublev showed he could defeat a prominent opponent, although that result alone does not establish how he will handle Medvedev on Sunday. Their only previous meeting also leaves little direct evidence about this matchup on hard courts.

The schedule presents a different uncertainty. Medvedev played eight matches in the last 14 days, so accumulated workload is a plausible way his usual advantage could narrow. Merida Aguilar, by contrast, had gone 16 days without a match. That creates a rust risk rather than an automatic freshness advantage. If Medvedev's service protection drops and Merida Aguilar returns effectively from the start, the favorite could face pressure in the part of his game that otherwise separates them.

The prediction

Court Shark's model favors Medvedev with a 70% chance to win, while the market consensus puts him at 79%. Both favor the same player. The model is less emphatic; my reading is that Merida Aguilar's return record offers a reason to expect resistance despite Medvedev's advantage on serve.

Court Shark's AI analyst, which reads the matchup without the market, also picks Medvedev, agreeing with the model. His service advantage and repeated success at this event support that choice. Court Shark's scoreline forecast makes a Medvedev straight-sets win the likeliest single result at 48%, with a median total of 22 games.

The middle half of forecast outcomes runs from 18 to 28 games, leaving room for a competitive match rather than only a short favorite's win. Merida Aguilar's ability to protect his own service games is the immediate test of whether he can keep Medvedev within reach.

How long it could go

Article snapshot, Oct 24, 2026 · Not live

A 57% chance the match lasts 18 to 28 games; 22 is the middle of the range.

Chance of each total number of games in the match
Total gamesChance
130.7%
141.7%
153.7%
165.6%
178.0%
188.3%
198.3%
207.6%
215.3%
227.0%
234.9%
241.5%
253.4%
264.1%
273.2%
283.7%
293.9%
303.8%
313.9%
323.6%
332.3%
341.7%
351.9%
361.0%
380.4%
390.3%
Source: Court Shark model and match data.

Explore this matchup

Compare both players side by side: recent results, surfaces, serve and return.

Player comparison

Article snapshot, Oct 24, 2026 · Not live

Each measure on the same scale: recent wins, wins on this surface, head-to-head wins and the model's chance.

Player comparison
MeasureDaniel Merida AguilarDaniil Medvedev
Wins, last 10 matches60% (6-4)80% (8-2)
Wins, last 10 on hard60% (6-4)80% (8-2)
Head-to-head wins0% (0-1)100% (1-0)
Model win probability30%70%
Source: Court Shark model and match data.

Recent form

Article snapshot, Oct 24, 2026 · Not live

Each player's most recent completed matches, up to 10, oldest on the left.

Recent results by player, oldest first
PlayerDateResultOpponentScoreEvent
Daniel Merida AguilarAug 9, 2026WTallon Griekspoor6-3 6-1Canada Masters
Daniel Merida AguilarAug 11, 2026LLearner Tien3-6 2-6Canada Masters
Daniel Merida AguilarAug 14, 2026WMarin Cilic3-6 6-1 6-1Cincinnati Masters
Daniel Merida AguilarAug 16, 2026WZizou Bergs6-3 6-2Cincinnati Masters
Daniel Merida AguilarAug 18, 2026LTaylor Fritz3-6 4-6Cincinnati Masters
Daniel Merida AguilarAug 30, 2026WMarton Fucsovics6-4 6-4 6-2US Open
Daniel Merida AguilarSep 2, 2026WAndrey Rublev6-7(3) 6-2 6-4 6-4US Open
Daniel Merida AguilarSep 4, 2026LAlex Michelsen6-7(5) 4-6 3-6US Open
Daniel Merida AguilarSep 19, 2026WAlejandro Tabilo5-7 6-3 6-3Davis Cup QLS R2: ESP vs CHI
Daniel Merida AguilarOct 8, 2026LBotic Van De Zandschulp6-1 3-6 4-6Shanghai Masters
Daniil MedvedevOct 4, 2026WFrancisco Cerundolo7-6(4) 6-3Beijing
Daniil MedvedevOct 5, 2026LNovak DjokovicBeijing
Daniil MedvedevOct 10, 2026WJan Lennard Struff4-6 6-4 6-3Shanghai Masters
Daniil MedvedevOct 12, 2026WDalibor Svrcina6-2 6-3Shanghai Masters
Daniil MedvedevOct 14, 2026WStefanos Tsitsipas6-4 7-5Shanghai Masters
Daniil MedvedevOct 16, 2026WTommy Paul6-3 1-6 6-3Shanghai Masters
Daniil MedvedevOct 17, 2026LRafael Jodar3-6 4-6Shanghai Masters
Daniil MedvedevOct 22, 2026WSho Shimabukuro6-2 6-1ATP Almaty
Daniil MedvedevOct 23, 2026WTerence Atmane6-4 6-4ATP Almaty
Daniil MedvedevOct 24, 2026WAlexander Bublik6-3ATP Almaty
Source: Court Shark model and match data.

Head-to-head by surface

Article snapshot, Oct 24, 2026 · Not live

Daniel Merida Aguilar and Daniil Medvedev have met once. Daniil Medvedev leads 1-0.

Head-to-head record, Daniel Merida Aguilar first
SurfaceDaniel Merida AguilarDaniil Medvedev
All surfaces01
Grass01
Source: Court Shark model and match data.

Win rate by surface

Article snapshot, Oct 24, 2026 · Not live

Share of matches won on each surface across each player's last 50 matches with full statistics.

Win rate by surface
SurfaceDaniel Merida AguilarDaniil Medvedev
Hard59% (10-7)76% (25-8)
Clay73% (22-8)63% (5-3)
GrassToo few matches (3)67% (6-3)
Source: Court Shark model and match data.

Serve and return on hard courts

Article snapshot, Oct 24, 2026 · Not live

How often each player held serve and broke serve on hard over their last 50 matches with full statistics, against the tour's all-years average on the surface.

Hold and break rates on hard
MeasureDaniel Merida AguilarDaniil MedvedevTour average, all years
Service games held77%88%77%
Return games broken27%28%23%
Matches in sample1733
Source: Court Shark model and match data.

Model and market on Daniel Merida Aguilar

Article snapshot, Oct 24, 2026 · Not live

Daniel Merida Aguilar's chance as the market consensus priced it from the opening line, next to the Court Shark model.

Daniel Merida Aguilar's chance to win
ReadingDaniel Merida AguilarDaniil Medvedev
Opening consensus21%79%
Latest consensus21%79%
Court Shark model30%70%
Source: Court Shark model and pre-match market consensus.

Model win probability

Article snapshot, Oct 24, 2026 · Not live

The Court Shark model's chance for each player to win this match.

Model win probability by player
PlayerWin probabilityRecent form (last 10)
Daniel Merida Aguilar30%6-4
Daniil Medvedev70%8-2
Source: Court Shark model and match data.

Ways to win

Article snapshot, Oct 24, 2026 · Not live

Every way the match can finish. The likeliest single result is Daniil Medvedev in straight sets (48%).

Chance of each final set score
ResultChance
Daniel Merida Aguilar wins 2-016%
Daniel Merida Aguilar wins 2-114%
Daniil Medvedev wins 2-122%
Daniil Medvedev wins 2-048%
Source: Court Shark model and match data.

Service games held: where they stand

Article snapshot, Oct 24, 2026 · Not live

Each dot is one of the ATP top 100 with enough matches in the last 52 weeks. Daniel Merida Aguilar is 78th of 94; Daniil Medvedev is 30th of 94.

Service games held, last 52 weeks, against the ATP top 100
PlayerService games heldPlace
Daniel Merida Aguilar77.4%78th of 94
Daniil Medvedev84.4%30th of 94
Field median81.8%
Field best (Jannik Sinner)94.6%1st
Source: Court Shark model and match data.
Explore this matchup

Court Shark win probabilities are statistical estimates, not advice. No outcome is guaranteed.

Methodology and sources

How we build model estimates and where our information comes from.

Model estimates and observed results

The win probabilities come from the Court Shark match model, trained on completed ATP and WTA matches. A probability says how often a player in this position wins, not that one result will happen. The model's number for a match is recorded before play and never changed afterwards, so it can be checked against the result.

Sources and citations

Results, scores, rankings and serve statistics come from the Court Shark match database. The market consensus is the pre-match price for each player converted to a probability. Figures in this article are a snapshot taken when it was written.

Limitations

Serve and return rates count only matches with full serve statistics, which are sparser for Challenger and lower-level events, and the tour average they are compared with covers every year on record. Head-to-head records count every meeting with a recorded winner, walkovers and retirements included. Charts and tables are a snapshot and do not update after publication.

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