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Court Shark Tennis Desk

Bublik vs Khachanov Prediction: Almaty Open 2026 Quarterfinal

Khachanov's recent form and return advantage support Court Shark's narrow preference, but Bublik's serve and deciding-set record explain a credible alternative.

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Alexander Bublik faces Karen Khachanov in the Almaty Open quarterfinal, with Court Shark's model giving Khachanov a 55% win probability. His recent form and return record support that narrow preference, while Bublik has the stronger case if service games dominate.

A semifinal place with little separating the favorites

Court Shark's model and the market differ by 11 percentage points on Karen Khachanov, enough to put them on opposite sides of his quarterfinal against Alexander Bublik. The disagreement concerns the favorite, not an overwhelming advantage. Khachanov's recent results support the model's reading, while Bublik's serve and broader hard-court record give substance to the opposing case. Neither case is decisive.

Friday's match in Almaty offers a semifinal place to players with contrasting histories at this tournament, where Khachanov previously won a title and Bublik had not. Khachanov went 5-1 in earlier main draws here; Bublik went 2-4. That history adds to Khachanov's case. The more useful distinction is whether his better return record can separate players whose service numbers have been almost identical.

Model and market on Alexander Bublik

Article snapshot, Oct 22, 2026 · Not live

Alexander Bublik's chance as the market consensus priced it from the opening line, next to the Court Shark model.

Alexander Bublik's chance to win
ReadingAlexander BublikKaren Khachanov
Opening consensus61%39%
Latest consensus56%44%
Court Shark model45%55%
Source: Court Shark model and pre-match market consensus.

Khachanov's return record meets Bublik's stronger broader results

The market opened with Bublik at 61% and subsequently moved five percentage points toward Khachanov. It still favors Bublik. That movement narrowed the disagreement with Court Shark's model without changing which player the market favored.

Khachanov went 7-3 over his latest ten matches, while Bublik went 5-5; their latest ten hard-court matches produced the same respective records. The surface-specific service figures offer a more direct matchup argument: both held 88% of service games over the last 52 weeks. With neither holding an advantage there, Khachanov's greater success on return becomes the clearest statistical reason to favor him.

Khachanov broke in 21% of return games, compared with Bublik's 16%. Those figures came from equally sized samples. Bublik nevertheless had a better hard-court winning record in the broader sample of matches with full statistics, an important counterweight to Khachanov's more favorable recent results.

Bublik's route runs through holds and a deciding set

Bublik's strongest route is to keep Khachanov from turning his return advantage into breaks, leaving the match dependent on a small number of points. His career deciding-set record offers support: he won 123 of 202. That strength becomes relevant if the players split sets.

Khachanov won 125 of 246 career deciding sets. The contrast favors Bublik. Extending the match would give Bublik a chance to draw on a part of his career record that compares favorably with Khachanov's.

Their head-to-head stood at 1-1, with the wins coming on different surfaces and years apart. Khachanov won their only hard-court meeting in Cincinnati in 2020, while Bublik won their latest meeting on grass in Halle. That is thin evidence. A match dominated by holds would strengthen Bublik's case; repeated return opportunities for Khachanov would make his recent surface record more relevant than their limited shared history.

The prediction

Court Shark's model narrowly favors Khachanov with a 55% win probability, while the market gives him 44%. The split is genuine. My reading favors Khachanov's return advantage over Bublik's stronger broader results, but it supports only a modest preference in a matchup between similarly effective servers.

Court Shark's AI analyst, which reads the matchup without the market, picks Bublik and disagrees with the model. His service strength and superior career deciding-set record offer concrete support for that choice. Court Shark's scoreline forecast gives Khachanov a 34% chance of winning in straight sets, the likeliest single result rather than a dominant outcome.

The forecast's median total is 24 games. Its middle half runs from 20 to 31 games, leaving room for either a compact result or an extended match. Khachanov's practical task is to make his return advantage count before Bublik can take the match into a deciding set.

How long it could go

Article snapshot, Oct 22, 2026 · Not live

A 58% chance the match lasts 20 to 31 games; 24 is the middle of the range.

Chance of each total number of games in the match
Total gamesChance
150.8%
161.5%
173.6%
184.6%
197.3%
207.4%
214.7%
2210.3%
239.4%
240.6%
253.5%
267.5%
271.7%
282.5%
292.7%
302.9%
314.5%
325.4%
333.4%
342.5%
355.0%
364.1%
370.3%
381.3%
392.2%
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 22, 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
MeasureAlexander BublikKaren Khachanov
Wins, last 10 matches50% (5-5)70% (7-3)
Wins, last 10 on hard50% (5-5)70% (7-3)
Head-to-head wins50% (1-1)50% (1-1)
Model win probability45%55%
Source: Court Shark model and match data.

Recent form

Article snapshot, Oct 22, 2026 · Not live

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

Recent results by player, oldest first
PlayerDateResultOpponentScoreEvent
Alexander BublikJul 25, 2026LQuentin Halys4-6 6-7(6)Kitzbuhel
Alexander BublikAug 30, 2026WJ J Wolf6-4 6-2 3-6 6-1US Open
Alexander BublikSep 2, 2026WAdrian Mannarino6-3 6-1 6-1US Open
Alexander BublikSep 4, 2026LTommy Paul4-6 6-3 7-6(4) 1-6 3-6US Open
Alexander BublikSep 25, 2026LRafael Jodar2-6 3-6Laver Cup
Alexander BublikOct 1, 2026LJakub Mensik4-6 6-7(5)Beijing
Alexander BublikOct 9, 2026WTomas Machac6-4 7-6(4)Shanghai Masters
Alexander BublikOct 11, 2026WBrandon Nakashima6-7(7) 6-3 7-6(5)Shanghai Masters
Alexander BublikOct 13, 2026LAlexander Zverev6-7(6) 6-4 6-7(1)Shanghai Masters
Alexander BublikOct 22, 2026WFabian Marozsan0-0ATP Almaty
Karen KhachanovSep 9, 2026WAlexander Blockx6-2 7-5 3-2 RETUS Open
Karen KhachanovSep 11, 2026LAlexander Zverev3-6 6-7(7) 6-7(6)US Open
Karen KhachanovSep 30, 2026WFelix Auger Aliassime6-3 6-3Beijing
Karen KhachanovOct 2, 2026WAlex Molcan7-5 6-3Beijing
Karen KhachanovOct 4, 2026LHubert Hurkacz6-7(2) 2-6Beijing
Karen KhachanovOct 9, 2026WArthur Fery7-6(6) 6-7(5) 7-6(2)Shanghai Masters
Karen KhachanovOct 11, 2026WAdrian Mannarino6-2 6-4Shanghai Masters
Karen KhachanovOct 13, 2026LAlex De Minaur3-6 4-6Shanghai Masters
Karen KhachanovOct 20, 2026WRei Sakamoto6-2 6-4ATP Almaty
Karen KhachanovOct 22, 2026WTomas Machac6-2 4-6 7-6(7)ATP Almaty
Source: Court Shark model and match data.

Head-to-head by surface

Article snapshot, Oct 22, 2026 · Not live

Alexander Bublik and Karen Khachanov have met 2 times. The record is level at 1-1.

Head-to-head record, Alexander Bublik first
SurfaceAlexander BublikKaren Khachanov
All surfaces11
Hard01
Grass10
Source: Court Shark model and match data.

Win rate by surface

Article snapshot, Oct 22, 2026 · Not live

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

Win rate by surface
SurfaceAlexander BublikKaren Khachanov
Hard59% (16-11)53% (19-17)
Clay53% (8-7)50% (5-5)
Grass63% (5-3)Too few matches (4)
Source: Court Shark model and match data.

Serve and return on hard courts

Article snapshot, Oct 22, 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
MeasureAlexander BublikKaren KhachanovTour average, all years
Service games held87%87%77%
Return games broken16%20%23%
Matches in sample2736
Source: Court Shark model and match data.

Model win probability

Article snapshot, Oct 22, 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)
Alexander Bublik45%5-5
Karen Khachanov55%7-3
Source: Court Shark model and match data.

Ways to win

Article snapshot, Oct 22, 2026 · Not live

Every way the match can finish. The likeliest single result is Karen Khachanov in straight sets (34%).

Chance of each final set score
ResultChance
Alexander Bublik wins 2-026%
Alexander Bublik wins 2-119%
Karen Khachanov wins 2-121%
Karen Khachanov wins 2-034%
Source: Court Shark model and match data.

Return games won: where they stand

Article snapshot, Oct 22, 2026 · Not live

Each dot is one of the ATP top 100 with enough matches in the last 52 weeks. Alexander Bublik is 80th of 94; Karen Khachanov is 32nd of 94.

Return games won, last 52 weeks, against the ATP top 100
PlayerReturn games wonPlace
Alexander Bublik15.4%80th of 94
Karen Khachanov20.7%32nd of 94
Field median18.5%
Field best (Daniel Merida Aguilar)30.7%1st
Source: Court Shark model and match data.

Two years of form

Article snapshot, Oct 22, 2026 · Not live

Each player's pre-match Elo rating since Oct 23, 2024. Latest: Alexander Bublik 2023 (Oct 13, 2026), Karen Khachanov 1980 (Oct 13, 2026).

Pre-match Elo rating over the last two years
PlayerStart of windowTwo-year peakLatest
Alexander Bublik1873 (Oct 23, 2024)2131 (Feb 14, 2026)2023 (Oct 13, 2026)
Karen Khachanov1970 (Oct 23, 2024)2073 (Aug 7, 2025)1980 (Oct 13, 2026)
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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