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.
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.
| Reading | Alexander Bublik | Karen Khachanov |
|---|---|---|
| Opening consensus | 61% | 39% |
| Latest consensus | 56% | 44% |
| Court Shark model | 45% | 55% |
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.
| Total games | Chance |
|---|---|
| 15 | 0.8% |
| 16 | 1.5% |
| 17 | 3.6% |
| 18 | 4.6% |
| 19 | 7.3% |
| 20 | 7.4% |
| 21 | 4.7% |
| 22 | 10.3% |
| 23 | 9.4% |
| 24 | 0.6% |
| 25 | 3.5% |
| 26 | 7.5% |
| 27 | 1.7% |
| 28 | 2.5% |
| 29 | 2.7% |
| 30 | 2.9% |
| 31 | 4.5% |
| 32 | 5.4% |
| 33 | 3.4% |
| 34 | 2.5% |
| 35 | 5.0% |
| 36 | 4.1% |
| 37 | 0.3% |
| 38 | 1.3% |
| 39 | 2.2% |
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.
| Measure | Alexander Bublik | Karen Khachanov |
|---|---|---|
| Wins, last 10 matches | 50% (5-5) | 70% (7-3) |
| Wins, last 10 on hard | 50% (5-5) | 70% (7-3) |
| Head-to-head wins | 50% (1-1) | 50% (1-1) |
| Model win probability | 45% | 55% |
Recent form
Article snapshot, Oct 22, 2026 · Not live
Each player's most recent completed matches, up to 10, oldest on the left.
| Player | Date | Result | Opponent | Score | Event |
|---|---|---|---|---|---|
| Alexander Bublik | Jul 25, 2026 | L | Quentin Halys | 4-6 6-7(6) | Kitzbuhel |
| Alexander Bublik | Aug 30, 2026 | W | J J Wolf | 6-4 6-2 3-6 6-1 | US Open |
| Alexander Bublik | Sep 2, 2026 | W | Adrian Mannarino | 6-3 6-1 6-1 | US Open |
| Alexander Bublik | Sep 4, 2026 | L | Tommy Paul | 4-6 6-3 7-6(4) 1-6 3-6 | US Open |
| Alexander Bublik | Sep 25, 2026 | L | Rafael Jodar | 2-6 3-6 | Laver Cup |
| Alexander Bublik | Oct 1, 2026 | L | Jakub Mensik | 4-6 6-7(5) | Beijing |
| Alexander Bublik | Oct 9, 2026 | W | Tomas Machac | 6-4 7-6(4) | Shanghai Masters |
| Alexander Bublik | Oct 11, 2026 | W | Brandon Nakashima | 6-7(7) 6-3 7-6(5) | Shanghai Masters |
| Alexander Bublik | Oct 13, 2026 | L | Alexander Zverev | 6-7(6) 6-4 6-7(1) | Shanghai Masters |
| Alexander Bublik | Oct 22, 2026 | W | Fabian Marozsan | 0-0 | ATP Almaty |
| Karen Khachanov | Sep 9, 2026 | W | Alexander Blockx | 6-2 7-5 3-2 RET | US Open |
| Karen Khachanov | Sep 11, 2026 | L | Alexander Zverev | 3-6 6-7(7) 6-7(6) | US Open |
| Karen Khachanov | Sep 30, 2026 | W | Felix Auger Aliassime | 6-3 6-3 | Beijing |
| Karen Khachanov | Oct 2, 2026 | W | Alex Molcan | 7-5 6-3 | Beijing |
| Karen Khachanov | Oct 4, 2026 | L | Hubert Hurkacz | 6-7(2) 2-6 | Beijing |
| Karen Khachanov | Oct 9, 2026 | W | Arthur Fery | 7-6(6) 6-7(5) 7-6(2) | Shanghai Masters |
| Karen Khachanov | Oct 11, 2026 | W | Adrian Mannarino | 6-2 6-4 | Shanghai Masters |
| Karen Khachanov | Oct 13, 2026 | L | Alex De Minaur | 3-6 4-6 | Shanghai Masters |
| Karen Khachanov | Oct 20, 2026 | W | Rei Sakamoto | 6-2 6-4 | ATP Almaty |
| Karen Khachanov | Oct 22, 2026 | W | Tomas Machac | 6-2 4-6 7-6(7) | ATP Almaty |
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.
| Surface | Alexander Bublik | Karen Khachanov |
|---|---|---|
| All surfaces | 1 | 1 |
| Hard | 0 | 1 |
| Grass | 1 | 0 |
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.
| Surface | Alexander Bublik | Karen Khachanov |
|---|---|---|
| Hard | 59% (16-11) | 53% (19-17) |
| Clay | 53% (8-7) | 50% (5-5) |
| Grass | 63% (5-3) | Too few matches (4) |
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.
| Measure | Alexander Bublik | Karen Khachanov | Tour average, all years |
|---|---|---|---|
| Service games held | 87% | 87% | 77% |
| Return games broken | 16% | 20% | 23% |
| Matches in sample | 27 | 36 |
Model win probability
Article snapshot, Oct 22, 2026 · Not live
The Court Shark model's chance for each player to win this match.
| Player | Win probability | Recent form (last 10) |
|---|---|---|
| Alexander Bublik | 45% | 5-5 |
| Karen Khachanov | 55% | 7-3 |
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%).
| Result | Chance |
|---|---|
| Alexander Bublik wins 2-0 | 26% |
| Alexander Bublik wins 2-1 | 19% |
| Karen Khachanov wins 2-1 | 21% |
| Karen Khachanov wins 2-0 | 34% |
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.
| Player | Return games won | Place |
|---|---|---|
| Alexander Bublik | 15.4% | 80th of 94 |
| Karen Khachanov | 20.7% | 32nd of 94 |
| Field median | 18.5% | |
| Field best (Daniel Merida Aguilar) | 30.7% | 1st |
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).
| Player | Start of window | Two-year peak | Latest |
|---|---|---|---|
| Alexander Bublik | 1873 (Oct 23, 2024) | 2131 (Feb 14, 2026) | 2023 (Oct 13, 2026) |
| Karen Khachanov | 1970 (Oct 23, 2024) | 2073 (Aug 7, 2025) | 1980 (Oct 13, 2026) |
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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