> ## Content Index
> Fetch the complete content index at: https://courtshark.ai/blog/llms.txt
> Use this file to discover other available public pages before exploring further.

# Bublik vs Khachanov Prediction: Almaty Open 2026 Quarterfinal
- URL: https://courtshark.ai/blog/bublik-vs-khachanov-almaty-open-2026-prediction/
- Published: 2026-10-22T19:29:03.000Z
- Updated: 2026-10-22T19:29:03.000Z
- Description: 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.
- Author: Court Shark Desk
- Tags: match-preview, Alexander Bublik, Karen Khachanov, Almaty Open 2026, Hard, ATP

In this analysis

1. [Key takeaway](#key-takeaway)
2. [A semifinal place with little separating the favorites](#s-a-semifinal-place-with-little-separating-the-favorites)
3. [Khachanov's return record meets Bublik's stronger broader results](#s-khachanov-s-return-record-meets-bublik-s-stronger-broader-re)
4. [Bublik's route runs through holds and a deciding set](#s-bublik-s-route-runs-through-holds-and-a-deciding-set)
5. [The prediction](#s-the-prediction)
6. [Explore this matchup](#explore)
7. [Methodology and sources](#methodology)

Key takeaway

Khachanov's better return record is the clearest support for the model's narrow preference. Bublik's equally strong serve and better career deciding-set record leave a credible route to the opposite result.

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](https://courtshark.ai/players/karen-khachanov-111575), enough to put them on opposite sides of his quarterfinal against [Alexander Bublik](https://courtshark.ai/players/alexander-bublik-122330). 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__
| Reading           | Alexander Bublik | Karen Khachanov |
| ----------------- | ---------------- | --------------- |
| Opening consensus | 61%              | 39%             |
| Latest consensus  | 56%              | 44%             |
| Court Shark model | 45%              | 55%             |

Source: Court Shark model and pre-match market consensus.View data table

## 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 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%   |

Source: Court Shark model and match data.View data table

## 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__
| 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%             |

Source: Court Shark model and match data.View data table

### 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__
| 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       |

Source: Court Shark model and match data.View data table

### 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__
| Surface      | Alexander Bublik | Karen Khachanov |
| ------------ | ---------------- | --------------- |
| All surfaces | 1                | 1               |
| Hard         | 0                | 1               |
| Grass        | 1                | 0               |

Source: Court Shark model and match data.View data table

### 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__
| 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) |

Source: Court Shark model and match data.View data table

### 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__
| 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              |                         |

Source: Court Shark model and match data.View data table

### 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__
| Player           | Win probability | Recent form (last 10) |
| ---------------- | --------------- | --------------------- |
| Alexander Bublik | 45%             | 5-5                   |
| Karen Khachanov  | 55%             | 7-3                   |

Source: Court Shark model and match data.View data table

### 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__
| 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%    |

Source: Court Shark model and match data.View data table

### 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__
| 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        |

Source: Court Shark model and match data.View data table

### 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__
| 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) |

Source: Court Shark model and match data.View data table

[Explore this matchup](https://courtshark.ai/h2h?p1=111575&p2=122330)

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

Our forecast

Court Shark's model

Karen Khachanov 55% to win

Match shape

Karen Khachanov in straight sets: 34%

Deciding set: 40%

Total games: median 24, middle half 20 to 31

AI analyst

Picks Alexander Bublik (disagrees with the model)

Its case: Alexander Bublik gets a narrow nod in home-country Almaty: the 848m indoor court has a 1.16 speed index, and his hard-court serve has produced a 15.4% ace rate and 77.5% first-serve points won, ideal conditions for his 196cm first-strike game after 10 days’ rest.

The risk it names: Karen Khachanov is the major risk, he is 7-3 in his latest 10 hard-court matches versus Bublik’s 4-6 and holds 83.9% of the time, but he needed 216 minutes across his last 2 matches, including a 7-6(7) deciding set yesterday.

Estimates recorded before play, not certainties.

Keep exploring

[Follow this match on Court Shark](https://courtshark.ai/matches?file=bdl%5F4728088)[Create a free account to keep it](https://courtshark.ai/register?redirect=%2Fmatches%3Ffile%3Dbdl%5F4728088)

Match context

Players

Alexander Bublik  
vs Karen Khachanov

Event

Almaty Open

Surface

Hard

Round

Quarterfinal

Date

Friday, October 23

Article snapshot · Not live

Continue your research

Compare form, explore surfaces and follow live match context.

[Explore Premium](https://courtshark.ai/register?redirect=/start-premium)[See what's included](https://courtshark.ai/premium)
- Advanced filters and splits
- Save your research
- Live context and updates

Related on Court Shark

- [How our match model works](https://courtshark.ai/blog/methodology/)
- [Open the full head-to-head](https://courtshark.ai/h2h?p1=111575&p2=122330)
- [Our editorial standards](https://courtshark.ai/blog/editorial-standards/)
- [About the desk](https://courtshark.ai/blog/about-the-desk/)

## 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.

About the desk

Who works on the Tennis Desk and how an article is put together. [Read about the desk](https://courtshark.ai/blog/about-the-desk/)

Editorial standards

What we publish, what we check and how we decide what is fit to print. [Read our standards](https://courtshark.ai/blog/editorial-standards/)

Corrections

Spotted an error? Write to hello@courtshark.ai and we will correct it and note the change. [Read the corrections policy](https://courtshark.ai/blog/editorial-standards/)