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Court Shark Tennis Desk

Khachanov vs Machac Prediction: Almaty Open 2026 Round of 16

Khachanov's Almaty title matters, but his hard-court serving advantage makes the stronger case against Machac.

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Karen Khachanov's Almaty Open record strengthens his case against Tomas Machac in the round of 16, though his serving advantage is more persuasive. Court Shark's model gives Khachanov a 71% chance.

Khachanov has won here before

The winner when Tomas Machac meets Karen Khachanov in Thursday's Almaty Open round of 16 reaches the quarterfinals. Khachanov's tournament record supports his position as favorite, but it is evidence of past success in these conditions rather than a decisive argument against this opponent. He won a title here. His earlier main-draw record stood at 5-1 across three seasons, a meaningful contrast with Machac's much shorter history at the event.

Machac's previous appearance produced a 1-1 record and no title, so this meeting puts a former champion against a player with little established tournament history. Both won their opening matches this week. That makes Khachanov's experience relevant to the next step in the draw, although those earlier results alone cannot establish how the court will affect this particular matchup.

Two years of form

Article snapshot, Oct 21, 2026 · Not live

Each player's pre-match Elo rating since Oct 23, 2024. Latest: Karen Khachanov 1980 (Oct 13, 2026), Tomas Machac 1900 (Oct 9, 2026).

Pre-match Elo rating over the last two years
PlayerStart of windowTwo-year peakLatest
Tomas Machac2003 (Oct 23, 2024)2049 (Mar 7, 2025)1900 (Oct 9, 2026)
Karen Khachanov1970 (Oct 23, 2024)2073 (Aug 7, 2025)1980 (Oct 13, 2026)
Source: Court Shark model and match data.

The serving gap gives the history substance

The stronger reason to favor Khachanov comes from his service record on hard courts over the past 52 weeks, rather than from his trophy alone. He held 87% of his service games. That is a substantial base for a favorite, because it leaves an opponent fewer opportunities to turn a competitive set into a lead. Machac held 79% of his service games over the same window, making protection of his own serve a more pressing concern.

Recent results point the same way. Khachanov went 7-3 in his latest hard-court matches, while Machac went 5-5, so the tournament history is supported by a current difference in results. This is not simply a choice between a former champion and a visitor. The broader surface evidence gives a tennis reason to expect Khachanov's comfort here to matter against Machac, rather than treating familiarity itself as an advantage.

Close sets offer Machac a route

Machac's clearest opening is to keep the sets close enough that Khachanov's stronger service record does not produce a comfortable advantage on the scoreboard. Khachanov broke in 21% of his hard-court return games during the same window. The tour benchmark was 23%. His return was less imposing. If Machac protects serve more effectively than his recent record suggests, Khachanov may have to settle sets without the cushion of an early break.

Machac also won 83 of 142 career tiebreaks, which gives him a credible route if neither player creates much separation on return. Those are career results, not a forecast for this court. Their only previous meeting ended in Khachanov's favor at the Australian Open, but it included two tiebreaks and a set won by Machac. That single encounter supports the favorite without establishing that this opponent is easy for him to beat.

The prediction

Court Shark's model gives Khachanov a 71% win probability, compared with the market consensus of 67%. Both favor Khachanov. The difference is modest, and the case for him is stronger when his tournament success is considered alongside his hard-court serving advantage rather than on its own.

Court Shark's AI analyst, which reads the matchup without the market, also picks Khachanov, agreeing with the model on the strength of his serve and recent results. The model gives a Khachanov straight-sets win a 49% chance. Its median match length is 23 games, suggesting that a win without dropping a set need not mean an especially short match.

The middle half of projected outcomes runs from 19 to 30 games. Machac's career tiebreak record makes Khachanov's ability to create return chances especially important if the sets stay level.

Ways to win

Article snapshot, Oct 21, 2026 · Not live

Every way the match can finish. The likeliest single result is Karen Khachanov in straight sets (49%).

Chance of each final set score
ResultChance
Tomas Machac wins 2-015%
Tomas Machac wins 2-114%
Karen Khachanov wins 2-122%
Karen Khachanov wins 2-049%
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 21, 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
MeasureTomas MachacKaren Khachanov
Wins, last 10 matches50% (5-5)70% (7-3)
Wins, last 10 on hard50% (5-5)70% (7-3)
Head-to-head wins0% (0-1)100% (1-0)
Model win probability29%71%
Source: Court Shark model and match data.

Recent form

Article snapshot, Oct 21, 2026 · Not live

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

Recent results by player, oldest first
PlayerDateResultOpponentScoreEvent
Tomas MachacAug 30, 2026LToby Samuel2-6 3-6 2-6US Open
Tomas MachacSep 28, 2026WYannick Hanfmann7-6(7) 6-7(6) 6-4Beijing
Tomas MachacSep 29, 2026LArthur Gea3-6 4-6Beijing
Tomas MachacOct 1, 2026LAlex Molcan3-6 2-6Beijing
Tomas MachacOct 7, 2026WZhizhen Zhang1-6 7-6(3) 6-2Shanghai Masters
Tomas MachacOct 9, 2026LAlexander Bublik4-6 6-7(4)Shanghai Masters
Tomas MachacOct 13, 2026WAlexandre Muller6-3 6-4Jinan Challenger
Tomas MachacOct 15, 2026WAleksandar Vukic6-2 6-1Jinan Challenger
Tomas MachacOct 16, 2026LLiam Draxl4-6 6-3 4-6Jinan Challenger
Tomas MachacOct 21, 2026WZangar Nurlanuly6-2 6-0ATP Almaty
Karen KhachanovSep 7, 2026WLearner Tien7-5 4-6 6-7(6) 6-1 6-4US Open
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
Source: Court Shark model and match data.

Head-to-head by surface

Article snapshot, Oct 21, 2026 · Not live

Tomas Machac and Karen Khachanov have met once. Karen Khachanov leads 1-0.

Head-to-head record, Tomas Machac first
SurfaceTomas MachacKaren Khachanov
All surfaces01
Hard01
Source: Court Shark model and match data.

Win rate by surface

Article snapshot, Oct 21, 2026 · Not live

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

Win rate by surface
SurfaceTomas MachacKaren Khachanov
Hard46% (16-19)50% (18-18)
Clay50% (5-5)50% (5-5)
Grass60% (3-2)Too few matches (4)
Source: Court Shark model and match data.

Serve and return on hard courts

Article snapshot, Oct 21, 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
MeasureTomas MachacKaren KhachanovTour average, all years
Service games held80%87%77%
Return games broken19%20%23%
Matches in sample3536
Source: Court Shark model and match data.

Model and market on Tomas Machac

Article snapshot, Oct 21, 2026 · Not live

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

Tomas Machac's chance to win
ReadingTomas MachacKaren Khachanov
Opening consensus33%67%
Latest consensus33%67%
Court Shark model29%71%
Source: Court Shark model and pre-match market consensus.

Model win probability

Article snapshot, Oct 21, 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)
Tomas Machac29%5-5
Karen Khachanov71%7-3
Source: Court Shark model and match data.

How long it could go

Article snapshot, Oct 21, 2026 · Not live

A 60% chance the match lasts 19 to 30 games; 23 is the middle of the range.

Chance of each total number of games in the match
Total gamesChance
130.2%
140.6%
151.8%
163.1%
175.9%
186.8%
198.4%
208.1%
215.4%
229.3%
237.6%
240.8%
253.2%
265.4%
272.2%
282.8%
293.1%
303.2%
314.3%
324.6%
332.9%
342.1%
353.5%
362.5%
370.2%
380.8%
391.0%
Source: Court Shark model and match data.

Service games held: where they stand

Article snapshot, Oct 21, 2026 · Not live

Each dot is one of the ATP top 100 with enough matches in the last 52 weeks. Tomas Machac is 81st of 94; Karen Khachanov is 15th of 94.

Service games held, last 52 weeks, against the ATP top 100
PlayerService games heldPlace
Tomas Machac76.3%81st of 94
Karen Khachanov86.7%15th of 94
Field median81.7%
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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