Medvedev vs Bublik: Almaty Open win ends in retirement
Medvedev was already ahead when Bublik retired in Almaty. The result matched the forecast, but it was not a completed straight-sets win.
Daniil Medvedev advanced after Alexander Bublik retired following a 6-3 opening set, rather than a completed straight-sets win. The favorite was already strengthening his position, but the early finish limits the verdict.
Medvedev was ahead before the retirement
Medvedev's lead preceded the early finish. Daniil Medvedev won the opening set 6-3 before Alexander Bublik retired from their Almaty Open semifinal. His advantage was established on court before the retirement settled the result, making the opening set the useful part of this match to assess.
During the opening set, Medvedev's estimated win chance rose from 72% to 83% as he established an early lead. His position was strengthening before the retirement ended the contest. That movement fits a favorite gaining control rather than a player relying on an abrupt ending to escape a difficult position.
Their matchup history also favored Medvedev, who arrived with a 6-1 overall advantage and a 4-0 record against Bublik on hard courts. My reading is that the opening set fit an established surface pattern rather than representing a surprising reversal. Bublik had yet to beat him on this surface.
How the match turned
Article snapshot, Oct 25, 2026 · Not live
Daniil Medvedev's chance rose from 72% to 83% after moving 3-1 ahead in the first set. The match ended when Alexander Bublik retired.
| Score | Daniil Medvedev win chance |
|---|---|
| Start | 70% |
| Set 1, 1-0 | 72% |
| Set 1, 1-1 | 70% |
| Set 1, 2-1 | 72% |
| Set 1, 3-1 | 83% |
| Set 1, 4-1 | 85% |
| Set 1, 4-2 | 84% |
| Set 1, 5-2 | 86% |
| Set 1, 5-3 | 85% |
| Set 1, 6-3 | 87% |
| Retirement | 100% |
The favorite won, without settling the probability
Court Shark's model gave Medvedev a 70% chance before the match. The market consensus had him at 64% as play began. Both favored the eventual winner, though Court Shark's estimate expressed greater confidence in Medvedev than the market did at the start of this semifinal.
The result matched the pick. One victory cannot establish whether that probability was well calibrated, especially when the match ended through retirement rather than a completed contest. It shows that the favored player advanced, not that the model's degree of confidence was proven correct or that a straight-sets victory was inevitable.
Recent form offered a separate reason to favor Medvedev: he entered with an 8-2 record, compared with Bublik's 6-4. Those records describe the players coming in, not an explanation for the retirement. In my assessment, Medvedev's stronger recent record and favorable history made his opening-set advantage consistent with expectations, even though the ending was unusual.
What the model expected, and what happened
Article snapshot, Oct 25, 2026 · Not live
Daniil Medvedev won 6-3. The model had made them the favorite.
| Player | Model before the match | Result |
|---|---|---|
| Daniil Medvedev | 70% | Won |
| Alexander Bublik | 30% | Lost |
Explore this matchup
Compare both players side by side: recent results, surfaces, serve and return.
Player comparison
Article snapshot, Oct 25, 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 | Daniil Medvedev | Alexander Bublik |
|---|---|---|
| Wins, last 10 matches | 80% (8-2) | 60% (6-4) |
| Wins, last 10 on hard | 80% (8-2) | 60% (6-4) |
| Head-to-head wins | 86% (6-1) | 14% (1-6) |
| Model win probability | 70% | 30% |
Recent form
Article snapshot, Oct 25, 2026 · Not live
Each player's most recent completed matches, up to 10, oldest on the left.
| Player | Date | Result | Opponent | Score | Event |
|---|---|---|---|---|---|
| Daniil Medvedev | Oct 3, 2026 | W | Jan Lennard Struff | 6-4 6-3 | Beijing |
| Daniil Medvedev | Oct 4, 2026 | W | Francisco Cerundolo | 7-6(4) 6-3 | Beijing |
| Daniil Medvedev | Oct 5, 2026 | L | Novak Djokovic | Beijing | |
| Daniil Medvedev | Oct 10, 2026 | W | Jan Lennard Struff | 4-6 6-4 6-3 | Shanghai Masters |
| Daniil Medvedev | Oct 12, 2026 | W | Dalibor Svrcina | 6-2 6-3 | Shanghai Masters |
| Daniil Medvedev | Oct 14, 2026 | W | Stefanos Tsitsipas | 6-4 7-5 | Shanghai Masters |
| Daniil Medvedev | Oct 16, 2026 | W | Tommy Paul | 6-3 1-6 6-3 | Shanghai Masters |
| Daniil Medvedev | Oct 17, 2026 | L | Rafael Jodar | 3-6 4-6 | Shanghai Masters |
| Daniil Medvedev | Oct 22, 2026 | W | Sho Shimabukuro | 6-2 6-1 | ATP Almaty |
| Daniil Medvedev | Oct 23, 2026 | W | Terence Atmane | 6-4 6-4 | ATP Almaty |
| 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 | ATP Almaty | |
| Alexander Bublik | Oct 23, 2026 | W | Karen Khachanov | 4-6 7-6(5) 7-6(5) | ATP Almaty |
Head-to-head by surface
Article snapshot, Oct 25, 2026 · Not live
Daniil Medvedev and Alexander Bublik have met 7 times. Daniil Medvedev leads 6-1.
| Surface | Daniil Medvedev | Alexander Bublik |
|---|---|---|
| All surfaces | 6 | 1 |
| Hard | 4 | 0 |
| Clay | 2 | 0 |
| Grass | 0 | 1 |
Win rate by surface
Article snapshot, Oct 25, 2026 · Not live
Share of matches won on each surface across each player's last 50 matches with full statistics.
| Surface | Daniil Medvedev | Alexander Bublik |
|---|---|---|
| Hard | 76% (25-8) | 59% (16-11) |
| Clay | 63% (5-3) | 53% (8-7) |
| Grass | 67% (6-3) | 63% (5-3) |
Serve and return on hard courts
Article snapshot, Oct 25, 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 | Daniil Medvedev | Alexander Bublik | Tour average, all years |
|---|---|---|---|
| Service games held | 88% | 87% | 77% |
| Return games broken | 28% | 16% | 23% |
| Matches in sample | 33 | 27 |
Model and market on Daniil Medvedev
Article snapshot, Oct 25, 2026 · Not live
Daniil Medvedev's chance as the market consensus priced it from the opening line, next to the Court Shark model.
| Reading | Daniil Medvedev | Alexander Bublik |
|---|---|---|
| Opening consensus | 65% | 35% |
| Consensus at the start | 64% | 36% |
| Court Shark model | 70% | 30% |
Model win probability
Article snapshot, Oct 25, 2026 · Not live
What the Court Shark model gave each player before the match started.
| Player | Win probability | Recent form (last 10) |
|---|---|---|
| Daniil Medvedev | 70% | 8-2 |
| Alexander Bublik | 30% | 6-4 |
Return games won: where they stand
Article snapshot, Oct 25, 2026 · Not live
Each dot is one of the ATP top 100 with enough matches in the last 52 weeks. Daniil Medvedev is 6th of 94; Alexander Bublik is 78th of 94.
| Player | Return games won | Place |
|---|---|---|
| Daniil Medvedev | 28.2% | 6th of 94 |
| Alexander Bublik | 15.6% | 78th of 94 |
| Field median | 18.6% | |
| Field best (Daniel Merida Aguilar) | 30.7% | 1st |
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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