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# Daniil Medvedev wins Hangzhou Open final
- URL: https://courtshark.ai/blog/daniil-medvedev-andrey-rublev-hangzhou-final/
- Published: 2026-09-30T07:01:23.000Z
- Updated: 2026-10-05T21:00:22.000Z
- Description: Daniil Medvedev's return pressure helped him beat Andrey Rublev 7-5 6-4 in the Hangzhou Open final.
- Author: Court Shark Desk
- Tags: results, Daniil Medvedev, Andrey Rublev, Hangzhou Open, Hard, ATP

In this analysis

1. [Key takeaway](#key-takeaway)
2. [The return edge decided the final](#s-the-return-edge-decided-the-final)
3. [Rublev's serve needed cleaner first strikes](#s-rublev-s-serve-needed-cleaner-first-strikes)
4. [Medvedev made the baseline work](#s-medvedev-made-the-baseline-work)
5. [History favored the stronger returner](#s-history-favored-the-stronger-returner)
6. [What the model says](#s-what-the-model-says)
7. [Explore this matchup](#explore)
8. [Methodology and sources](#methodology)

Key takeaway

Daniil Medvedev beat Andrey Rublev 7-5 6-4 in the Hangzhou Open final. Court Shark's pre-match model gave Medvedev a 61% chance, with his return game and head-to-head edge framing the matchup.

## The return edge decided the final

Medvedev won the serve-versus-return contest. [Daniil Medvedev](https://courtshark.ai/players/daniil-medvedev-106421) had the clearer route to pressure because his deep court position and steady baseline coverage can make even strong serving games feel crowded. That pattern mattered more than raw attacking intent in a final between two players who know each other's games well.

The final score was 7-5 6-4\. It was a tight match on Tuesday, September 29, and neither set left much room for a loose service game or a rushed return. Medvedev's ability to keep points alive gave Rublev fewer short exchanges after the serve, where he is most able to dictate with pace.

This was familiar territory. Medvedev carried an 8-2 overall head-to-head lead into the match, including a 6-4 6-2 win at the Tour Finals in 2023\. Rublev's serve can create quick openings, yet Medvedev repeatedly has found ways to get returns back and extend the next ball.

### What the model expected, and what happened

Article snapshot, Sep 30, 2026 · Not live

Daniil Medvedev won 7-5 6-4\. The model had made them the favorite.

__Pre-match model probability and the result__
| Player          | Model before the match | Result |
| --------------- | ---------------------- | ------ |
| Daniil Medvedev | 61%                    | Won    |
| Andrey Rublev   | 39%                    | Lost   |

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

## Rublev's serve needed cleaner first strikes

[Andrey Rublev](https://courtshark.ai/players/andrey-rublev-126094) arrived with a three-match winning run, so there was no sign of a player short of rhythm. He had played three matches in the previous 14 days, the same recent workload as Medvedev. Fresh legs were available on both sides.

Rublev's task was still difficult. Against Medvedev, a serve that merely starts the point is rarely enough, because the returner is willing to absorb pace and make the server hit another demanding ball. The 7-5 opening set suggests that Rublev stayed close, but could not build the separation needed to make his serving games comfortable.

Hard courts had offered mixed recent evidence. Rublev was 5-5 across his last ten matches on the surface, while Medvedev was 7-3\. That difference does not describe every point, but it helps explain why Medvedev had more dependable patterns when rallies began after a neutral return.

## Medvedev made the baseline work

Medvedev entered as the No. 6 player in the rankings. His ranking alone did not win the final, but it reflected a more consistent recent run than the No. 25 Rublev brought to Hangzhou. The match called for patience after serve, and Medvedev supplied it.

His recent record was 7-3 over his last ten matches. Rublev was 6-4 over the same span, which kept the gap manageable and made the final competitive rather than one-sided. Still, Medvedev had produced his form on hard courts as well, where the surface rewards his ability to redirect from deep positions.

The second set ended 6-4\. That margin fits the shape of the matchup, with Rublev dangerous enough to keep the contest close but Medvedev better placed to turn a few return games into extended tests. A single break can decide a set. Medvedev gave himself more chances to find it.

## History favored the stronger returner

The head-to-head was particularly relevant because all ten previous meetings had come on this surface. Medvedev led 8-2 there, a substantial advantage in a pairing where return quality repeatedly determines who gets to attack second balls. Rublev has power to change a match quickly. Medvedev has usually denied him the easy version of that plan.

Their last meeting came at the Tour Finals in 2023\. Medvedev won 6-4 6-2, and that result offered a sharper example of how the matchup can tilt once Rublev's service games become laborious. Hangzhou was closer, which matters, but the same broad pressure point remained visible.

Both men began the final after a three-match winning run. Medvedev, aged 30, brought more recent hard-court consistency, while Rublev, aged 28, needed his serve to shorten points before Medvedev could settle into his defensive patterns. He could not consistently do that. The scoreline rewarded the player who made returning a source of control.

## What the model says

The model gave Medvedev a 61% chance and Rublev a 39% chance before the final. That assessment left room for a close contest, which is what the 7-5 6-4 score produced, while still identifying Medvedev as the likelier winner. His head-to-head record and stronger hard-court form supported that call.

The market consensus had Medvedev at 66% and Rublev at 34%. It had opened with Medvedev at 67%, then moved one point toward Rublev before play began. The gap between the model and market was five points on Medvedev.

There is no next round because this was the final. Medvedev leaves Hangzhou with the title, and Rublev leaves after a close defeat that again showed how hard it is to hold attacking positions against Medvedev's return game.

## Explore this matchup

Compare both players side by side: recent results, head-to-head and the model.

### Player comparison

Article snapshot, Sep 30, 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               | Daniil Medvedev | Andrey Rublev |
| --------------------- | --------------- | ------------- |
| Wins, last 10 matches | 70% (7-3)       | 60% (6-4)     |
| Wins, last 10 on hard | 70% (7-3)       | 50% (5-5)     |
| Head-to-head wins     | 80% (8-2)       | 20% (2-8)     |
| Model win probability | 61%             | 39%           |

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

### Head-to-head by surface

Article snapshot, Sep 30, 2026 · Not live

Daniil Medvedev and Andrey Rublev have met 10 times. Daniil Medvedev leads 8-2.

__Head-to-head record, Daniil Medvedev first__
| Surface      | Daniil Medvedev | Andrey Rublev |
| ------------ | --------------- | ------------- |
| All surfaces | 8               | 2             |
| Hard         | 8               | 2             |

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

### Model and market on Daniil Medvedev

Article snapshot, Sep 30, 2026 · Not live

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

__Daniil Medvedev's chance to win__
| Reading                | Daniil Medvedev | Andrey Rublev |
| ---------------------- | --------------- | ------------- |
| Opening consensus      | 67%             | 33%           |
| Consensus at the start | 66%             | 34%           |
| Court Shark model      | 61%             | 39%           |

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

[Explore this matchup](https://courtshark.ai/h2h?p1=106421&p2=126094)

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

Match context

Players

Daniil Medvedev  
vs Andrey Rublev

Event

Hangzhou Open

Surface

Hard

Round

Final

Date

Tuesday, September 29

Article snapshot · Not live

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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=106421&p2=126094)
- [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.

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Who writes the Journal 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/)

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