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# Eala vs Stojsavljevic: Tokyo win follows expectations
- URL: https://courtshark.ai/blog/eala-stojsavljevic-tokyo-result-forecast/
- Published: 2026-10-27T07:01:14.000Z
- Updated: 2026-10-27T07:01:14.000Z
- Description: Eala was the clear favorite in Tokyo. Her decisive win stood out more than the result itself, given her uneven recent form.
- Author: Court Shark Desk
- Tags: results, Alexandra Eala, Mika Stojsavljevic, Tokyo 2026, Hard, Form

In this analysis

1. [Key takeaway](#key-takeaway)
2. [A clear win despite Eala's mixed form](#s-a-clear-win-despite-eala-s-mixed-form)
3. [The winner matched the forecast](#s-the-winner-matched-the-forecast)
4. [Explore this matchup](#explore)
5. [Methodology and sources](#methodology)

Key takeaway

Eala delivered the expected win despite mixed recent form. The comfortable margin was notable, but a winner probability is not a prediction of the score.

Alexandra Eala beat Mika Stojsavljevic in straight sets in Tokyo. The decisive margin stood out more than the winner, especially given Eala's uneven recent form.

## A clear win despite Eala's mixed form

[Alexandra Eala](https://courtshark.ai/players/alexandra-eala-10223253) beat [Mika Stojsavljevic](https://courtshark.ai/players/mika-stojsavljevic-10261963) in Tokyo. Eala won 6-1 6-2 despite arriving without a sustained winning run. The margin stood out. The notable part was how decisively she won, rather than the identity of the winner.

Eala entered with a 4-6 record across her last ten matches, matching her recent hard-court record. Stojsavljevic had gone 2-8 in her last ten on hard. That contrast helps explain why Eala's mixed results did not make this an evenly balanced matchup, even though neither player brought strong recent form.

Rankings also favored Eala, No. 20 against No. 278\. Stojsavljevic was returning from a long layoff and had lost her previous five matches, while Eala had played recently. My reading is that this was a favorable opportunity for Eala to interrupt her own losing run, rather than a test against an opponent in rhythm.

### What the model expected, and what happened

Article snapshot, Oct 27, 2026 · Not live

Alexandra Eala won 6-1 6-2\. The model had made them the favorite.

__Pre-match model probability and the result__
| Player             | Model before the match | Result |
| ------------------ | ---------------------- | ------ |
| Alexandra Eala     | 83%                    | Won    |
| Mika Stojsavljevic | 17%                    | Lost   |

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

### Recent form

Article snapshot, Oct 27, 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          |
| ------------------ | ------------ | ------ | --------------------- | ----------------- | -------------- |
| Alexandra Eala     | Aug 10, 2026 | L      | Belinda Bencic        | 4-6 0-6           | Toronto        |
| Alexandra Eala     | Aug 15, 2026 | W      | Elena Gabriela Ruse   | 6-1 3-0 RET       | Cincinnati     |
| Alexandra Eala     | Aug 18, 2026 | L      | Amanda Anisimova      | 6-4 4-6 2-6       | Cincinnati     |
| Alexandra Eala     | Sep 2, 2026  | W      | Mary Stoiana          | 6-1 6-2           | US Open        |
| Alexandra Eala     | Sep 3, 2026  | W      | Oleksandra Oliynykova | 6-1 6-4           | US Open        |
| Alexandra Eala     | Sep 5, 2026  | L      | Iva Jovic             | 5-7 6-3 5-7       | US Open        |
| Alexandra Eala     | Sep 24, 2026 | L      | Tatiana Barkova       | 6-4 5-7 3-6       | Singapore      |
| Alexandra Eala     | Oct 12, 2026 | L      | Han Shi               | 6-4 3-6 3-6       | Wuhan          |
| Alexandra Eala     | Oct 19, 2026 | W      | Diane Parry           | 6-3 6-1           | WTA Ningbo     |
| Alexandra Eala     | Oct 22, 2026 | L      | Diana Shnaider        | 5-7 4-6           | WTA Ningbo     |
| Mika Stojsavljevic | Apr 15, 2026 | W      | Dalayna Hewitt        | 6-2 2-6 7-6(6)    | W35 MIYAZAKI   |
| Mika Stojsavljevic | Apr 16, 2026 | L      | Misaki Matsuda        | 3-6 3-6           | W35 MIYAZAKI   |
| Mika Stojsavljevic | Apr 29, 2026 | L      | Mananchaya Sawangkaew | 3-6 3-6           | W100 Gifu      |
| Mika Stojsavljevic | Jun 3, 2026  | W      | Emerson Jones         | 3-6 6-1 7-5       | Birmingham 125 |
| Mika Stojsavljevic | Jun 4, 2026  | W      | Elvina Kalieva        | 6-4 6-7(2) 6-2    | Birmingham 125 |
| Mika Stojsavljevic | Jun 5, 2026  | L      | Nikola Bartunkova     | 4-6 7-6(8) 6-7(4) | Birmingham 125 |
| Mika Stojsavljevic | Jun 10, 2026 | L      | Donna Vekic           | 2-6 3-6           | Queen's Club   |
| Mika Stojsavljevic | Jun 13, 2026 | L      | Himeno Sakatsume      | 2-6 6-7(2)        | Nottingham     |
| Mika Stojsavljevic | Jun 29, 2026 | L      | Belinda Bencic        | 2-6 1-6           | Wimbledon      |
| Mika Stojsavljevic | Jul 15, 2026 | L      | Oceane Dodin          | 4-6 7-6(5) 5-7    | W50 Nottingham |

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

## The winner matched the forecast

Court Shark gave Eala an 83% pre-match win probability. The market consensus had her at 87% as the match started. Both favored the same player clearly, so the result settled no disagreement over which player was more likely to win.

Opening market consensus was 88% for Eala before moving toward Stojsavljevic. The favorite remained clear. That movement changed the degree of favoritism rather than its direction, and the eventual winner was still the player favored throughout the available market readings.

A correct winner alone cannot establish whether the forecast was well calibrated or whether it was better than the market's estimate. A win probability also does not specify a set score, so Eala's emphatic margin should not be treated as a separate score prediction coming true.

### Model and market on Alexandra Eala

Article snapshot, Oct 27, 2026 · Not live

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

__Alexandra Eala's chance to win__
| Reading                | Alexandra Eala | Mika Stojsavljevic |
| ---------------------- | -------------- | ------------------ |
| Opening consensus      | 88%            | 12%                |
| Consensus at the start | 87%            | 13%                |
| Court Shark model      | 83%            | 17%                |

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

## Explore this matchup

Compare both players side by side: recent results, surfaces, serve and return.

### Player comparison

Article snapshot, Oct 27, 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               | Alexandra Eala | Mika Stojsavljevic |
| --------------------- | -------------- | ------------------ |
| Wins, last 10 matches | 40% (4-6)      | 30% (3-7)          |
| Wins, last 10 on hard | 40% (4-6)      | 20% (2-8)          |
| Model win probability | 83%            | 17%                |

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

### Win rate by surface

Article snapshot, Oct 27, 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 | Alexandra Eala | Mika Stojsavljevic |
| ------- | -------------- | ------------------ |
| Hard    | 64% (16-9)     | 63% (22-13)        |
| Clay    | 44% (4-5)      | No matches         |
| Grass   | 75% (12-4)     | 27% (3-8)          |

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

### Serve and return on hard courts

Article snapshot, Oct 27, 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             | Alexandra Eala | Mika Stojsavljevic | Tour average, all years |
| ------------------- | -------------- | ------------------ | ----------------------- |
| Service games held  | 67%            | 70%                | 63%                     |
| Return games broken | 39%            | 32%                | 37%                     |
| Matches in sample   | 25             | 35                 |                         |

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

### Model win probability

Article snapshot, Oct 27, 2026 · Not live

What the Court Shark model gave each player before the match started.

__Model win probability by player__
| Player             | Win probability | Recent form (last 10) |
| ------------------ | --------------- | --------------------- |
| Alexandra Eala     | 83%             | 4-6                   |
| Mika Stojsavljevic | 17%             | 3-7                   |

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

[Explore this matchup](https://courtshark.ai/h2h?p1=10223253&p2=10261963)

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

Keep exploring

[See the profile of Alexandra Eala](https://courtshark.ai/players/alexandra-eala-10223253)[Create a free account to keep it](https://courtshark.ai/register?redirect=%2Fplayers%2Falexandra-eala-10223253)

Match context

Players

Alexandra Eala  
vs Mika Stojsavljevic

Event

Tokyo

Surface

Hard

Round

Round of 32

Date

Monday, October 26

Article snapshot · Not live

Continue your research

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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=10223253&p2=10261963)
- [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/)