Grand Slam · Round of 16 · Australian Open
Final score & match stats
Playing styles and historical archetype record
Pliskova
🤖 Servebot
Saville
🎾 All-Court
Matchup analysis
The 🤖 Servebot archetype wins about 53% vs 🎾 All-Court across 644 matches in our dataset. That is a small stylistic lean for Karolina Pliskova here.
Servebot players often use high ace rate and dominant service to pressure the all-court's tactical versatility. On Hard, that can swing with conditions.
Hypothetical if you put 1u on each player to win every one of their matches · Last 90 days
| Metric | Pliskova | Saville |
|---|---|---|
| W-L | 8–3 | - |
| Avg odds | 2.14 | - |
| ROI % | +55.2% | - |
| Units P/L | +6.07u | - |
Prior meetings and scores · 4 career meetings
4
Pliskova
0
Saville
Sep 17, 2018
Tokyo
H Hard · Round of 16
Jan 16, 2017
Australian Open
H Hard · Round of 16
Jun 20, 2016
Eastbourne
G Grass · Round of 32
Mar 23, 2015
Miami
H Hard · Round of 16
Serve and return comparison · Last 90 days
| Stat | Pliskova | Saville |
|---|---|---|
| Serve | ||
| 1st Serve In % | 65.7% | 0% |
| 1st Serve Pts Won % | 68.2% | 0% |
| 2nd Serve Pts Won % | 41.7% | 0% |
| Aces / Match | 4.1 | 0 |
| Double Faults / Match | 5.8 | 0 |
| Break Points Saved % | 51.1% | 0% |
| Return | ||
| 1st Return Pts Won % | 35% | 0% |
| 2nd Return Pts Won % | 53.1% | 0% |
| BP Converted % | 50.5% | 0% |
| Rally | ||
| Winners / Match | 0 | 0 |
| Unforced Errors / Match | 0 | 0 |
| Net Pts Won % | 0% | 0% |
| Total Pts Won % | 50.6% | 0% |
| Surface (Hard) | ||
| Hard Win % | 0% | 0% |
Last five matches per player
Matchup overview
Karolina Pliskova and Daria Saville face off in the Round of 16 at Australian Open on Hard.
Karolina Pliskova leads 4-0 over 4 previous meetings.
Karolina Pliskova is 3-2 over the last 5 matches. Latest result: W vs Laura Siegemund (May 5).
Daria Saville is 2-3 over the last 5 matches. Latest result: L vs Madison Keys (May 26).
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