ATP Challenger Tour · Round of 32 · Toyota
Final score
Playing styles and historical archetype record
Jung
⚙️ Grinder
Thompson
🤖 Servebot
Matchup analysis
The 🤖 Servebot archetype wins about 58% vs ⚙️ Grinder across 5,334 matches in our dataset. That is a small stylistic lean for Jordan Thompson here.
Servebot players often use high ace rate and dominant service to pressure the grinder's relentless consistency. On Carpet, that can swing with conditions.
Hypothetical if you put 1u on each player to win every one of their matches · Last 90 days
| Metric | Jung | Thompson |
|---|---|---|
| W-L | 0–5 | - |
| Avg odds | 3.41 | - |
| ROI % | -100.0% | - |
| Units P/L | -5.00u | - |
Small sample: ROI stabilizes with more matches; fewer than 10 in the window is noisy.
Prior meetings and scores · 4 career meetings
3
Jung
1
Thompson
Sep 12, 2016
Nanchang
C Clay · Quarterfinals
Sep 11, 2016
Shanghai
H Hard · Semifinals
Apr 17, 2016
Nanjing
C Clay · Quarterfinals
Nov 12, 2015
Toyota
? Carpet · Round of 32
Serve and return comparison · Last 90 days
| Stat | Jung | Thompson |
|---|---|---|
| Serve | ||
| 1st Serve In % | 67.9% | 0% |
| 1st Serve Pts Won % | 65.2% | 0% |
| 2nd Serve Pts Won % | 40% | 0% |
| Aces / Match | 3.5 | 0 |
| Double Faults / Match | 2 | 0 |
| Break Points Saved % | 52.1% | 0% |
| Return | ||
| 1st Return Pts Won % | 31.9% | 0% |
| 2nd Return Pts Won % | 50.7% | 0% |
| BP Converted % | 58.5% | 0% |
| Rally | ||
| Winners / Match | 14.3 | 0 |
| Unforced Errors / Match | 23.8 | 0 |
| Net Pts Won % | 56.3% | 0% |
| Total Pts Won % | 48% | 0% |
| Surface (Carpet) | ||
| Carpet Win % | 0% | 0% |
Last five matches per player
Matchup overview
Jason Jung and Jordan Thompson face off in the Round of 32 at Toyota on Carpet.
Jason Jung leads 3-1 over 4 previous meetings.
Jason Jung is 0-5 over the last 5 matches. Latest result: L vs Zdenek Kolar (Jun 9).
Jordan Thompson is 3-2 over the last 5 matches. Latest result: L vs Nuno Borges (Jan 21).
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