ATP Tour
ATP World Ranking - 11 pts
🛡️ The Spoiler
A defensive specialist who retrieves better than a Grinder but without the elite return game of a Counterpuncher. Neutralises power hitters through court coverage and consistency - and uniquely, holds a winning record against The Complete Package.
Strong against
Weak against
Age
23
Height
6'3" (191 cm)
Weight
77 kg (170 lbs)
Plays
Right-Handed, Two-Handed BH
Career-High Ranking
#1069 (2025-10-27)
9
Wins
12
Losses
42.9%
Win %
0
Titles
Career record broken down by surface
| Year | Summary | Clay | Hard | Grass |
|---|---|---|---|---|
| 2026 | 1/3 | 0/1 | 1/2 | - |
| 2025 | 8/9 | 7/6 | 1/3 | - |
| Career | 9/12 | 7/7 | 2/5 | - |
Averages · Last 90 days (2 matches)
Serve
Return
Rally
Last 10 results
| Date | Tournament | Round | Opponent | Surface | Score | Result |
|---|---|---|---|---|---|---|
| Jun 15, 2026 | Futures 2026 | Iliyan Radulov | Hard | L | ||
| May 4, 2026 | M25 Santa Margherita di Pula | Round of 32 | Lorenzo Comino | Clay | 36 67 | L |
| Feb 16, 2026 | M25 Trento | Round of 32 | Lorenzo Beraldo | Hard | 63 64 | W |
| Feb 16, 2026 | M25 Trento | Round of 16 | Mirza Basic | Hard | 36 16 | L |
| Nov 16, 2025 | Bergamo | 1st Round Qualifying | Andrea Guerrieri | Hard | 64 26 26 | L |
| Oct 27, 2025 | M15 Selva Gardena | Round of 32 | Ziga Sesko | Hard | 67 46 | L |
| Oct 6, 2025 | M15 Sharm ElSheikh | Round of 32 | Preston Brown | Hard | 62 62 | W |
| Oct 6, 2025 | M15 Sharm ElSheikh | Round of 16 | Aleksandre Bakshi | Hard | 36 36 | L |
| Sep 15, 2025 | M25 Santa Margherita di Pula | Round of 16 | Lorenzo Sciahbasi | Clay | 16 46 | L |
| Sep 15, 2025 | M25 Santa Margherita di Pula | Round of 32 | Giacomo Crisostomo | Clay | 64 62 | W |
Leonardo Malgaroli is currently ranked #1158 in the ATP singles rankings with 11 points.
Leonardo Malgaroli (ATP #1158) has a career win-loss record of 9-12 (42.9% win rate) and has won 0 ATP titles.
Smashrs tracks Leonardo's upcoming matches with AI-powered predictions across six independent models. Our confidence score reflects the degree of agreement between models - a higher score means stronger consensus. Check back before each match for the latest prediction.
