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David Ladao

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San Diego, CA
3.0C year-end 2025
i
Computer — generated by the USTA algorithm from match play
4 matches · 1W–3L · seasons 2025–2026
Match history4 matches
L
2025-11-30 · SD 3.0 Full Metal Racquets @Barnes/ Borja · #2 Doubles · 3.0 · with Manny Borja
loading the estimate
2-6, 6-7
L
2025-10-26 · SD 3.0 Full Metal Racquets @Barnes/ Borja · #2 Doubles · 3.0 · with Michael Tiong
loading the estimate
2-6, 6-4, 0-1
W
2025-10-12 · SD 3.0 Full Metal Racquets @Barnes/ Borja · #1 Doubles · 3.0 · with Kyle Granali
loading the estimate
2-6, 6-4, 1-0
L
2025-10-04 · SD 3.0 Full Metal Racquets @Barnes/ Borja · #1 Doubles · 3.0 · with Alexandre Tadevossian
loading the estimate
1-6, 0-6
Where you rank locallyagainst everyone at your level
Teams1 team
Over timerating by season, and how you rank
By level1 level played
3.0
25%
1W–3L · 36.1% of games

Games won matters more than matches won — NTRP adjusts on margins.

By lineusually #1 Doubles, 50% of the time
#1 Doubles
50%
2 matches
#2 Doubles
50%
2 matches

How often, across every team and every match we hold — including ones that do not count toward a rating. Advanced stats has a court-position table too, and it answers a different question: how well you do there, over matches that count. A team’s own page shows how that one team uses you.

Not affiliated with or endorsed by the USTA. Ratings labelled as published are USTA year-end figures; anything we describe as an estimate is ours, not USTA’s. Match data is from USTA TennisLink.

It’s one of the reasons why I like tennis so much. Because you have to figure it out on your own.
Roger Federer