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James Wang

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San Francisco, CA
3.5C year-end 2025
i
Computer — generated by the USTA algorithm from match play
7 matches · 1W–6L · seasons 2023–2025
Match history7 matches
L
2025-03-10 · GLTF/GOLDMAN TC 40AM4.0B · #1 Singles · 4.0
loading the estimate
2-6, 4-6
L
2025-03-06 · GLTF/GOLDMAN TC 40AM4.0B · #3 Doubles · 4.0 · with Rodolphe Cassand
loading the estimate
6-7, 4-6
L
2025-02-27 · GLTF/GOLDMAN TC 40AM4.0B · #1 Singles · 4.0
loading the estimate
5-7, 2-6
L
2024-03-04 · GLTF/GOLDMAN TC 40AM4.0B · #1 Singles · 4.0
loading the estimate
1-6, 1-6
W
2024-02-23 · GLTF/GOLDMAN TC 40AM4.0B · #1 Singles · 4.0
loading the estimate
6-3, 6-0
L
2023-01-26 · GLTF/GOLDMAN TC 40AM4.0A · #2 Doubles · 4.0 · with William Kramer
loading the estimate
1-6, 4-6
L
2023-01-03 · GLTF/GOLDMAN TC 40AM4.0A · #3 Doubles · 4.0 · with Kevin Kowalczyk
loading the estimate
1-6, 2-6
Where you rank locallyagainst everyone at your level
Teams3 teams · 2023–2025
Over timerating by season, and how you rank
By level1 level played
4.0
14.3%
1W–6L · 36.9% of games

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

By lineusually #1 Singles, 57% of the time
#1 Singles
57%
4 matches
#3 Doubles
29%
2 matches
#2 Doubles
14%
1 match

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.

The mark of great sportsmen is not how good they are at their best, but how good they are at their worst.
Martina Navratilova