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Sam Peng

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Baltimore, MD
4.0C year-end 2024
i
Computer — generated by the USTA algorithm from match play
4 matches · 1W–3L · seasons 2024–2024
Match history4 matches
W
2024-05-19 · sLeezy · #1 Singles · 4.0
loading the estimate
6-1, 6-0
L
2024-05-12 · sLeezy · #1 Doubles · 4.0 · with Mark Eckley
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2-6, 1-6
L
2024-04-30 · sLeezy · #2 Doubles · 4.0 · with Julian Chun
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3-6, 0-6
L
2024-04-18 · sLeezy · #1 Doubles · 4.0 · with Neil Shipman
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6-4, 6-7, 0-1
Where you rank locallyagainst everyone at your level
Teams1 team
Over timerating by season, and how you rank
By level1 level played
4.0
25%
1W–3L · 44.8% 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
#1 Singles
25%
1 match
#2 Doubles
25%
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.

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