← Search

Milinda McNeely

Add to scout listFree account. Monday email when they play.
Los Angeles, CA
3.5C year-end 2025
i
Computer — generated by the USTA algorithm from match play
81 matches · 32W–49L · seasons 2017–2026
Match history81 matches
W
2026-11-01 · SGV Ball Busters-A. Chow-San Marino HS/ Su10 · #3 Doubles · 3.5 · with Dayna Moelleken
loading the estimate
6-0, 7-5
W
2026-10-31 · LA - Fine Young Can of Balls · #3 Doubles · 3.5 · with MayLin Tao
loading the estimate
6-4, 6-1
W
2026-10-18 · LA - Fine Young Can of Balls · #3 Doubles · 3.5 · with Dayna Moelleken
loading the estimate
4-6, 6-3, 1-0
W
2026-10-04 · SGV Ball Busters-A. Chow-San Marino HS/ Su10 · #3 Doubles · 3.5 · with Deidra Hoye
loading the estimate
6-2, 6-3
L
2026-08-16 · LA - LATC 55+ Women · #2 Doubles · 7.0 · with Dayna Moelleken
loading the estimate
6-1, 2-6, 0-1
W
2026-08-08 · LA - LATC 55+ Women · #3 Doubles · 7.0 · with Laura Putney
loading the estimate
6-4, 6-2
L
2026-07-25 · LA - LATC 55+ Women · #1 Doubles · 7.0 · with MARY WOODWARD
loading the estimate
7-5, 1-6, 0-1
L
2026-07-19 · LA - LATC 55+ Women · #3 Doubles · 7.0 · with Diane Wagner
loading the estimate
3-6, 6-1, 0-1
W
2026-07-11 · LA - LATC 55+ Women · #3 Doubles · 7.0 · with Dayna Moelleken
loading the estimate
6-1, 6-2
L
2026-06-20 · SGV Ball Busters-A. Chow-San Marino HS/ Su10/11:30 · #2 Doubles · 3.5 · with Dayna Moelleken
loading the estimate
6-7, 3-6
L
2026-05-31 · LA - LATC · #3 Doubles · 3.5 · with Dorothy Kim
loading the estimate
2-6, 1-6
W
2026-05-30 · SGV Ball Busters-A. Chow-San Marino HS/ Su10/11:30 · #3 Doubles · 3.5 · with Kimberly Foon
loading the estimate
1-6, 6-1, 1-0
Where you rank locallyagainst everyone at your level
Teams37 teams · 2019–2026
Over timerating by season, and how you rank
By level2 levels played
3.5
41.1%
23W–33L · 48.2% of games
7.0
37.5%
9W–15L · 51.9% of games

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

By lineusually #3 Doubles, 48% of the time
#3 Doubles
48%
39 matches
#2 Doubles
32%
26 matches
#1 Doubles
15%
12 matches
#1 Singles
3%
2 matches
#2 Singles
1%
1 match
Singles
1%
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.

I don’t want to be somebody else. I want to be myself and win in my way.
Rafael Nadal