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Marissa Tegels

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Minneapolis, MN
2.5C year-end 2023
i
Computer — generated by the USTA algorithm from match play
10 matches · 3W–7L · seasons 2022–2024
Match history10 matches
W
2023-11-29 · ICT Stark 10:30am · #6 Singles · 3.0
loading the estimate
6-2, 5-5
L
2023-10-04 · ICT Stark 10:30am · #6 Singles · 3.0
loading the estimate
4-6, 2-6
W
2023-09-20 · ICT Stark 10:30am · #6 Singles · 3.0
loading the estimate
6-2, 6-3
L
2023-03-01 · ICT Stark 12:00 PM · #6 Singles · 3.0
loading the estimate
3-6, 3-6
W
2023-02-15 · ICT Stark 12:00 PM · #6 Singles · 3.0
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1-6, 6-3, 1-0
L
2023-02-08 · ICT Stark 12:00 PM · #3 Singles · 3.0
loading the estimate
2-6, 3-6
L
2023-01-18 · ICT Stark 12:00 PM · #3 Singles · 3.0
loading the estimate
0-6, 2-6
L
2022-11-30 · ICT Stark 12:00 PM · #5 Singles · 3.0
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4-6, 4-6
L
2022-11-02 · ICT Stark 12:00 PM · #3 Singles · 3.0
loading the estimate
3-6, 3-5
L
2022-09-21 · ICT Stark 12:00 PM · #6 Singles · 3.0
loading the estimate
2-6, 5-4
Where you rank locallyagainst everyone at your level
Teams2 teams · 2023–2024
Over timerating by season, and how you rank
By level1 level played
3.0
30%
3W–7L · 41% of games

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

By lineusually #6 Singles, 60% of the time
#6 Singles
60%
6 matches
#3 Singles
30%
3 matches
#5 Singles
10%
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.

You can get through anything if you keep going one point at a time.
Arthur Ashe