Learner Tien
ATP ELO profile · tour-level matches since 2015
Season ELO trajectory
One point per match: the player's ELO rating after that match, matches in round order. Ratings are season-scoped: every January the engine re-seeds each player from ATP entry points, then updates after every result. That is why trajectories are shown one season at a time. Hover a point for the match behind it.
Career record
71-44 61.7% in 115 matches
Season by season
| Season | M | W-L | Start | Peak | End |
|---|---|---|---|---|---|
| 2026 | 43 | 28-15 | 1654 | 1867 | 1844 |
| 2025 | 61 | 38-23 | 1549 | 1859 | 1859 |
| 2024 | 7 | 5-2 | 1510 | 1601 | 1565 |
| 2023 | 3 | 0-3 | 1502 | 1474 | 1448 |
| 2022 | 1 | 0-1 | 1500 | 1490 | 1490 |
Recent matches
| Week | Tournament | Opponent | Result |
|---|---|---|---|
| Aug 30, 2026 | Us Open · Hard | Gael Monfils | W 3-0 |
| Nuno Borges | W 3-0 | ||
| Aug 13, 2026 | Cincinnati · Hard | Frances Tiafoe | L 1-2 |
| Sebastian Baez | W 2-0 | ||
| Aug 02, 2026 | Toronto · Hard | Ben Shelton | L 0-2 |
| Daniel Merida | W 2-0 | ||
| Thiago Agustin Tirante | W 2-0 | ||
| Tommy Paul | W 2-0 | ||
| Gael Monfils | W 2-1 | ||
| Jul 27, 2026 | Washington · Hard | Adrian Mannarino | L 0-2 |
Serve predictions: how close do we get on Learner Tien?
Comparison covers 48 of the 53 aces projections we made in 2025. A match needs five earlier matches on record before the baseline exists.
The baseline predicts a player's aces as the average of their last five matches. Our model beats it when its projections land closer to what actually happened. Both numbers are the average miss per match, so lower is better, and both are for the selected season only.
Predictability: does Learner Tien follow the script?
On serve · 2026| Season | M | W-L | Model hit | Upsets | Verdict |
|---|---|---|---|---|---|
| 2026 | 43 | 28-15 | 55.8% | 19 vs 15.7 exp | On serve |
| 2025 | 52 | 30-22 | 63.5% | 19 vs 20.5 exp | On serve |
An upset = our model's favorite losing. "Upsets" compares how many actually happened in Learner Tien's matches with how many the model expected for that exact schedule. A season-level read (a wild-card season does not carry over year to year). How to read this · full board: most predictable ATP players.
Reuse this data · CC BY 4.0
The ATP ELO ratings dataset is free to reuse, including commercially, under CC BY 4.0. Attribution with a link is the only requirement. Copy-paste credit:
Data: <a href="https://www.predixsport.com/tennis-power-rankings/learner-tien">ATP ELO ratings by Predixsport</a> (CC BY 4.0)