To better help players understand their level of play over time and how they compete against higher and lower-rated players, UTR introduces advanced player metrics! These metrics allow the user to see a player’s historical rating fluctuations and analyze wins/losses at the individual match level.
Let’s take a look at this new feature, which can be found in the “Stats” tab on the player profile. We can look at Cori Gauff’s profile as an example.
1. These filters allow the user to see:
- Results from the last 12 months (default) or the last 6 months.
- Results that count for the player’s rating (default) or all results.
- Note: Other than the current UTR circle and the rating history line, all other metrics update according to these filters.
2. This section shows:
- The player's current UTR.
- The player's win/loss record and min/max UTR.
3. This section shows the highest rated opponent this player has defeated.
4. Rating History: The default chart has a line for the player’s rating history. This line can help the user identify whether the player’s rating is trending or has been stable over time.
The rating history chart also has colored dots. These dots show wins (in pink) and losses (in gray) by result date and opponent’s UTR. Hover over any dot to see the result date, opponent, opponent’s UTR and score of the match.
Analysis: Cori Gauff’s rating history chart gives us several insights into her current and historical UTR. We see that in July 2019, Gauff had great results against high-level competition. She had six wins over players with a UTR of 12.25 or higher during Wimbledon. The teal rating history line shows that as a result of these wins, her rating went up.
5. Results Analysis: The second chart shows those same dots, rearranged by opponent’s UTR and percent of games won. UTR difference and percent of games won are the two main aspects of the UTR algorithm.
This chart can be broken into four quadrants.
Top right: More than 50% of games won against a higher-rated opponent
Results added to this quadrant may cause the player’s rating to increase
Top left: More than 50% of games won against a lower-rated opponent
Results added to this quadrant may cause the player’s rating to increase or decrease, depending on the combination of UTR difference and percent of games won
Bottom left: Less than 50% of games won against a lower-rated opponent
Results added to this quadrant may cause the player’s rating to decrease
Bottom right: Less than 50% of games won against a higher-rated opponent
Analysis: Cori Gauff’s results analysis chart helps us determine which results were expected by the UTR algorithm. When Gauff plays lower-rated opponents, the algorithm expects her to win at least 50% of games. She has won at least 50% of games in 15 of 19 matches against lower-rated opponents. Similarly, when Gauff plays higher-rated opponents, the algorithm expects her to win less than 50% of games. She has won less than 50% of games in 6 of 11 matches against higher-rated opponents.
Learn all about the Algorithm here.