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Ranking Feature
Analysis of Junior Ratings and Rankings

The Tennis Recruiting ranking system provides a predictive measure of junior tennis players' abilities. In other words, the ranking system can be used to predict winners - and probabilities for upsets - in match-ups between players.

For example, consider the 2,616 singles matches at the 2015 Clay Court Championships. In this tournament, the player ranked higher by Tennis Recruiting defeated the lower-ranked player in 2,020 matches - meaning that Tennis Recruiting correctly predicted 77.2% of all matches. Our system also called for 561 upsets - which was within 1.4% of the 596 upsets that actually occurred.

So... is 77.2% a good number? And is this tournament representative of how the system would perform in other tournaments?

This brief article tries to answer those questions. We take a look at how the Tennis Recruiting (TRN) system performs when compared against other junior tennis ranking and rating systems. We compare the performance of our system with Universal Tennis Ratings (UTR), USTA Points Per Round (USTA), and ITF Junior Rankings (ITF) for a set of sectional, national, and international tournaments.


Rating Comparison Systems

To evaluate these ranking and rating systems in terms of predictiveness, we record the rankings of the players according to each system before a tournament starts, and then we count the number of matches in the tournament that the systems get right and wrong. For example, if a ranking system gets half of the matches right, then the resulting percentage is 50%.

The following table shows how the four rating systems performed for a set of recent high-profile tournaments. Each row corresponds to a single tournament, and each column corresponds to a different rating system. The table itself displays the percentage of matches where the higher-rated player defeated the lower-rated player. The tournament names link to heatmaps and forecasts performed by Tennis Recruiting during the tournament. The percentages link to post-tournament ranking analysis for the corresponding system.

Date Tournament Name Matches Wins Predicted
2014 USTA Winter Nationals 949 75.3% 74.7% 69.5%
2015 Easter Bowl 831 75.5% 71.7% 66.7% 71.1%
2015 Roland Garros Junior French Open 124 71.8% 65.7% 57.4%
2015 Eastern Sectional Championships 682 81.2% 78.3% 74.9%
2015 Florida Sectional Championships 914 80.1% 78.9% 69.4%
2015 Texas Grand Slam 1,768 80.5% 81.1% 71.0%
2015 Southern Sectional Championships 2,346 79.9% 78.3% 67.8%
2015 Mid-Atlantic Sectional Championships 601 82.7% 81.3% 70.5%
2015 Midwest Sectional Championships 1,919 82.7% 82.1% 74.0%
2015 Southern California Sectional Championships 845 79.5% 79.0% 68.0%
2015 Wimbledon Jr. Championships 126 70.6% 68.7% 58.7%
2015 USTA Clay Court Championships 2,616 77.2% 75.0% 68.5%
2015 USTA National Championships 2,627 76.3% 75.1% 69.6%
2015 US Open 358 72.9% 70.0% 69.2%
2015 USTA Winter Nationals 2,172 76.0% 75.4% 68.8%
2016 Australian Open 374 76.2% 73.0% 71.1%
2016 Easter Bowl 815 72.5% 70.1% 65.5% 63.0%
2016 NCAA Championships 187 75.9% 72.2% 72.8%
2016 Roland Garros 376 73.9% 74.5% 68.5%
2016 Wimbledon Jr. Championships 371 77.1% 73.6% 72.0%
2016 USTA Clay Court Championships 2,618 75.9% 74.6% 67.2%
2016 USTA National Championships 2,617 76.8% 75.3% 69.3%
2016 US Open 363 73.3% 70.1% 69.4%
26,599 77.6% 76.2% 69.0% 68.6%

As you can see in the table, Tennis Recruiting outperformed all other rating systems considered in all but two of the tournaments we studied in this analysis.

Focusing on the 2015 USTA Clay Courts, we noted above that TRN correctly predicted 2,020 matches - or 77.22%. By comparison, the UTR and USTA correctly predicted 75.0% and 68.5% matches, respectively. (We do not show numbers for the ITF because few players in the Clays have ITF rankings.)

Looking across all tournaments in the table between December 27, 2014 and August 1, 2015, notice that TRN accurately predicted almost 79% of all matches - which is superior to all other systems considered.


Notes on the Evaluation

There are several technical notes regarding the evaluation:

  • For the purposes of this analysis, we define an upset to be a match where a lower-rated player defeats a higher-rated player - regardless of the rating difference.

  • Defining an upset in this way is different from the study put out by Universal Tennis on the 2014 Winter Nationals. In that study, Universal Tennis defines an upset to occur when a player loses a match to an opponent rated 1.0 or more points below. While that approach is certainly meaningful, using ranges like this is somewhat arbitrary. For example, at Tennis Recruiting, we could define an upset as a loss to someone more than one star rating below (e.g., a 4 Star losing to a 2 Star). The larger the range, the fewer the number of upsets. For this reason, we use the ratings to come up with a complete ordering of all the players - and we define upset at the finest level for all systems.

  • For each tournament we studied, we recorded TRN, UTR, USTA, and ITF ratings for the competitors immediately prior to the tournament. New rating values were not calculated or considered during the tournament. Only the rating values prior to the tournament are used for evaluation.

  • A match is counted only when both players have ratings.

  • Every algorithm treats defaults, withdrawals, walkovers, and retirements differently. For simplicity, we do not include these matches in this analysis. Only matches played to completion are included here.

  • ITF rankings are only considered for ITF tournaments because the majority of players in USTA tournaments do not have ITF rankings. Likewise, we do not include analysis of USTA rankings for international events that have only a handful of American juniors.

  • If a system assigns identical ratings to two players who play each other in a match, we credit that system with half (0.5) of a win and half (0.5) of an upset in the analysis.


So there you have it. We at Tennis Recruiting are very proud of our ranking system, and we have tried to back up our claims with numbers.

If you have thoughts to share on our rankings or analysis, feel free to leave a comment or ask a question below. We will make every effort to answer any questions you have about this study in the comments section below.


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Page updated on Saturday, April 01, 2017
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