We ended our last series with a few questions along the lines of “Can the winner of a match be accurately predicted if you know the player’s rating?” This post will show that Tennis League Analytics’ (TLA’s) Player Strength Rating (PSR) can be a useful tool in predicting who wins tennis matches as well as putting together team rosters and lineups.
We’ll start with a related question that’s recently been asked a few times: “Why is my Player Strength Rating below my NTRP rating?” An example with specific numbers is a player rated 4.0 (USTA NTRP) with a Player Strength Rating (or dynamic rating) of 3.21. TLA follows the USTA’s NTRP rating scale. You can read on USTA’s website that “The NTRP system identifies general levels of ability, but an individual will be rated within those levels at 50 different hundredths of a point. For example, a 3.5 player can fall anywhere between a 3.01 and a 3.50.”
So the rating that is expressed to a one-half point is called the NTRP rating or year-end rating (3.5, 4.0, 4.5, etc.). The rating expressed to the one-hundredth of a point is called a dynamic rating (this explanation also appears on the USTA webpage referenced above).
TLA’s PSR is more like the dynamic rating but broader and more indicative of a player’s true strength because it includes all types of league matches - men’s, women’s, mixed, combo, and tri-level.
Our previous blog series showed that certain combinations of doubles partner’s win more often, based on NTRP ratings. Does knowing PSRs help even more with predicting the outcome of matches?
Based on the same ~100,000 doubles matches that were reviewed in the first blog series, the answer is simply and clearly, yes.
It makes perfect sense that stronger players have higher ratings. And that players with higher ratings (compared to their opponents) are more likely to win. And that the larger the difference between ratings, the more likely it is for the higher rated players to win. But by how much?
In doubles, when one partnership is an average of .1 points stronger than their opponents, they win 65% of the time. Here’s an example: an 8.0 doubles match involves four players with 4.0 NTRP ratings. Team A’s players have PSRs of 3.6 and 3.7; team B’s players have PSRs of 3.7 and 3.8. So each of B’s players is .1 PSR points stronger than A’s players. B will win 65% of the time.
If the average PSR difference increases to .15, the chance of winning increases to 73%. Bump the PSR difference to .2 and the likelihood to win increases to 77%. The chart shows more points.
It’s easy to say, “Stronger players win more often.” The trick is to be able to accurately assess who’s a stronger player. And win-loss records are not the way to do so because wins and losses don’t say anything about the relative strength of either player. A stronger 4.0 can lose 5 matches in a row and maintain a 3.84 rating. A weaker 4.0 can win 5 matches in a row and reach a 3.63. Rating changes depend on the strength of the players involved. So knowing a player’s strength rating can provide a tactical advantage when putting together teams and lineups.
The Team Player Trend Report (found on the Team Reports page here) shows PSRs for every player on a team.
Data driven rosters and lineups allowed the Oakland A’s, as depicted in the book and movie Moneyball, to outperform teams managed by “experience based judgement.” Tennis teams can now also use data to drive their decisions.