What is a Rick Rating

What is a Rick Rating?

When I was a team captain for a senior men's team I found it hard to rank players that I didn't know and even worst I didn't rank players that I did know correctly. I had one guy who looked like a 4.0 player, but his results were always like a low 3.0 player. To help me deal with this problem and to give me a competitive edge against other teams I wrote a computer program to generate ratings based on playing results using the USTA TennisLink data found online.

My program generates USTA-like ratings that I call "Rick ratings". I researched how the USTA generates their ratings and I decided to copy what they do and to do some things differently. They don't like to see too many players moving up and down in ratings because that would be disruptive to the leagues too much. I my case my sole goal is to compare players to each other. So my results will be different, but I think that my program's output is fairly good for what it tries to do: compare playing performances. There are problems with my software, but even the USTA rating system has problems. Like when two players always play together you can't break apart their playing levels.

My rating system is designed so that it spreads out the rankings for a playing level. For example: a person playing a 3.0 league with average results playing on court 2 gets a Rick Rating = 3.25 (The mid-point between 3.0 and 3.5). So it should work out that 50% of the players will be above and 50% below that rating.

My rating system works like the USTA system. It doesn't care about who wins matches it only looks at who wins the highest percentage of games. Like the USTA system you could lose all of your matches and still have your rating go up if you win more games than you lose. Like the USTA system it also factors in the ratings of the players you are playing against. If your rating is higher than your opponents by a lot, then beating them by a little could cause your rating to go down. The software expected you to win by a bigger margin.

One problem is that the quality of the results depend greatly on the amount of data. The more matches a player is rated on the better the rating. So a weak player could play only 1 match, but end up with a high rating if they had been luckily enough to play with a strong player on court 1 and the won that match. Also the more players play with different playing partners the better their rating will reflect their playing level. Two people who only play together will end up with the same rating no matter how different their playing skills are.

There are more than one way to run my software so rating results can vary. So it's not how accurate the ratings are that should be looked at, but how accurate the rankings are. It is not so accurate that you can trust who it ranks number 1 vs. number 2, or even a bigger spread like number 5 vs. number 8. The system is more correct as the differences get larger. The number 1 player is going to be a stronger player than the number 10 player. Really it's more accurate to say that the number 1 player had better playing results in the league than players ranked below.

The software outputs to an Excel file and I color code the spreadsheet to help to highlight useful information.

To judge the quality of the Rick Ratings is easy even without knowing anything about the players. You add the ratings together of each double pair playing a match and if the pair with the higher ratings wins then the ratings predicted that win correctly. In a test that I ran it correctly predicted the winner 90% of the time.