The previous post mapped the states in each USTA section. Then the map was used to show the player count by section. Before we look at which sections produce the most championship teams, let’s look into the section sizes a litle more.
In this post we’ll look for size details within each section. We’ve seen that the USTA splits the U.S. states and territories into 17 sections. Those sections are then split into districts. Some districts are split into areas. Let’s see a geographical perspective of the size of the districts and areas. If a district has areas, the area will be mapped. Otherwise, the district will be shown.
In the continental U.S., the USTA sections consist of 307 districts and areas, each is represented by a yellow dot. The larger the dot, the greater the number of players in the district/area between 2014 and 2017. Can you find the three largest districts/areas without looking at the chart below?
|Num of Players
|Georgia Ga Atlanta
|Colorado Co Denver
|Eastern Massachusetts Eastern Mass
|S E Michigan
|Southern Region Westchester Rockland
|North Carolina Nc (Chl)
|South Carolina Sc Low Country Lcta
|North Carolina Nc Capital Area (Ral)
|Central Indiana Indianapolis
The No. Cal section does not appear to have the same Section-District-Area structure that the other USTA sections have so the entire section shows up as one district. Atlanta and Denver seem to be the true giant districts/areas, especially Atlanta. Most of the rest are large metro areas.
In the next post we’ll look at which sections produce championship teams.
There seems to be interest in knowing more about what parts of the country produce the most national championship teams. We can also show what districts or areas produce the most sectional champions. It’s not hard to just list the championship teams and then tally what section, district, area, or state they are from - and we’ll get to that.
But of more interest is finding whether there is a relationship between championship teams and factors such as:
If you think that there’s a connection between championship teams and another factor, contact us, we may use your suggestion.
We’ll start with a brief tour of the USTA sections and work through to the answers. The USTA is split into 17 sections as shown on map below.
Two sections reside outside of the continental US - Puerto Rico and Hawaii. And Alaska is part of the Pacific NW section.
The following table shows the number of players in each section that played at least one league match between Jan 2014 and March 2017. The number represents the USTA number assigned to each section.
|Num of Players
The table is okay but requires a lot of work to gain any insight. Let’s show the player counts on the USTA sections map using colors to represent the number of players.
This map uses the colors of the rainbow to represent the number of players in each section. “Red” is the large end of the scale and “violet” the small end; Think ROYGBIV in reverse.
It’s much easier to see in the map that the Southern section in red is multiple times larger than any other section. There are no sections colored orange or yellow. A handful of sections are in greens, another handful in blues, and two in the indigo / violet range.
Over the next few weeks we’ll dig into these numbers to try to answer the questions about which USTA sections and district/areas produce championship teams and why.
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.