USATT Ratings

June 19, 2014

Is the USATT Rating System Inflationary, Deflationary, or Stable?

I don't have exact numbers on this, but it's fairly obvious that, over the years, the ratings have inflated. When I started out in 1976 there were only three players rated over 2400 (Danny Seemiller, D-J Lee, and Gil Joon Park, with the latter two from South Korea); now there are 116, and this is only among USA players. There are more foreign players now listed as USA players than before, so this is part of the reason, but the bulk of these 2400+ players are just as much USA players as those back in the late 1970s. Dan Seemiller had just reached top 30 in the world with a rating just over 2500. Insook Bhushan (then Insook Na) had just come to the U.S. from South Korea, and was top ten in the world among women, but was rated only about 2250. These days top ten in the world among women would be about 2650. At one point I was 18th in the country among U.S. citizens with a 2292 rating; these days it wouldn't make the top 100. So yes, the ratings have inflated. (My impression, however, is that any inflation has decreased or stopped in recent years. For one thing, the highest rated USA players now are actually a bit lower than some from the previous generations, but that's offset by the fact that the previous generations had players with higher world rankings and deserved the higher ratings.)

But wait, some of you are thinking, hasn't the level of play improved, and that's why there are so many more higher-rated players these days? That modern players have improved is absolutely true - but that has no bearing on the ratings. As players on average improve, so do their opponents. Think of it this way. If everyone were to suddenly improve 100 rating points in level, there would be no effect on the ratings themselves since opponents would also be 100 points better. And so even though everyone's about 100 points better, the ratings themselves would stay the same. 

The level of play has improved because of more training centers, more coaches, better equipment, and more advanced techniques. For example, backhand play these days is far stronger than it was when I started out. Players attack from closer to the table, making it harder to keep a rally going. And if I could have had some modern sponges back in the early 1980s, I (and most top players) would have caused some serious havoc.

The interesting question here is what has inflated faster, the rating system or the level of play? It's a tough call. I would say a 2000 player from the 1970s is more skilled than a 2000 player of today, but that doesn't mean he'd beat the 2000 player of today, who makes up for his lesser skill with more modern techniques and better equipment. (For this, I'm not going to worry about details like the larger ball, different serving rules, etc.) To use a simple example, I'm fairly certain that any modern 2300 player could go back in time to the 1940s with a sponge racket and be World Champion. The very best players from the 1940s were more skilled than a modern 2300 player, but the 2300 player would have modern sponge, looping, serves, etc. (To put it another way, at my peak, and with my sponge racket, I could have beaten the best players in the 1940s, but I don't think I was a more skilled player than the best hardbatters of that era. An interesting question is how long it would take the best players of that era to adjust?)

So why has the system inflated? Actually, the system would be a deflationary system except the adjustment factor is too high. The inflation comes from all the points pumped into the system from the adjustment factor, where any player who gains 51 or more points in a tournament is adjusted upwards. (There are no downward adjustments.)

If there were no adjustment factor, the system would be deflationary, and the average rating would be dropping. Why? Because the average player improves after his initial rating. Assuming no adjustment factor, let's say that the average first rating is 1200, and that the average player then improves to 1500. That means the player takes 300 rating points from others in the system. Result? Assuming the same number of players in the system, there are now 300 less points distributed among them, and so the average rating goes down - even though the average level of those players has stayed the same. This should be true of any rating system where there's a direct or indirect exchange of rating points.

Let's assume that the average player instead got worse on average. Then they'd be giving the system points, and so the system would be inflationary

One distinction to make here is the difference between the ratings going down on average while the average level stays the same (a deflationary system), and one that goes down because there is a large influx of new players with lower levels. The addition of all these lower-rated players would lower the average rating, but deservedly so since the average level will have gone down. But among the established players, where the level has stayed the same, the ratings wouldn't change, and so the system isn't really deflationary, though the average rating has dropped. 

"Can You Predict the Odds in a Match from their Ratings?" Revisited

Yesterday I blogged about the above. In it I showed why a rating system will always have more upsets at the lower levels than at the higher levels, even if statistically it appears that the odds should be the same at all levels. Here's an easy way of explaining this, using 100-point upsets as an example.

The most accurate rating system in the world is still going to have more 100-point upsets at the lower levels (and upsets in general) for the simple reason that no matter how accurate the rating is at the time the player last played, players at lower levels are more likely to have major improvements than players at higher levels. In other words, the ratings might be accurate at the time the players played, but they become inaccurate at lower levels more quickly than at higher levels. 

Here's a simple example. Suppose you have a highly accurate rating system that accurately rates 20 players. Ten are accurately rated at 1000, and ten are accurately rated at 2500. The next time these 20 players play, the ten who were rated 1000 are more likely to have improved to 1100 than the ten players rated 2500 are to have improved to 2600, and so it's more likely the 1000-rated players are going to be beating 1100 players than the 2500-rated players beating 2600 players. Therefore, it is more likely that these 1000 rated players are going to pull off 100-point upsets than the 2500 players. 

Here's still another way of looking at it. The odds of a 1000-level player beating an 1100-level player may be the same as the odds of a 2500-level player beating a 2600-level player, i.e. 1 in 6. The problem is that it's more likely that a player listed as 1000 is actually 1100 in level than a player listed as 2500 is actually 2600 in level. 

Playing the Middle

Here's a new coaching article from Samson Dubina, "Are You in a Jam?"

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Here's the job description and application info for CEO of USA Table Tennis. I read over the listing - that's a LOT of requirements!!! I'll probably blog about this tomorrow.

Review of the Nittaku Poly Ball

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Here's the article, with links to these player pages.

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Here's the photo album of Coach Lily Yip in China with Lily Zhang and Krish Avvari.

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Here's a list of scheduled openings for the movie around the country, including Ocean City; Omaha; San Francisco; Phoenix; Miami; Louisville; Grand Rapids; Athens, GA; Goshen, IN; and Winston-Salem.

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Here's the listing.

Table Tennis Nemesis

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Here's the video (1:57).

Table Table Tennis

Here's the video (11 sec) - they are playing with two tables set a distance apart.

Earthly Table Tennis

This is what I call an out-of-this-world ping-pong table. I want one!!!

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