Official Ratings/Rankings of ÖTTV, NÖTTV, STTV, KTTV, BTTV, TTTV, StTTV, WTTV, VTTV, OÖTTV, TTQ, TTSA, TTTA, TTV, and ELTTL.

## Priors for Unrated PlayersWhen Ratings Central processes an event, we first assign a prior mean and standard deviation to each unrated player in the event. (The adjective “prior” means that it is the player’s mean and standard deviation prior to the start of the event.) If you specified a prior mean and standard deviation for the player, then we use those values. If you didn’t specify a prior mean and standard deviation for the player, then we use the prior mean and standard deviation that you specified for the event. The following sections give detailed advice on how to set the individual player prior means and standard deviations and the event prior mean and standard deviation. If you have any questions or aren’t sure what to do, please for assistance. Please get unrated players at your events as many matches with rated players of a similar playing level as you can. This will make the resulting ratings for these players more accurate. Note that the Ratings Central rating scale (i.e., what playing strength a number corresponds to) is similar to, but not identical to, the USATT rating scale. To convert from the USATT rating scale to the Ratings Central scale, subtract 200 points; note that this conversion is only approximate and the number of points to subtract at lower ratings may be smaller. The Ratings Central scale is not the same as the ITTF rating scale or the CTTA rating scale. Note thatRatings Central uses the same rating scale for all the table tennis sports (Table Tennis, Paralympic Table Tennis, Hardbat Table Tennis, Sandpaper Table Tennis). If a Table Tennis player who plays with an inverted sponge racket or a pips-out sponge racket plays Hardbat Table Tennis (with a hardbat, of course), we would expect their rating as a Hardbat Table Tennis player to be 200 points lower than their Table Tennis rating. If they play Sandpaper Table Tennis, we would expect their rating as a Sandpaper Table Tennis player to be 250 points lower than their Table Tennis rating. ## Player PriorsThe following advice for setting player priors assumes that you are very familiar with the rating scale, i.e., you know and play with many players who have established ratings. If this is not true, then you should probably rely on the event prior and rarely set individual player priors. If you aren’t sure what to do, please for assistance. It is usually a good idea to set the prior mean and standard deviation for as many unrated players as you can. However, you should only set the prior mean and standard deviation for an unrated player if you have additional information about that player. However, the “additional information” can be any information other than the player’s match wins and losses in the event (we see those). For example, you might know the player from before the event or you might watch the player play their matches or you might look at how many points the player scored in their matches. If a player is different from the general population of unrated players at the event, e.g., much better or much worse (perhaps because they are very young), then it would be an especially good idea to set the player’s prior mean and standard deviation. If many or most of the players in your event are unrated, then it is especially helpful to the rating system if you can set the prior means and standard deviations for as many of the unrated players as you can. The prior standard deviation for a player measures how sure you are that you know that player’s playing strength. You should be willing to bet at 1:2 odds that the player’s playing strength is within one standard deviation of the mean, and you should be willing to bet at 2:1 odds that the player’s playing strength is more than one standard deviation from the mean. (Odds of 1:2 mean that you win $1 if you win the bet, but you lose $2 if you lose the bet. Odds of 2:1 mean that you win $2 if you win, but you lose $1 if you lose.) For example, suppose you assign a prior mean of 1200 and a prior standard deviation of 100 to a player. Then you should be willing to bet at 1:2 odds that the player is really between 1100 and 1300, and you should be willing to bet at 2:1 odds that the player is really less than 1100 or more than 1300. Equivalently, you should believe that there is a 2⁄3 chance that the player is really between 1100 and 1300 and a 1⁄3 chance that the player is really less than 1100 or more than 1300. Here are some very rough guidelines: If you know an unrated player extremely well (e.g., they’ve been playing at your club every week for a couple of years), then you might use a prior standard deviation of 75. If you only know a player moderately well (e.g., they came to your club a few times and played several matches with players of a similar level), then you might use a prior standard deviation of 125. If you know very little about a player (e.g., you had the player hit with a rated player of a similar level for five minutes), then you might use a prior standard deviation of 200. If a player has a USATT rating, then that is a source of information. However, USATT ratings vary widely in their accuracy, so it is best to check that a player’s USATT rating seems reasonable using your own knowledge of the player. USATT ratings have been drifting upward over time, and there are also significant regional differences. USATT ratings are currently probably 200 points higher on average than Ratings Central ratings. If all you know about a player is their USATT rating, then we suggest the following: For the prior mean, use their USATT rating minus 200. For players rated at least 1000, use a prior standard deviation of 150. For players rated less than 1000, use a prior standard deviation of 250. ## Event PriorYou must always set the event prior mean and standard deviation. While the prior mean and standard deviation for a player measure what you know of the player’s playing strength, it is best to interpret the event prior mean and standard deviation as describing the range of unrated players at your event. For example, if you think the unrated players range from 800 to 1400, then you would use the average of these two values (i.e., 1100) as the mean and the difference of these two values divided by four (i.e., 150) as the standard deviation. More precisely, about 2⁄3 of the unrated players should be within one standard deviation of the mean (and about 1⁄3 should be more than one standard deviation from the mean), 95% should be within two standard deviations, and 99.7% should be within three standard deviations. So, for the example in the previous paragraph of a mean of 1100 and a standard deviation of 150, you should think that - 2⁄3 of the players are between 950 and 1250,
- 95% of the players are between 800 and 1400,
- 99.7% of the players are between 650 and 1550.
Note that when estimating the event prior standard deviation from the range of players that you expect at your event, you should interpret the range as being plus or minus two standard deviations, not three. If you set the prior mean and standard deviation for any individual unrated players, then the event prior mean and standard deviation should only describe the population of unrated players for whom you haven’t set individual prior means and standard deviations. If you set the prior mean and standard deviation individually for every unrated player at your event, then Ratings Central won’t actually use the event prior mean and standard deviation, but you still have to set them. It is possible that a player that you thought was rated may become unrated because of a correction to some other event. If this happens, the event prior mean and standard deviation would be used for the player, even though you thought it wouldn’t be. But, this eventuality is extremely unlikely, so not worth worrying about. If you would like to receive an email the minute that an event that you played in is processed, please give your event director your email address or your email address. Please include your Ratings Central ID number, if you know it. |

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