The most widely used chess rating system that is in use today actually is of fairly recent origin. In fact, organizations like the United States Chess Federation and similar types of organizations and associations around the globe implemented what has become known as the Elo or the ELO system beginning in the early 1960s. The so-called Elo or ELO system (hereinafter “ELO” for ease of reference in this article) was the creation of a gentleman born in Hungary but who was a physics professor in the United States named Arpad Elo -- hence the moniker Elo or ELO. The chess rating scheme oftentimes if signified in all capital letters although it really is not an acronym. The ELO chess rating system actually was created in order to improve the overall chess rating system that previously was in place. In time, ELO has been used in many other arenas beyond chess rating. In addition to chess rating, ELO can be used as an appropriate rating system for any competitive game situation that involves multiple players, including computer games. Indeed, the ELO chess rating scheme has evolved so far as to be applied to such sports as international football, U.S. football and U.S. Major League Baseball. At the heart of the ELO chess rating system was the substitution of statistical estimation in place of a system that is based upon competitive rewards. Rather then subjective evaluations based on so-called “greatness” in relation to game related or play related achievements. An easy to understand example is to consider a chess tournament. Previously, chess rating could be based upon a rather arbitrary determination that one chess tournament is three times more important than a less competition. Therefore, “points” would be awarded to the winner of this more significant chess tournament in a more significant proportion under this subjective system of chess rating.
On the other hand, the ELO chess rating system engages a purely statistical model that considers the actual game or tournament results to underlying variables that are intended to reflect the actual abilities of a particular chess player. Of course, competitors can still contend that the ELO chess rating scheme still rewards success and failure in a particular situation; however, many experts in the field of chess rating believe that this system more accurately evaluates and reflects the actual abilities of a chess player. The contention is that the ELO chess rating system is a much more reliable chess rating scheme than anything else that has come before or anything else that might be available for utilization today.In developing the ELO chess rating system, ELO operated on the basic premise that the performance of each and every chess player in any particular game is what technically is known as a “normally distributed random variable.” At the heart of the normally distributed random variable is the conclusion that while a chess players performance will vary from one game to the next, sometimes even significantly, the mean or median “value” of a particular chess player’s performance over time in fact would change only slowly.
On the other hand, the ELO chess rating system engages a purely statistical model that considers the actual game or tournament results to underlying variables that are intended to reflect the actual abilities of a particular chess player. Of course, competitors can still contend that the ELO chess rating scheme still rewards success and failure in a particular situation; however, many experts in the field of chess rating believe that this system more accurately evaluates and reflects the actual abilities of a chess player. The contention is that the ELO chess rating system is a much more reliable chess rating scheme than anything else that has come before or anything else that might be available for utilization today.In developing the ELO chess rating system, ELO operated on the basic premise that the performance of each and every chess player in any particular game is what technically is known as a “normally distributed random variable.” At the heart of the normally distributed random variable is the conclusion that while a chess players performance will vary from one game to the next, sometimes even significantly, the mean or median “value” of a particular chess player’s performance over time in fact would change only slowly.
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