FICS 1.6.2

1 files changed, 219 insertions, 0 deletions

diff --git a/data/help/glicko b/data/help/glicko
new file mode 100644
index 0000000..d4614b2
--- /dev/null
+++ b/data/help/glicko
@@ -0,0 +1,219 @@
+
+       +-------------------------------------------------+
+       |   Vek-splanation of the Glicko Ratings System   |
+       +-------------------------------------------------+
+
+As you may have noticed, each FICS player now has a rating and an RD.  
+ 
+RD stands for "ratings deviation".
+ 
+Why a new system
+----------------
+ 
+The new system with the RD improves upon the binary categorization that was
+used before on fics and elsewhere, where players with fewer than 20 games were
+labeled"provisional" and others were labeled "established".  Instead of two
+separate ratings formulas for the two categories, there is now a single
+formula incorporating the two ratings and the two RD's to find the ratings
+changes for you and your opponent after a game.
+
+What RD represents
+------------------
+ 
+The Ratings Deviation is used to measure how much a player's current rating
+should be trusted.  A high RD indicates that the player may not be competing
+frequently or that the player has not played very many games yet at the
+current rating level.   A low RD indicates that the player's rating is fairly
+well established.  This is described in more detail below under "RD
+Interpretation".
+
+How RD Affects Ratings Changes
+------------------------------
+
+In general, if your RD is high, then your rating will change a lot each time
+you play.  As it gets smaller, the ratings change per game will go down. 
+However, your opponent's RD will have the opposite effect, to a smaller
+extent: if his RD is high, then your ratings change will be somewhat smaller
+than it would be otherwise.
+
+A further use of RD's:
+----------------------
+
+Vek asked Mark Glickman the following:
+
+> Given player one with rating r1, error s1,
+> and player two with r2 and s2, do you have a formula for the probability
+> that player 1's "true" rating is greater than player 2's ?
+
+Mark said:
+ 
+  Yes - it's:
+ 
+  1/(1 + 10^(-(r1-r2)f(sqrt(s1^2 + s2^2))/400) )
+ 
+  where f(s) is [the function applied to RD in Step 2 below].
+
+How RD is Updated
+-----------------
+
+In this system, the RD will decrease somewhat each time you play a game,
+because when you play more games there is a stronger basis for concluding what
+your rating should be.  However, if you go for a long time without playing any
+games, your RD will increase to reflect the increased  uncertainty in your
+rating due to the passage of time.  Also, your RD will decrease more if your
+opponent's rating is similar to yours, and decrease less your opponent's
+rating is much different.
+
+Why Ratings Changes Aren't Balanced
+-----------------------------------
+
+In the other system, except for provisional games, the ratings changes for the
+two players in a game would balance each other out - if A wins 16 points, B
+loses 16 points.  That is not the case with this system.  Here is the
+explanation I received from Mark Glickman:
+
+  The system does not conserve rating points - and with good
+  reason!  Suppose two players both have ratings of 1700,
+  except one has not played in awhile and the other playing
+  constantly.  In the former case, the player's rating is not
+  a reliable measure while in the latter case the rating is a fairly
+  reliable measure.  Let's say the player with the uncertain rating
+  defeats the player with the precisely measured rating.
+  Then I would claim that the player with the imprecisely
+  measured rating should have his rating increase a fair
+  amount (because we have learned something informative from
+  defeating a player with a precisely measured ability) and
+  the player with the precise rating should have his rating
+  decrease by a very small amount (because losing to a player
+  with an imprecise rating contains little information).
+  That's the intuitive gist of my extension to the Elo system.    
+ 
+  On average, the system will stay roughly constant (by the
+  law of large numbers).  In other words, the above scenario
+  in the long run should occur just as often with the 
+  imprecisely rated player losing.
+ 
+Mathematical Interpretation of RD
+---------------------------------
+
+Direct from Mark Glickman:
+ 
+Each player can be characterized as having a true (but unknown) rating that
+may be thought of as the player's average ability.  We never get to know that
+value, partly because we only observe a finite number of games, but also
+because that true rating changes over time as a player's ability changes.  But
+we can *estimate* the unknown rating.  Rather than restrict oneself to a
+single estimate of the true rating, we can describe our estimate as an
+*interval* of plausible values.  The interval is wider if we are less sure
+about the player's unknown true rating, and the interval is narrower if we are
+more sure about the unknown rating.  The RD quantifies the uncertainty in
+terms of probability:
+ 
+The interval formed by Current rating +/- RD contains your true rating with
+probability of about 0.67.
+ 
+The interval formed by Current rating +/- 2 * RD contains your true rating
+with probability of about 0.95.
+ 
+The interval formed by Current rating +/- 3 * RD contains your true rating
+with probability of about 0.997.
+ 
+For those of you who know something about statistics, these are not confidence
+intervals, but are called "central posterior intervals" because the derivation
+came from a "Bayesian" analysis of the problem.
+ 
+These numbers are found from the cumulative distribution function of the
+normal distribution with mean = current rating, and standard deviation = RD.   
+For example, CDF[ N[1600,50], 1550 ] = .159  approximately (that's shorthand
+Mathematica notation.)
+
+The Formulas
+------------
+
+Algorithm to calculate ratings change for a game against a given opponent:
+ 
+Step 1.  Before a game, calculate initial rating and RD for each player.
+ 
+  a)  If no games yet, initial rating assumed to be 1720.
+      Otherwise, use existing rating.  
+      (The 1720 is not printed out, however.)
+ 
+  b)  If no RD yet, initial RD assumed to be 350 if you have no games,
+      or 70 if your rating is carried over from ICC.
+      Otherwise, calculate new RD, based on the RD that was obtained
+      after the most recent game played, and on the amount of time (t) that
+      has passed since that game, as follows:
+ 
+      RD' = Sqrt(RD^2 + c log(1+t))
+ 
+      where c is a numerical constant chosen so that predictions made
+      according to the ratings from this system will be approximately
+      optimal.
+ 
+Step 2.   Calculate the "attenuating factor" due to your OPPONENT's RD,
+          for use in later steps.
+ 
+       f =  1/Sqrt(1 + p RD^2)
+ 
+          Here p is the mathematical constant 3 (ln 10)^2
+                                             -------------
+                                              Pi^2 400^2    .
+ 
+          Note that this is between 0 and 1 - if RD is very big,
+          then f will be closer to 0.
+ 
+Step 3.   r1 <- your rating,
+          r2 <- opponent's rating,
+ 
+                    1
+      E <-  ----------------------
+                    -(r1-r2)*f/400     <- it has f(RD) in it!
+              1 + 10
+ 
+          This quantity E seems to be treated kind of like a probability.
+ 
+Step 4.   K =               q*f
+              --------------------------------------
+               1/(RD)^2   +   q^2 * f^2 * E * (1-E)
+ 
+          where q is a mathematical constant:  q = (ln 10)/400.
+ 
+Step 5.   This is the K factor for the game, so
+ 
+          Your new rating = (pregame rating) + K * (w - E)
+ 
+          where w is 1 for a win, .5 for a draw, and 0 for a loss.
+ 
+Step 6.   Your new RD is calculated as
+ 
+          RD' =                     1
+                  -------------------------------------------------
+                  Sqrt(    1/(RD)^2   +   q^2 * f^2 * E * (1-E)   )  . 
+ 
+The same steps are done for your opponent.
+ 
+Further information
+-------------------
+ 
+A PostScript file containing Mark Glickman's paper discussing this ratings
+system may be obtained via ftp.  The ftp site is hustat.harvard.edu, the
+directory is /pub/glickman, and the file is called "glicko.ps".  It is
+available at http://hustat.harvard.edu/pub/glickman/glicko.ps.
+
+Credits
+-------
+ 
+The Glicko Ratings System was invented by Mark Glickman, Ph.D. who is
+currently at the Harvard Statistics Department, and who is bound for Boston
+University.
+
+Vek and Hawk programmed and debugged the new ratings calculations (we may
+still be debugging it).  Helpful assistance was given by Surf, and Shane fixed
+a heinous bug that Vek invented.
+ 
+Vek wrote this helpfile and Mark Glickman made some essential
+corrections and additions.
+
+  Last major update: April 19, 1995.
+  Minor revisions: August 28, 1995 by Friar.
+