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From: ttennis@bu.edu (Table Tennis)
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Subject: rec.sport.table-tennis FAQ: game-misc [Part 3/8]
Followup-To: rec.sport.table-tennis
Date: 8 Mar 1994 02:29:40 GMT
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Summary: This posting contains a list of Frequently Asked Questions (and their answers) about Table Tennis ("Ping Pong").  It should be read by anyone who wishes to post to the rec.sport.table-tennis newsgroup.
Keywords: FAQ3 Table Tennis
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Archive-name: table-tennis/3_game-misc
Version: 3.3

rec.sport.table-tennis answers to Frequently Asked Questions and other
news, posted monthly, now in mail folder digest format. New items preceded 
with +:
 
Table of Contents:
==================
   3.1. How long is a 11 pt game?
   3.1.1 table "Probability of winning match"
   3.2. What are Handicap Events?
   3.2.1 How does USTTA Rating system works?
   3.2.2 What is the probablility of winning?
   3.2.3 Handicap Charts
   3.3. Canadian TTA to USTTA rating conversion chart
   3.4. Does it matter who serves first?
   3.5. What is Speedglue?
   3.5.1 First Press Release Statement on Speedglue Ban
   3.5.2 What speedglue are ITTF-approved?
   3.5.3 ITTF Ban
   3.5.4 Fight the Glue Ban: ITTF vs TRUE
+  3.6. ITTF/ETTU RANK list [93DEC] (use ISO8859-1 Latin font)
+  3.6.1 MEN RANK
+  3.6.2 WOMEN RANK

Send comments, suggestions, contributions, revisions and criticisms
regarding this FAQ list via e-mail to:

	ttennis@bu.edu

From marcus@djmarcus.read.tasc.com Wed Feb 10 10:39:01 1993
Subject: 3.1 HOW LONG IS AN 11 POINT GAME?
===========================================

Eleven points, of course. A more precise question: Is a 4 out of 7 match of 
11 point games the same as a 2 out of 3 match of 21 point games?  Why do we
care? Over the last few years many tournaments both in the  US and in other
countries have  experimented with 11 point  games to see  if  they make the
matches more  exciting.  Why don't  you  try  such  an  event at  your next
tournament? The results can still count for  rating points (check  with the
rating chairman for the current policy).

How do  we measure the length of  a match other   than  simply counting the
total points? The key is to realize that the length of a match is reflected
in the probability that the better player will  lose. The longer the match,
the  smaller  the  probability    of  an upset.  Using   standard  modeling
assumptions (probability of winning a point is independent of the score) we
may relate the probability of winning a point to the probability of winning
a  match  under various    formats.  For  simplicity, we  will  assume  the
probability  of winning a  point  does not depend on  who   serves.  (It is
possible to take  into account the  dependence on who  is serving, but  the
conclusions remain the same.)

The table gives the probabilities of winning a match under various formats.
Each row of the table corresponds to a  different format.  For example, the
first row is for one game to 11 points. The "Games" column gives the number
of games you need  to win the match, so  "2" means a 2 out  of 3 match. The
last  row, labeled "2  sets" is for  the tennis  format: Each  game is to 4
points with deuce  at 3, each  set is to 6 games  with deuce at 5,  and the
match is 2 out of 3 sets. I've used the old tennis format: no tie-breakers.
Note that I've also included a format of one game to 51.  This is a popular
format for handicap matches.

Each column  gives the probability  of winning  the match for   a different
probability of winning a point. Note that the first column is the  same for
all formats because it corresponds to a probability  of winning a  point of
0.5. If the two players are evenly matched and the format is fair  (and all
these formats are),  then  the probability  of  winning the  match  is  0.5
regardless of the length. The larger the numbers in a given row, the longer
the match.  The rows are in order  with the shortest  format at the top and
the longest format at the bottom.

So what can we conclude? A normal 2 out of 3 match is  half way between the
11 point game formats of 3 out of 5 and 4 out of 7.  It  is slightly closer
to the 4 out of 7 format. A normal 3 out of 5 match is between the 11 point
formats of 5 out of 9 and 6 out of 11, but is closer to the 5 out of 9. The
51 point game is almost the same as a normal 2  out of 3.  And finally, the
tennis format of 2 out of 3 sets is longer than all the other formats.

From marcus@djmarcus.read.tasc.com Wed Feb 10 10:39:01 1993
Subject: 3.1.1 table       PROBABILITY OF WINNING MATCH
-------------------------------------------------
   Format    |    Probability of Winning Point
Points Games | 0.50  0.52  0.54  0.56  0.58  0.60
-------------------------------------------------
    11     1 | 0.50  0.58  0.65  0.72  0.78  0.84
    21     1 | 0.50  0.60  0.70  0.79  0.86  0.91
    11     2 | 0.50  0.61  0.72  0.81  0.88  0.93
    11     3 | 0.50  0.64  0.77  0.86  0.93  0.97
    21     2 | 0.50  0.65  0.79  0.88  0.94  0.98
    51     1 | 0.50  0.66  0.79  0.89  0.95  0.98
    11     4 | 0.50  0.66  0.80  0.90  0.96  0.98
    11     5 | 0.50  0.68  0.83  0.92  0.97  0.99
    21     3 | 0.50  0.69  0.84  0.93  0.98  0.99
    11     6 | 0.50  0.70  0.85  0.94  0.98  1.00
      2 sets | 0.50  0.71  0.87  0.95  0.99  1.00
-------------------------------------------------

From marcus@djmarcus.read.tasc.com Wed Feb 10 10:38:58 1993
Subject: 3.2 WHAT ARE HANDICAP EVENTS?
=======================================

Handicap events  are  a lot of fun. You  get  to play  people  you wouldn't
ordinarily play   and everyone has   to  play their best in    every match.
However, the key is a good handicap chart. Simple formulas such as four (or
two) handicap points  per hundred  rating  points (in a game  to  21) are a
start, but we should be able to do better.  We  will construct new handicap
charts for both 21 point games and 51 point games.

It is traditional for a handicap match to  consist of  one  game to 51. The
reason is that a large handicap in a 21 point game can force the players to
drastically    change  their   styles:  the  stronger    player  plays  too
conservatively  since the  weaker player only  needs  to  win a few "lucky"
points. Playing 2 out of  3 doesn't change this, but  one game to 51  gives
more room to maneuver.

How do we construct a handicap chart? There are three steps:

1. We need some data from  which we can  estimate the probability  that one
player will defeat another player in a nonhandicap match.

2. Then we  relate the probability  of winning  a nonhandicap match  to the
probability of winning each point.

3.  Finally we calculate how many  handicap  points will make  the handicap
match fair.

From marcus@djmarcus.read.tasc.com Wed Feb 10 10:38:58 1993
Subject: 3.2.1 HOW DOES USTTA RATING SYSTEM WORKS?
--------------------------------------------------
Before discussing the data, let's discuss how the rating system works. This
will make it easier to understand the data.

The tournament director of each tournament sends all the results for the
tournament to the USTTA rating chairman Dan Simon. Dan processes the
tournaments in the order they were played. After processing, he sends a
report back to the tournament director that gives the new rating for each
player who played in the tournament. So, you may get your new rating from
the tournament director several weeks after the tournament.

Here is the rating chart which gives the number of rating points that the
winner of each match wins and the loser loses.

---------------------------------------
Rating     | Higher rated | Lower rated
difference | player wins  | player wins
---------------------------------------
  0- 12    |            8 |           8
 13- 37    |            7 |          10
 38- 62    |            6 |          13
 63- 87    |            5 |          16
 88-112    |            4 |          20
113-137    |            3 |          25
138-162    |            2 |          30
163-187    |            2 |          35
188-212    |            1 |          40
213-237    |            1 |          45
238-       |            0 |          50
---------------------------------------

However, the calculation of the ratings involves more than just this chart.
The  first  problem is unrated  players. Dan looks at  the  results of each
unrated player (including  the number of  points the player scored).  Using
this information, he assigns  a rating to each unrated  player. From now on
he treats unrated players just like rated players  using the newly assigned
rating.  So, you do  win  and lose points when  you play an unrated player.

To  finish calculating the  post-tournament  ratings, Dan makes  two passes
through the results. The first pass is a screening pass to identify players
whose ratings should be adjusted.  Dan  uses the  rating chart to calculate
how many points  each player would win  for the tournament. Any player  who
would win at least fifty  rating  points has his rating  adjusted  up. This
means   that Dan replaces  his  pre-tournament rating with   a new adjusted
rating which is used as his rating for the second pass. In the second pass,
Dan uses the rating chart again to calculate the post-tournament rating for
each player.

So, from the point of view of  the rating system, there  are actually three
ratings   for  every  player in  a  tournament.   The  first  rating is the
pre-tournament rating  which  is the rating the  player  has going into the
tournament after  all earlier tournaments  have been processed. This is not
necessarily  the  same as the  rating   used  at the   tournament since Dan
processes the tournaments in the order they were played.

The second rating is the  adjusted pre-tournament rating. This is different
from the pre-tournament rating for two classes of players:

1. unrated players, 
2. players who have their ratings adjusted.

No one has a zero adjusted rating, since all  the unrated players are given
a rating. If the player  was rated and  he is not being adjusted,  then his
adjusted rating is the same as his  pre-tournament rating. The third rating
is the post-tournament rating.

To summarize: the pre-tournament rating is the rating before the tournament
is processed. The adjusted  rating is the  rating after unrated players are
given ratings  and after  the first  screening  pass.  The  post-tournament
rating is the player's new rating that will be  published in the next issue
of TT Today.


DATA

Dan graciously sent me the results  from  eight tournaments played in April
and May 1989. Here are some statistics of the number of players and matches
in those eight tournaments.

---------------------------------------------------------
Category            |     Players      |    Matches
                    |------------------------------------
                    | Number  Per cent | Number  Per cent
                    |         of total |         of total
---------------------------------------------------------
all                 |    459     100.0 |   1510     100.0
unrated             |     49      10.7 |    225      14.9
adjusted            |     49      10.7 |    417      27.6
unrated or adjusted |     98      21.4 |    609      40.3
---------------------------------------------------------

The row labeled  "all" is  all the  players and all  the matches.   The row
labeled  "unrated"   is  those players who   were  unrated  going  into the
tournament and  those matches in which  either player was unrated.  The row
labeled "adjusted"  is those players  who had  their  ratings adjusted  and
those matches in which either player was adjusted. The row labeled "unrated
or adjusted" is those players who were either unrated or  had their ratings
adjusted and those matches in which either player was unrated or adjusted.

In case you were wondering, the number of "unrated" matches plus the number
of "adjusted"  matches doesn't equal the  number of  "unrated  or adjusted"
matches because there were 33 matches in which an  unrated player played an
adjusted player. It   is interesting that  40.3% of   the  matches  involve
unrated or adjusted  players. This and the fact  that   you don't know  the
pre-tournament  ratings is  why   you  can't  exactly  calculate  your  own
post-tournament rating.

Which set of ratings should we use to construct a  handicap chart? Well, in
principle we should use the pre-tournament  ratings since these ratings are
closest to the ratings that  are  actually used  at the tournaments. Rather
than make a decision, we'll construct charts  using each  of the three sets
of ratings.

From marcus@djmarcus.read.tasc.com Wed Feb 10 10:38:58 1993
Subject: 3.2.2 WHAT'S THE PROBABILITY OF WINNING?
-------------------------------------------------
We want to  extract from the  data the probability  of winning a match as a
function of the difference in ratings of the two players. Let's look at the
distribution of the matches by rating.

-------------------------------------------------------------
Rating     |       Pre      |     Adjusted   |       Post
difference |-------------------------------------------------
           | Matches Upsets | Matches Upsets | Matches Upsets
-------------------------------------------------------------
   0- 299  |     973    272 |    1126    260 |    1123    212
 300- 599  |     229     15 |     275      4 |     283      1
 600- 899  |      69      1 |      86      0 |      80      0
 900-1199  |      11      0 |      17      0 |      18      0
1200-3000  |       3      0 |       6      0 |       6      0
-------------------------------------------------------------

The reason there are fewer  total  matches  in the "Pre" column is  that we
have  excluded those   matches  that  involve  an unrated  player. For  our
purposes, the main thing to notice is how few matches  there are with large
rating differences and  how few of  them  are upsets. Hence any estimate we
calculate for  the  probability  of winning when   there  are large  rating
differences will be of questionable accuracy. Of course we are using only 8
tournaments; there are over 200 tournaments per year.


TECHNICAL STUFF

To proceed we  need a model for the  probability of winning   a nonhandicap
match as  a  function of the  rating  difference. This  gets technical  for
awhile. We will use a logistic model. Let D be the  rating difference, P be
the probability of winning  a nonhandicap 2  out of 3  match, and b  be the
model parameter. The form of the logistic model is

   P( D ) = exp( bD ) / ( 1 + exp( bD ) )

We fit the model to each of the three sets of data by maximum likelihood.
Here is the result.

------------------
Ratings  |       b
---------|--------
Pre      | 0.00795
Adjusted | 0.01115
Post     | 0.01517
------------------

Each model lets us calculate the probability of winning a nonhandicap 2 out
of 3 match   for any  difference in rating.    Given standard   assumptions
(probability of winning a  point is independent of the  score and of who is
serving)  a   probability of  winning  a  nonhandicap  2   out  of  3 match
corresponds to a probability of winning a point.

This suggests  how to calculate a handicap  chart. Pick  one of   the three
models.  Pick   a rating difference.  Convert this   to the probability  of
winning a nonhandicap 2 out of 3 match using the model. Convert this to the
probability  of winning  a  point. Now find   the handicap   such  that the
probability of winning a handicap match is 0.5 (i.e., the handicap match is
fair to both players). By the way, my 386 computer (no  coprocessor) needed
about an hour to compute the charts.

From marcus@djmarcus.read.tasc.com Wed Feb 10 10:38:58 1993
Subject: 3.2.3 HANDICAP CHARTS
------------------------------
Here are the handicap charts calculated from the above  data. First are the
charts for a 51 point game. Second are the charts for a 21 point game. Each
table contains three handicap charts labeled "Pre", "Adjusted",  and "Post"
corresponding to the  three sets of  ratings that we  have. Since we had so
little data for rating  differences of more  than 300 points, I wouldn't be
surprised if the charts  are not good  for large handicaps. I've used these
handicap charts in tournaments and I recommend you use the Post chart.


--------------------------------------------
Handicap |         Rating Difference
         |----------------------------------
         |       Pre |  Adjusted |      Post
--------------------------------------------
       0 |    0-   9 |    0-   6 |    0-   5
       1 |   10-  29 |    7-  21 |    6-  15
       2 |   30-  49 |   22-  35 |   16-  26
       3 |   50-  70 |   36-  50 |   27-  37
       4 |   71-  92 |   51-  65 |   38-  48
       5 |   93- 114 |   66-  81 |   49-  60
       6 |  115- 137 |   82-  98 |   61-  72
       7 |  138- 161 |   99- 115 |   73-  84
       8 |  162- 186 |  116- 133 |   85-  97
       9 |  187- 212 |  134- 151 |   98- 111
      10 |  213- 240 |  152- 171 |  112- 126
      11 |  241- 269 |  172- 192 |  127- 141
      12 |  270- 300 |  193- 214 |  142- 157
      13 |  301- 333 |  215- 237 |  158- 174
      14 |  334- 368 |  238- 262 |  175- 193
      15 |  369- 405 |  263- 289 |  194- 212
      16 |  406- 445 |  290- 317 |  213- 233
      17 |  446- 488 |  318- 348 |  234- 256
      18 |  489- 534 |  349- 381 |  257- 280
      19 |  535- 583 |  382- 416 |  281- 305
      20 |  584- 636 |  417- 454 |  306- 333
      21 |  637- 694 |  455- 495 |  334- 363
      22 |  695- 756 |  496- 539 |  364- 396
      23 |  757- 823 |  540- 586 |  397- 431
      24 |  824- 895 |  587- 638 |  432- 469
      25 |  896- 973 |  639- 694 |  470- 510
      26 |  974-1058 |  695- 755 |  511- 555
      27 | 1059-1150 |  756- 820 |  556- 603
      28 | 1151-1251 |  821- 892 |  604- 655
      29 | 1252-1360 |  893- 969 |  656- 712
      30 | 1361-1478 |  970-1054 |  713- 775
      31 | 1479-1608 | 1055-1147 |  776- 843
      32 | 1609-1750 | 1148-1248 |  844- 917
      33 | 1751-1906 | 1249-1359 |  918- 999
      34 | 1907-2077 | 1360-1481 | 1000-1089
      35 | 2078-2267 | 1482-1616 | 1090-1188
      36 | 2268-2477 | 1617-1766 | 1189-1298
      37 | 2478-2711 | 1767-1933 | 1299-1421
      38 | 2712-2973 | 1934-2120 | 1422-1559
      39 | 2974-3000 | 2121-2331 | 1560-1713
      40 |           | 2332-2570 | 1714-1889
      41 |           | 2571-2844 | 1890-2091
      42 |           | 2845-3000 | 2092-2324
      43 |           |           | 2325-2598
      44 |           |           | 2599-3000
--------------------------------------------


--------------------------------------------
Handicap |         Rating Difference
         |----------------------------------
         |       Pre |  Adjusted |      Post
--------------------------------------------
       0 |    0-  23 |    0-  17 |    0-  12
       1 |   24-  73 |   18-  52 |   13-  38
       2 |   74- 127 |   53-  90 |   39-  66
       3 |  128- 185 |   91- 132 |   67-  97
       4 |  186- 251 |  133- 179 |   98- 131
       5 |  252- 327 |  180- 233 |  132- 171
       6 |  328- 414 |  234- 295 |  172- 217
       7 |  415- 518 |  296- 369 |  218- 271
       8 |  519- 641 |  370- 457 |  272- 336
       9 |  642- 790 |  458- 563 |  337- 414
      10 |  791- 970 |  564- 691 |  415- 508
      11 |  971-1190 |  692- 848 |  509- 623
      12 | 1191-1460 |  849-1041 |  624- 765
      13 | 1461-1797 | 1042-1281 |  766- 942
      14 | 1798-2223 | 1282-1585 |  943-1165
      15 | 2224-2774 | 1586-1978 | 1166-1454
      16 | 2775-3000 | 1979-2504 | 1455-1840
      17 |           | 2505-3000 | 1841-2383
      18 |           |           | 2384-3000
--------------------------------------------

From ttennis@bu.edu Fri Jan 21 00:39:04 1994
Subject: 3.3 CANADIAN TTA to USTTA RATING CONVERSION CHART
==========================================================

0000-0399 +670	1800-1899 +090	2350-2399 -050
0400-0699 +545	1900-1999 +055	2400-2449 -060
0700-0899 +460	2000-2049 +025	2450-2499 -065
0900-1099 +390	2050-2099 +010	2500-2549 -075
1100-1299 +315	2100-2149 -005	2550-2599 -085
1300-1499 +245	2150-2199 -015	2600-2649 -095
1500-1599 +195	2200-2249 -020	2650-2699 -100
1600-1699 +160	2250-2299 -030	2700-2749 -110
1700-1799 +125	2300-2349 -040	2750-2799 -120

From marcus@djmarcus.read.tasc.com Wed Feb 10 10:39:02 1993
Subject: 3.4 DOES IT MATTER WHO SERVES FIRST?
=============================================
(See p31 of Jan/Feb 91 TTTopics)

At the start of every match, assuming you win the coin flip (or the roll of
the ball), you  must decide  if  you want  to serve or  to receive. Does it
matter which you  choose?  Now, I  don't  mean  is  there  a  psychological
advantage.  To  see  what I mean  consider  chess. There  is a  significant
advantage to  having white in chess. Even if you prefer defense to offense,
you should take white. Or consider a game of volleyball. In volleyball your
team only scores points when  it  is serving. It is intuitively clear that,
given a choice, you should serve first.

So what about table tennis? Is there an actual advantage to serving first?
Before reading further, try to answer this question.

Let's  be  explicit  about  our  modeling  assumptions.  Assume   that  the
probability of winning a point only depends on which player is serving, and
in particular is independent of the score. First note that if the game goes
deuce, then  it  doesn't matter who served first since no matter  who wins,
each player will have served the same number of times.

What if  the  game doesn't go deuce? Consider the following modification of
the rules: Rather than stopping  when  one  player reaches 21, keep playing
until 40 points have been  played.  If you win the game under the  modified
rules, then you must win at least 21 of the  40 points and hence would have
won the game under  the  standard  rules.  Similarly  if you lose under the
modified rules, you  also  would have  lost under the standard  rules. But,
under the modified rules, both  players  serve 20 times  and so it  doesn't
matter which  one  served first. So the answer to  our question  is: No, it
doesn't matter who serves first.

How about handicap matches? Traditionally a handicap match is played as one
game to 51. In  order to analyze  this, modify the  rules so  we'll  play a
total of 100 points (unless we go deuce). Serve changes when the sum of the
scores  is a multiple of  5,  just as  in non-handicap  games. Let A be the
player who serves first and let B be the player who serves second.

Suppose the handicap is 1 point. Player A serves 4 points and then B serves
5 points, and the  rest  of the game  continues  normally with  each player
serving 5 points at a time. Hence A will serve a  total of 49 points and  B
will serve  a  total of 50. Therefore  you should  choose to  serve  second
(unless you are weird and are more likely to win a point when your opponent
serves). Now let's  consider a handicap of 5. Then player  A will  serve 50
points  and  B will  serve 45.  Therefore  you should  serve  first. If the
handicap is 10, then both  players  will serve 45 and it doesn't matter who
serves first.

Let's summarize what  you should do for handicap games. Only the last digit
matters (so  you want  to do the same  thing for a handicap of 17  as for a
handicap  of  7). If  the last digit  of the handicap is 0, then it doesn't
matter who serves first.  If the last  digit of the handicap is 1, 2, 3, or
4, then you  want to  serve second. If the last digit of the handicap is 5,
6, 7, 8, or 9, then you want to serve first.

We'll leave  doubles  for  a  future article  or  you  might  try  it as  a
(difficult) homework  problem. It  might also be interesting to analyze a 2
out of 3 handicap match where each game is to 21.

Perhaps a few words about psychological advantage is in order. If  there is
no real advantage  and the  players know this, then  there shouldn't be any
psychological advantage. However, if you know there is  no  real advantage,
but  your  opponent  doesn't,  then perhaps  you  can  get  a psychological
advantage by letting him serve first.

From Alexander.J.Chien@med.umich.edu Tue Feb 23 11:50:24 1993
Subject: 3.5. What is Speedglue ?
=================================

Speedglue, the glue used in the practice of regluing your rubbers, has been
used since the late  70's.  I believe  that the practice  was attributed to
Klampar or Surbek.  What  the players do before   each practice session  or
match is to peel off the rubber sheet from the wood blade,  put  fresh glue
on both the blade and rubber sheets, and replace the rubbers  back onto the
wood.  The secret is a solvent that is found in the glue  - most commonly -
trichloroethylene.  The trichloroethene  can  penetrate into  the molecular
network of the sponge effectively 'swelling' up the sponge (A crude analogy
may be taking a sponge that the hard when dry  and becomes soft  wneh wet).
The rubber sheet, when 'swelled' by tri-chloroethylene becomes much softer.
This will do a few things to your bat. The ball  can penetrate further into
the sponge of your  rubber, in effect, making more  contact with the blade.
Thus, the more contact  the ball has with  the  blade, the faster your shot
will be. Also, since you can sink the ball  further into the spong  you can
generate more spin.   The softer  sponge also markedly increases the  dwell
time that the ball stays  on  your racket -  so  it can also increase  your
control.  

Regluing is  more effective  with rubber sheets  that  have a  soft sponge.
The softer sponges have a less heavily cross-linked molecular  network than
hard sponges that allow the  solvents to  penetrate easier and swell/expand
the sponge easier. Thus, there will be more of a regluing effect if you use
a soft sponged  rubber. However, a  soft sponge will  lose  it's elastisity
faster than a hard sponge. 

Some disadvantages  come with  regluing.  The  first  disadvantage  is  the
decrease  in elasticity of the  sponge. When  trichloroethylene  penetrates
the  sponge and  breaks  apart molecular cross-links,  the  sponge  becomes
softer.  When  the  solvent  proceeds  to evaporate from  the  sponge,  the
cross-links are not in the same  condition as  they were before the solvent
was  applied, and  thus, a decrease  in  the elasticity/ resilience of  the
sponge.   After about  20 regluings, there can be a significant change from
the  original  character  of  the rubber.   The second  disadvantage is the
constant change is racket  angle when  playing.   The effect of the solvent
gradually decreases over time, and   constant modifications in  your racket
angle must  be done.  Also, regluing will add weight to  your bat each time
you reglue because of the extra  glue applied.  Finally, the  solvents used
are usually  very volatile, toxic, and could be  cancerous.

From ttennis@bu.edu Fri Jan 21 00:39:04 1994
Subject: 3.5.1 First PRESS RELEASE STATEMENT on SPEEDGLUE BAN
-------------------------------------------------------------
The ITTF Executive Board, at its meeting at Manchester on  14th of December
1992, received reports from scientific experts  in toxicology and chemistry
on  the harmful effects of  the Aromatic and   Chlorinated solvents used in
some types  of rubber adhesives.   On the  basis  of  these reports  it was
agreed  unanimously to  recommend  the Executive  Commitee to take   urgent
action to prevent the  use of such adhesives  by Table Tennis Players.  The
Executive Commitee accepted this recommendation and decided:

1. To impose an immediate ban in  events directly under ITTF  control, such
   as the Global Youth Championships in Tokyo in January 1993 and the World
   Championships in Gothnburg in May 1993; and 

2. To  ask   Continental   and National Federations    and  organisers   of
   international competitions to  enforce a similar  ban  in  events  under
   their control from 1st January 1
Any person, e.g. player, coach, official, responsible for contravening this
rule will  be liable to  immediate  disqualification and suspension  for at
least 3 months.  Where it is necessary for rubbers to  be replaced during a
competition it must be done in a designated place, under the supervision of
an official and using an adhesive supplied by the organiser. 

Manufacturers and suppliers are asked to discontinue  marketing of adhesive
containing Aromatic and  Chlorinated  solvents, and to   ensure  that their
products are clearly marked with the ingredients. 

Players and coaches  are  asked to cooperate  in  ensuring that the ban  is
observed. 

Manchester, December 15th, 1992.

Signed
Ichiro Ogimura, President.

From  hoens@gmd.de Tue Apr 30 10:38:13 1993
Subject: 3.5.2 WHAT SPEEDGLUES are ITTF-APPROVED?
-------------------------------------------------
this is the list of ittf-approved speed-glues,
list nr 3, dated 17.march93

Andro Fast, 		Butterfly Fair Chack, 	
Butterfly Pro Chack,	Changi Power Drive, 
Contra Speed, 		Donic Appelgren Puro,
Hanno Fresh, 		Joola Green, 
Juic Ecolo Effect,	Nittaku Banda Waldner Clean, 
Nittaku Rubber Dine,	Posno Spin Speed, 
Schildkroet TT Glue,	Schoeler & Micke Belagkleber,
Skitt Coppa Light,	Stiga Victory Tibhar,
Rapid Clean, 		TSP Norika Clean,
Victoria Belagkleber

From LEEEDWARDS@delphi.com Tue Nov 16 22:50:05 1993
Subject: 3.5.3 FIGHT THE GLUE BAN: ITTF vs TRUE
===============================================


            THE OSAKA VICE INCIDENT AND THE GLUE BAN
                 THE ITTF VERSION AND THE TRUTH
 
 
                        THE ITTF VERSION
 
       On December 4 the police raided a table tennis shop in
Osaka, Japan, and confiscated their stock of adhesives; the
resulting large headlines in the press were not flattering to
the sport.
       Good timing!  The Executive Board had to formulate a
recommendation, with no time for further inquiry or considered
deliberation.  Yet with publicity like that the ITTF could not
be seen to take no action.  The manufacturers had done nothing
to remove the problem, so the ITTF had to.  Failure to act could
result in very costly legal liability.
       The ITTF E.C. had to take immediate action after the
incident in Japan -- otherwise the amount of negative publicity
would have been extremely damaging to the sport, and the ITTF
could even have been subject to litigation.
       The ITTF's action last December was indeed a political
response to the police raid in Osaka, albeit a rather pragmatic
one.  For the fact is that headlines are headlines, and a
struggling sport like ours cannot afford bad ones.
 
                            THE TRUTH
 
       The police raid in Osaka was only reported in local
newspapers.  There was no report of it in newspapers in Tokyo.
It was too small an incident to be reported nationwide.  I would
be very much surprised if it was reported outside Japan.  It
was too small even to be handled nationwide.
       The start of the police raid was a phone call from parents
of a junior table tennis player.  She went to a table tennis
shop in Osaka and asked for that glue (a particular Japanese
brand containing the solvent toluene).  An employee explained
to her that if she was to used for glue sniffing, she should
do it secretly.  This was found out by her parents, who called
the police, and there was a raid.  The police confiscated the
glue from the store.  The thing was that the employee sold it
knowing it would be used for a purpose other than table tennis.
 
 
               THE MANUFACTURERS AND THE GLUE BAN
                 THE ITTF VERSION AND THE TRUTH
 
                        THE ITTF VERSION
 
 
       President Ogimura met in December with more than ten
manufacturers and reported on the problems associated with the
ban on certain types of glue.  The ITTF does expect all
manufacturers to adapt themselves to the new situation.
       a.  Announcement of harmless rubber adhesive for the
time being during the transition period.
       b.  Announcement of systems which will not require rubber
adhesive at all when players put rubber on their rackets.
       For example:
            1.  Rubber sheet which is coated with pressure
sensitive adhesive, and coated by cover paper.
            2.  A film which is coated by pressure sensitive
adhesive on both sides with cover papers for the use of those
rubbers without adhesive prefixed.
       Too much spin on the ball encourages short rallies. 
Even without speed glues, 10,000 rotations per minute have been
reported.  Mistakes by misjudging spin cannot be understood,
appreciated or cheered by spectators inside the arena and on
TV.  Out of this meeting the Japanese manufacturers agreed to
cooperate with the ITTF.
 
 
                            THE TRUTH
 
       The Manufacturers Panel has to correct the following
remark given at Mr. Ogimura's Press Conference on May 14th,
1993 "No manufacturers were against the decision."
       The Manufacturers Panel told the ITTF in the Manufacturers
Meeting:
       1.  We fully agree with ban of toxic glues as done by
the end of last year and fully assist the efforts of ITTF to
find a way to take out all harmful agents.
       2.  We feel that the way the glue problem has been handled
in this Championship (Gothenburg) is good, at least up to a
future solution to be acceptable for all (ITTF, Players,
Manufacturers).
       3.  We think that the question of ban glueing is no longer
only a problem of health, but of the view of developing our
sport (Mr. Ogimura likes to reduce speed and spin, which we
do not think is necessary).
       Besides the discussion about glueing we have demanded
several times during this meeting (to Mr. Ogimura and the
Equipment Committee) not to change any rule concerning material
without doing serious tests together with players and
manufacturers during a 2-years-period in advance.
       Gothenburg, May 19th, 1993
       On behalf of the Manufacturers Panel
       Butterfly                 Donic
       Joola                     Nittaku


From jaeger@is.informatik.uni-stuttgart.de Tue Jan 18 17:37:51 1994
Subject: 3.6  ITTF, ETTU, Computer Rank List, DECEMBER 1993
===========================================================

From jaeger@is.informatik.uni-stuttgart.de Tue Jan 18 17:37:51 1994
Subject: 3.6.1       MEN
------------------------
   world    europe points       name
  new old
    1   1      1    2043    Jan-Ove WALDNER		SWE
    2   3      2    1987    Jean-Michel SAIVE		BEL
    3   2      3    1983    Jean-Philippe GATIEN	FRA
    4   4           1965    WANG Tao			CHN
    5   5           1964    MA Wenge			CHN
    6   6           1951    KIM Taek Soo		KOR
    7  10      4    1929    Andrzej GRUBBA		POL
    8   7      5    1922    Peter KARLSSON		SWE
    9   9           1907    LI Gun Sang			PRK
   10   8      6    1896    Jrg ROSSKOPF		GER 
   11  10      7    1888    Jrgen PERSSON		SWE
   12  12      8    1885    Zoran PRIMORAC		CRO
   13  14      9    1882    CHEN Xinhua			ENG
   14  13           1853    Johnny HUANG		CAN
   15  15           1852    YOO Nam Kyu			KOR
   16  16           1849    KIM Song Hui		PRK
   17  17           1829    WANG Yonggang		CHN
   18  19           1810    LU Lin			CHN
   19  21           1802    LIU Guoliang		CHN
   20  17     10    1794    Erik LINDH			SWE
   21  20     11    1790    DING Yi			AUT
   22  22           1768    YU Shentong			CHN
   23  25           1750    Hiroshi SHIBUTANI		JPN
   24  26           1749    XIE Chaojie			CHN
   25  23     12    1737    Mikael APPELGREN		SWE
   26  23     13    1726    Steffen FETZNER		GER 
   27  27     14    1714    Carl PREAN			ENG
   28  32     15    1708    Petr KORBEL			CZE
   29  28           1702    Kiyoshi SAITO		JPN
   30  29           1686    KIM Guk Chol		PRK
   31  31           1683    WANG Hao			CHN
   32  33     16    1677    YANG Jianhua		LUX
   33  34     17    1676    Paul HALDAN			NED
   34  36           1662    LI Yi			CHN
   35  44     18    1659    Vladmir SAMSONOV		BLR
   36  37           1655    LEE Chul Seung		KOR
   37  50     19    1647    Thierry CABRERA		BEL
   38  39           1634    KANG Hee Chan		KOR
   39  40           1633    XIONG Ke			CHN
   40  35     20    1631    Georg-Zsolt Bhm		GER 
   41  42           1628    CHENG Yinghua		USA
   41  38     21    1628    Dimitri MAZUNOV		RUS
   41  42     21    1628    Ilija LUPULESKU		YUG
   44  40     23    1626    Peter FRANTZ		GER 
   45  46           1618    Koji MATSUSHITA		JPN
   46  47           1614    ZHANG Lei			CHN
   46  45     24    1614    Calin CREANGA		GRE
   48  47           1613    Yuji MATSUSHITA		JPN
   49  49           1612    LO Chuen Tsung		HKG
   50  52           1599    DONG Lun			CHN
   51  54           1591    CHOI Gyong Sop		PRK
   52  53     25    1585    Alan COOKE			ENG
   53  55     26    1583    Igor SOLOPOV		EST
   54  51     27    1577    Andrei MAZUNOV		RUS
   55  56           1573    WU Wen-Chila		TPE
   56  58     28    1558    Patrick CHILA		FRA
   57  57           1552    CHAN Kong Wah		HKG
   58  60           1544    KIM Myong Jun		PRK
   59  59     29    1543    Damien ELOI			FRA
   60  61     30    1538    Tomas JANCI			SVK
   61  64     31    1533    Andras PODPINKA		BEL
   62  63     32    1528    Zoran KALINIC		YUG
   63  62     33    1526    Philippe SAIVE		BEL
   64  69     34    1520    Trinko KEEN			NED
   65  67           1513    Kiyonobu IWASAKI		JPN
   66  68           1510    Toshio TAZAKI		JPN
   66  81           1510    LIN Zhigang			CHN
   68  66           1509    CHOO Kyo Sung		KOR
   69  74     35    1506    Danny HEISTER		NED
   70  70     36    1504    Leszek KUCHARSKI		POL
    .          .
  108 108     62    1371    Richard PRAUSE		GER 
  131 131     76    1284    Oliver ALKE			GER 
  140   -     81    1266    Thorben WOSIK		GER 
  143 149     83    1258    Christian DREHER		GER 
  183 170    104    1176    Sascha KSTNER		GER 
  199 190    112    1147    Thomas SCHRDER		GER 
  232   -    138    1083    Kay-Andrew GREIL		GER 



From jaeger@is.informatik.uni-stuttgart.de Tue Jan 18 17:37:51 1994
Subject: 3.6.2       WOMEN
--------------------------
    1   1           2251    DENG Yaping			CHN
    2   2           2123    QIAO Hong			CHN
    3   3           2085    HYUN Jung Hwa		KOR
    4   4           1996    GAO Jun			CHN
    5   5           1994    CHEN Zihe			CHN
    6   6           1992    LI Bun Hui			PRK
    7   7           1972    CHEN Jing			TPE
    8   8           1964    Chai Po Wa			HKG
    9   9           1941    YU Sun Bok			PRK
   10  10           1927    TANG Weiyi			CHN
   11  11           1918    JING Jun Hong		SIN
   12  12           1912    ZHANG Qin			CHN
   13  13           1908    LIU Wei			CHN
   14  18           1906    WANG Chen			CHN
   14  14           1906    GENG Lijuan			CAN
   16  15           1901    WU Na			CHN
   17  16           1895    ZHENG Yuan			CHN
   18  28      1    1889    Csilla BATORFI		HUN
   19  17      2    1882    Otilia BADESCU		ROM
   20  19           1879    HONG Soon Hwa		KOR
   21  19           1872    Chire KOYAMA		JPN
   22  21      3    1841    Bettine VRIESEKOOP		NED
   23  22           1840    CHAN Tan Lui		HKG
   24  23           1834    YING Ronghui		CHN
   25  25      4    1829    Nicole STRUSE		GER 
   26  24           1826    HONG Cha Ok			KOR
   27  27           1812    CHENG To			HKG
   28  29      5    1802    WANG-DRECHOU Xiaoming	FRA
   29  26           1799    LI Ju			CHN
   30  30      6    1797    Jie SCHPP			GER 
   31  31           1795    Fumiyo YAMASHITA		JPN
   32  32           1793    Li Mi Suk			PRK
   33  33           1792    QIAO Yunping		CHN
   34  34           1778    XU Jing			TPE
   35  35           1772    YANG Ying			CHN
   36  36           1765    AN Hui Suk			PRK
   37  37           1764    Diana HUANG			CAN
   38  38      7    1749    TU Dai Yong			SUI
   39  39           1737    WI Sun Bok			PRK
   40  40      8    1720    Elena TIMINA		RUS
   41  41      9    1719    Emilia Elena CIOSU		ROM
   42  42     10    1715    Daniela GERGELCHEVA		BUL
   43  44     11    1708    Mirjam HOOMAN		NED
   43  45     11    1708    Fliura ABBATE-BULATOVA	ITA
   45  43     13    1702    Lisa LOMAS			ENG
   46  46     14    1694    Marie SVENSSON		SWE
   47  48     15    1684    Jasna FAZLIC-LUPULESKU	YUG
   48  47           1668    ZHU Qingni			CHN
   49  49     16    1664    Olga NEMES			GER 
   49  51           1664    PARK Hae Jung		CHN
   51  52     17    1660    Asa SVENSSON		SWE
    .
   55  57     18    1619    Alessia ARISI		ITA
   56  55     19    1616    Irina PALINA		RUS
   56  60     19    1616    Krisztina TOTH		HUN
   58  59     21    1614    Galina MELNIK		RUS
   60  53     22    1609    NI Xialian			LUX
   61  62     23    1580    Pernilla PETTERSON		SWE
   63  63     24    1567    Polona FRELIH		SLO
   69  68     25    1526    Alison GORDON		ENG
    .
   90  92     39    1451    Christiane PRAEDEL		GER 
   99  99     45    1406    Elke SCHALL			GER 
  102 103     46    1396    Cornella FALTERMAIER	GER 
  137   -     72    1287    Christina FISCHER		GER 
  202 192    118    1140    Nicole DELLE		GER 
  207   -    121    1132    Nina WOLF			GER 


