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rec.sport.table-tennis FAQ: game-misc [Part 3/8]


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Archive-name: table-tennis/3_game-misc
Version: 12.0

See reader questions & answers on this topic! - Help others by sharing your knowledge
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 USATT Rating system works?
   3.2.2 What is the probablility of winning?
   3.2.3 Handicap Charts
   3.3. Canadian TTA to USATT 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 
   3.6.1 MEN RANK [95FEB]
   3.6.2 WOMEN RANK [94SEP] 

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

	ttennis@bu.edu

From djmarcus@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 djmarcus@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 djmarcus@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 djmarcus@tasc.com Wed Feb 10 10:38:58 1993
Subject: 3.2.1 HOW DOES USATT 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 USATT 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 djmarcus@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 djmarcus@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 USATT 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 djmarcus@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 paulsenr@gaya.nki.no Wed Dec 06 09:45:52 1995
Subject: 3.6  ITTF, ETTU, World Rank List, Nov 1995
===================================================

I have now posted the latest world ranking on my site, if you want to
take a look at it, you will find it at:

http://gaya.nki.no:80/~paulsenr/fokus/wran1195.htm


From jaeger@is.informatik.uni-stuttgart.de Tue Mar 21 17:10:29 1995
Subject: 3.6.1       MEN (Sep95)
--------------------------------
  World         Europe
 New Old

   1   1  1662    1     Jean-Michel SAIVE               BEL
   2   2  1616          WANG Tao                        CHN
   3   6  1597    2     Jean-Philippe GATIEN            FRA
   4   7  1587          KIM Taek Soo                    KOR
   5   3  1584    3     Jan-Ove WALDNER                 SWE
   6   7  1562    4     Zoran PRIMORAC                  CRO
   7   4  1545          MA Wenge                        CHN
   8   9  1534    5     Jörg ROSSKOPF                   GER
   9  10  1527          LI Gun Sang                     PRK
  10   4  1525    6     Peter KARLSSON                  SWE
  11  11  1509    7     Andrzej GRUBBA                  POL
  12  13  1508          KONG Linhui                     CHN
  13  12  1503          LIU Gouliang                    CHN
  14  14  1501    8     Jörgen PERSSON                  SWE
  15  15  1493          Johnny HUANG                    CAN
  16  16  1473          KIM Song Hui                    PRK
  17  18  1468          YOO Nam Kyu                     KOR
  18  17  1464          WANG Yonggang                   CHN
  19  18  1463    9     CHEN Xinhua                     ENG
  20  20  1430          LU Lin                          CHN
  21  21  1414          DING Song                       CHN
  22  22  1401          XIE Chaojie                     CHN
  23  23  1376          WANG Hao                        CHN
  24  24  1374          Hiroshi SHIBUTANI               JPN
  25  24  1365   10     DING Yi                         AUT
  26  26  1360   11     Vladimir SAMSONOV               BLR
  27  28  1356   12     Erik LINDH                      SWE
  28  34  1349          LIN Zhigang                     CHN
  29  29  1348          Kiyoshi SAITOH                  JPN
  30  46  1347          XIONG Ke                        CHN
  31  27  1346   13     Patrick CHILA                   FRA
  32  30  1342   14     Mikael APPELGREN                SWE
  33  31  1341   15     Petr KORBEL                     CZE
  34  32  1337   16     Carl PREAN                      ENG
  35  37  1335          CHENG Yinghua                   USA
  36  33  1325   17     Philippe SAIVE                  BEL
  37  35  1323   18     Calin CREANGA                   GRE
  38  42  1317   19     Dimitri MAZUNOV                 RUS
  39  36  1315          ZHANG Lei                       CHN
  40  62  1313   20     Damien ELOI                     FRA
  41  48  1306   21     Thierry CABRERA                 BEL
  42  38  1305          Iljia LUPULESKU                 USA
  43  40  1304          KANG Hee Chan                   KOR
  44  41  1303   22     Steffen FETZNER                 GER
  45  42  1299          LEE Chul Seung                  KOR
  45  42  1299   23     Georg-Zsolt BÖHM                GER
  47  45  1297   24     Andreas Podpinka                BEL
  48  38  1295   25     Paul HALDAN                     NED
  49  50  1294   26     Andrei MAZUNOV                  RUS
  50  62  1293          Koji MATSUSHITA                 JPN
  51  47  1292          LO Chuen Tsung                  HKG
  52  49  1278          DONG Lun                        CHN
  53  51  1277   27     Peter FRANZ                     GER
  54  52  1275          CHOI Gyong Sop                  PRK
  55  54  1272   28     Igor SOLOPOV                    EST
  56  57  1260   29     Trinko KEEN                     NED
  57  65  1255   30     Alan COOKE                      ENG
  58  56  1249   31     YANG Min                        ITA
  59  59  1245          CHAN Kong Wah                   HKG
  60   -  1244          IWASAKI Kiyonobu                JPN
  61  64  1236          KIM Myong Jun                   PRK
  62  63  1234   32     Vasile FLOREA                   ROM
  63  61  1233   33     Christophe LEGOUT               FRA
  63  60  1233          WU Wen-Chia                     TPE
  65  66  1231          MATSUSHITA Yuji                 JPN
  65  67  1231   34     Matthew SYED                    ENG
  67   -  1224   35     Danny HEISTER                   NED
  68  65  1218   36     Olivier MARMUREK                FRA
  69  75  1212   37     Thomas VON SCHEELE              SWE
  69  71  1212   38     Lucjan BLASZCZYK                POL
  71  69  1211   39     Tomas JANCI                     SVK
  72  72  1208   40     Zoran KALINIC                   YUG
  72  70  1208          CHU Kyo Sung                    KOR
  72  70  1208          WANG Fei                        CHN
  75  74  1207   41     Roland VIMI                     SVK
   .   .     .    .
  81  81  1182   46     Richard PRAUSE                  GER
 147 139  1033   82     Oliver ALKE                     GER
 150 144  1031   84     Christian DREHER                GER
 151 142  1030   85     Torben WOSIK                    GER
 218 190   907  123     Sascha KÖSTNER                  GER
 222 215   898  127     Thomas SCHRÖDER                 GER
 238 246   880  136     Kay-Andrew GREIL                GER
 306   -   806  181     Thomas KEINATH                  GER

                                                (02/1995)

From jaeger@is.informatik.uni-stuttgart.de Tue Feb 18 17:37:51 1994
Subject: 3.6.2       WOMEN (Sep94)
----------------------------------

   1   1  2258          DENG Yaping                     CHN
   2   2  2087          QIAN Hong                       CHN
   3   3  2002          GAO Jun                         CHN
   4   5  2000          Chai Po Wa                      HKG
   5   4  1995          CHEN Zihe                       CHN
   6  11  1966          LIU Wei                         CHN
   7  10  1961          TANG Weiyi                      CHN
   8   6  1952          WANG Chen                       CHN
   9   7  1949          LI Bun Hui                      PRK
  10   6  1937          CHEN Jing                       TPE
  11   9  1932          YU Sun Bok                      PRK
  12  14  1906          GENG Lijuna                     CAN
  13  12  1903          JING Jun Hong                   SIN
  14  16  1897          WU Na                           CHN
  15  15  1894          ZHENG Yuan                      CHN
  16  16  1890          Chire KOYAMA                    JPN
  17  18  1870    1     Jie Schöpp                      GER
  18  20  1853    2     Csilla BATORFI                  HUN
  18  19  1853    2     Otilia BADESCU                  ROM
  20  22  1848          CHAN Tan Lui                    HKG
  21  21  1836    4     Nicole STRUSE                   GER
  22  23  1832          YING Ronghui                    CHN
  23  24  1827    5     Bettine VRIESEKOOP              NED
  24   -  1794          QIAO Yunping                    CHN
  25  26  1790          LI Mi Suk                       PRK
  26  28  1785          LI Ju                           CHN
  27  30  1782          YANG Ying                       CHN
  28  27  1778          Fumiyo YAMASHITA                JPN
  29  29  1774          XU Jing                         TPE
  30  30  1773    6     Xiaoming WANG-DRECHOU           FRA
  31  25  1766          CHENG To                        HKG
  32  32  1764          AN Hui Suk                      PRK
  32  33  1764          Diana HUANG                     CAN
  34  34  1753    7     Fliura ABBATE-BULATOVA          ITA
  35  35  1747    8     Marie SVENSSON                  SWE
  36  36  1740    9     TU Dai Yong                     SUI
  37  38  1738          WI Sun Bok                      PRK
  38  38  1714   10     Emilia Elena CIOSU              ROM
  39   -  1705          LEE Kyung Sun                   KOR
  40  46  1701          PARK Hae Jung                   KOR
  41  48  1689          PARK Kyung Hae                  KOR
  42  42  1685   11     Jasna FAZLIC-LUPULESCU          YUG
  42  42  1685   11     Olga NEMES                      GER
  44  41  1684          LEE Jung Im                     KOR
  45  39  1677   13     Elena TIMINA                    RUS
  46  44  1669   14     Daniela GERGELCHEVA             BUL
  46  45  1669   14     Alena SUCHANKOVA                CZE
  48  43  1668   16     Mirjam HOOMAN                   NED
  49   -  1666          Mitsue ENDO                     JPN
  50  47  1656   17     Galina MELNIK                   RUS
  51   -  1654          LEE Tae Joo                     KOR
  52  48  1651   18     Asa SVENSSON                    SWE
  53  50  1649   19     Lisa LOMAS                      ENG
  54  52  1642   20     Krisztina TOTH                  HUN
  55  51  1640          KIM Boon Sik                    KOR
  56  56  1639   21     Irina PALINA                    RUS
  56  66  1639          RYU Ji Hye                      KOR
  58  53  1638   22     Valentna POPOVA                 SVK
  59   -  1632          JUN-FENG Amy                    USA
  60  58  1617   23     NI Xialian                      LUX
  61  57  1615          GAO Dong Ping                   SIN
  62  59  1610   24     Alessia ARISI                   ITA
  62  54  1610          Rika SATO                       JPN
  64  70  1609          LI Chunli                       NZL
  65  60  1603   25     Gerdie KEEN                     NED
   .   .     .    .
  95  93  1447   44     Christiane PRAEDEL              GER
 102 101  1411   48     Elke SCHALL                     GER
 136 138  1303   72     Christina FISCHER               GER
 213 217  1145  126     Nicole DELLE                    GER
 222 224  1132  132     Nina WOLF                       GER
 228 231  1121  137     Cornelia BÖTTCHER               GER
 247 252  1091  146     Sandra STROEZEL                 GER

                                                (08/1994)

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