How many clicks are there in the 1-1?
on moves 1, 2:
sum of 4 black 1-1 clicks is 6250
sum of 4 white 1-1 clicks is 3524
black tengen alone is 181 192 clicks
white tengen 71 067 clicks
these pictures are about difference, not about how top they are
Sorry i don’t understand.
on moves 1,2 ?
move number 1 (black), move number 2 (white)
1-1 is coordinate
yes
Does it mean that in the database 6250 games started with a 1-1?
In a large enough data set, there are bound to be some trolls and misclicks
I think it would make sense to filter out some of the very rare moves to reduce such noise
Timesujis?
For white 2 on 1-1 we have forgotten handicap
(For black 1 we could say forgotten handicap + wrong color)
And last we have full beginners too.
top 10, click to open, click to zoom
…
Top 10 coordinates are in the center for more than 100 moves, but then:
199:
200:
201:
202:
on all moves later top 10 coordinates are all on the 1st line
…it ends so fast and abruptly.
Maybe we need more than just relative frequency with different color, but relative click amount with different circle size, so it would be a better indication of the actual distribution (maybe a log-scale factor for relative size, so they won’t disappear with less than 1 pixel)
Exactly.
Titles aren’t very good for picking teaching games.
Of course there could be more looking for different languages (French, German, Japanese and so on). But choosing a title is completely free and based on player’s taste and creativity.
I also forgot to mention that some games have “teach” in their title just because one player has “teach” in his username and the game title is like vs
I could investigate further in remaining reverse komi games: removing all those with “teach” in the title and looking at the rest.
Considering all you’ve said, I don’t think this is representative of teaching games, unfortunately.
Why did you choose “teach” instead of “teaching game”? I don’t think it would be representative still, but, it would have made more sense no?
Need a language AI to decrypt what is teaching game
I agree.
Just because titles like “Please teach me” or "“will teach new and high kyu” seems actually tied to teaching games.
That brought also some false positives, but I can’t say which are more… big data are full of noise.
I just realised that I forgot to filter out annuled games from that sample!
There are 3555 games out of 15874 which should be removed:
Ranked | ||||
---|---|---|---|---|
Outcome | Board | False | True | Total |
Abandonment | 19x19 | 2 | 2 | |
Cancellation | 9x9 | 126 | 80 | 206 |
19x19 | 1036 | 153 | 1189 | |
Disconnection | 9x9 | 8 | 25 | 33 |
19x19 | 48 | 6 | 54 | |
Moderator Decision | 9x9 | 2 | 2 | |
19x19 | 5 | 5 | ||
Timeout | 9x9 | 313 | 214 | 527 |
19x19 | 938 | 599 | 1537 | |
Total | 2478 | 1077 | 3555 |
I didn’t mention resigned games (there’s 7701 of them) since I suppose that a teaching game could legitimately end by resignation.
Back to reverse komi:
In the chart that you quoted there were 70897 games. Only 147 of them have “teach” in their title.
Here is a breackdown of their outcome:
Outcome | Games |
---|---|
Cancellation | 3594 |
Disconnection | 440 |
Resignation | 29389 |
Score | 16090 |
Timeout | 21342 |
Total | 70855 |
Here are more frequent game titles:
Game Name | Games |
---|---|
Friendly Match | 14603 |
친선 대국 | 2631 |
友谊赛 | 2099 |
Online Lesson | 1589 |
親睦戦 | 1392 |
友谊对局 | 978 |
Let’s play go! | 851 |
Дружеский матч | 783 |
友誼對局 | 646 |
Freundschaftsspiel | 596 |
Partie amicale | 391 |
Partida amistosa | 327 |
go | 191 |
i get black, you get 50 komi | 151 |
Vriendschappelijke Wedstrijd | 125 |
Challenge from onigaijin4649 | 101 |
Challenge from lavb | 100 |
Looks like “Friendly game” in many languages.
Simply the default setting (which change with your language setting, 2cts guess)
Yes! I just deleted all moves with below average number of clicks from simulation.
move 186:
now these shapes are clear and make some sense
only then 1st line moves begin
2
4
6
12
24
50
100
200
250
300
https://forums.online-go.com/t/weak-score-estimator-and-japanese-rules/41041/70
here I showed Simple Score Estimator that works just like this:
it just floods in all 4 directions symmetrically, like this
But, I got new idea:
what if instead of flooding symmetrically, coordinates with the biggest number of clicks from real data will be painted?
each next iteration is from data(averaged by all 8 symmetries) from next move:
I summed number of clicks of each of 300 moves of both black and white
then averaged by all 8 symmetries
then replaced most popular move with 55, the most unpopular move with 1, …
(there are only 55 really different moves on 19x19 board)
1 | 2 | 3 | 8 | 10 | 9 | 6 | 4 | 5 | 7 | 5 | 4 | 6 | 9 | 10 | 8 | 3 | 2 | 1 |
2 | 11 | 12 | 17 | 19 | 18 | 16 | 14 | 13 | 15 | 13 | 14 | 16 | 18 | 19 | 17 | 12 | 11 | 2 |
3 | 12 | 49 | 53 | 47 | 54 | 40 | 46 | 45 | 50 | 45 | 46 | 40 | 54 | 47 | 53 | 49 | 12 | 3 |
8 | 17 | 53 | 55 | 44 | 51 | 41 | 43 | 42 | 52 | 42 | 43 | 41 | 51 | 44 | 55 | 53 | 17 | 8 |
10 | 19 | 47 | 44 | 20 | 39 | 31 | 35 | 25 | 36 | 25 | 35 | 31 | 39 | 20 | 44 | 47 | 19 | 10 |
9 | 18 | 54 | 51 | 39 | 37 | 34 | 30 | 27 | 38 | 27 | 30 | 34 | 37 | 39 | 51 | 54 | 18 | 9 |
6 | 16 | 40 | 41 | 31 | 34 | 32 | 28 | 24 | 33 | 24 | 28 | 32 | 34 | 31 | 41 | 40 | 16 | 6 |
4 | 14 | 46 | 43 | 35 | 30 | 28 | 26 | 23 | 29 | 23 | 26 | 28 | 30 | 35 | 43 | 46 | 14 | 4 |
5 | 13 | 45 | 42 | 25 | 27 | 24 | 23 | 21 | 22 | 21 | 23 | 24 | 27 | 25 | 42 | 45 | 13 | 5 |
7 | 15 | 50 | 52 | 36 | 38 | 33 | 29 | 22 | 48 | 22 | 29 | 33 | 38 | 36 | 52 | 50 | 15 | 7 |
5 | 13 | 45 | 42 | 25 | 27 | 24 | 23 | 21 | 22 | 21 | 23 | 24 | 27 | 25 | 42 | 45 | 13 | 5 |
4 | 14 | 46 | 43 | 35 | 30 | 28 | 26 | 23 | 29 | 23 | 26 | 28 | 30 | 35 | 43 | 46 | 14 | 4 |
6 | 16 | 40 | 41 | 31 | 34 | 32 | 28 | 24 | 33 | 24 | 28 | 32 | 34 | 31 | 41 | 40 | 16 | 6 |
9 | 18 | 54 | 51 | 39 | 37 | 34 | 30 | 27 | 38 | 27 | 30 | 34 | 37 | 39 | 51 | 54 | 18 | 9 |
10 | 19 | 47 | 44 | 20 | 39 | 31 | 35 | 25 | 36 | 25 | 35 | 31 | 39 | 20 | 44 | 47 | 19 | 10 |
8 | 17 | 53 | 55 | 44 | 51 | 41 | 43 | 42 | 52 | 42 | 43 | 41 | 51 | 44 | 55 | 53 | 17 | 8 |
3 | 12 | 49 | 53 | 47 | 54 | 40 | 46 | 45 | 50 | 45 | 46 | 40 | 54 | 47 | 53 | 49 | 12 | 3 |
2 | 11 | 12 | 17 | 19 | 18 | 16 | 14 | 13 | 15 | 13 | 14 | 16 | 18 | 19 | 17 | 12 | 11 | 2 |
1 | 2 | 3 | 8 | 10 | 9 | 6 | 4 | 5 | 7 | 5 | 4 | 6 | 9 | 10 | 8 | 3 | 2 | 1 |
Now, question is: why 5-5 point is so unpopular? Only 1st and 2nd line moves have less clicks. Moves around tengen have more clicks.
This is not center and not side, it is corner, close to most popular point.
difference between moves:
(the least popular marked as 1, point at the right is corner)
inside 1st line:
inside 2nd line:
inside 3rd line:
inside 4th line:
inside 5th line:
inside 6th line:
inside 7th line
inside 8th line:
inside 9th line:
difference between lines:
average of moves inside lines done, so lines are compared
most popular line marked as 10
(1st line at the top)
(tengen at the bottom)
Naturally, if something is close to the most popular point, chances are the most popular point is already occupied. Playing 5-5 when the 4-4 is already occupied does nothing, most of the time.
I’ve been thinking about game time settings (byo yomi and fischer really) and wondering which is popular and what actual times are typically or often used.
I suppose there will be peaks at the automatch time settings (I suppose I should know what these are…) but I’d like to know what settings are actually popular (or not) compared to the discussed that there have been in the forums from time to time.
I guess this data dump has this kind of info but I also suppose it’s not completely straightforward to pull out and present things in a meaningful way with all the various combinations of main time periods, increments etc. Even just looking at Fischer and byo-yomi might be too much but I figured there’s no harm in asking!
Indeed the data is easy to extract, the question is just how you want it presented
Here is an example of what info is stored and how:
"time_control": {
"time_control": "byoyomi",
"period_time": 30,
"main_time": 600,
"periods": 5,
"system": "byoyomi",
"speed": "live"
},
I’ll take a look at it in a day or two unless someone beats me to it (re-downloading the torrent now because I switched computers since I analysed this data last time).