We analyzed a total of {{res['sample_size']}} games, of player {{res['name_in_games']}}, from January 2016.

Hmm, {{res['sample_size']}} games is not very much and the results are thus not reliable, try to upload at least 20 games. Ideally, you should upload 30-40 games.

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# Black White Date Setup Result
1 darkfmcts3 [5d] haha123 2016-01-04 19×19 Komi 7.50 B+Resign
2 AyaMC5 [4d] darkfmcts3 [5d] 2016-01-04 19×19 Komi 7.50 W+Resign
3 droplet [4d] darkfmcts3 [5d] 2016-01-04 19×19 Komi 0.50 W+1.50
4 TOSHI1011 [5d] darkfmcts3 [5d] 2016-01-05 19×19 Komi 7.50 W+Resign
5 droplet [4d] darkfmcts3 [5d] 2016-01-05 19×19 Komi 7.50 W+0.50
6 darkfmcts3 [5d] gammaray 2016-01-06 19×19 Komi 7.50 B+Resign
7 darkfmcts3 [5d] gammaray 2016-01-06 19×19 Komi 7.50 B+Resign
8 darkfmcts3 [5d] gammaray 2016-01-06 19×19 Komi 7.50 B+11.50
9 straycat darkfmcts3 [5d] 2016-01-06 19×19 Komi 7.50 B+Resign
10 TOSHI1011 [5d] darkfmcts3 [5d] 2016-01-06 19×19 Komi 7.50 B+29.50
11 gammaray darkfmcts3 [5d] 2016-01-06 19×19 Komi 7.50 W+Resign
12 Jermelle darkfmcts3 [5d] 2016-01-06 19×19 Komi 7.50 W+Resign
13 gammaray darkfmcts3 [5d] 2016-01-06 19×19 Komi 7.50 W+Resign
14 darkfmcts3 [5d] tgashaun [5d] 2016-01-07 19×19 Komi 7.50 W+10.50
15 darkfmcts3 [5d] rsun 2016-01-07 19×19 Komi 7.50 B+29.50
16 inseon888 darkfmcts3 [5d] 2016-01-07 19×19 Komi 0.50 W+Resign
17 akbnn darkfmcts3 [5d] 2016-01-07 19×19 Komi 7.50 W+Resign
18 inseon888 darkfmcts3 [5d] 2016-01-07 19×19 Komi 7.50 W+Time
19 Q31 [2d] darkfmcts3 [5d] 2016-01-08 19×19 Komi 0.50 W+Time
20 harlej9k darkfmcts3 [5d] 2016-01-08 19×19 Komi 7.50 W+Resign
21 lwhite [4d] darkfmcts3 [5d] 2016-01-08 19×19 Komi 0.50 B+36.50
22 darkfmcts3 [5d] YZ1508 [4d] 2016-01-09 19×19 Komi 0.50 B+Time
23 darkfmcts3 [5d] haha123 2016-01-09 19×19 Komi 7.50 B+Resign
24 TOSHI1011 [5d] darkfmcts3 [5d] 2016-01-09 19×19 Komi 7.50 W+Resign
25 Riyadh [2d] darkfmcts3 [5d] 2016-01-09 19×19 Komi 0.50 W+Time
26 TOSHI1011 [5d] darkfmcts3 [5d] 2016-01-09 19×19 Komi 7.50 W+2.50
27 Noobmaster [1d] darkfmcts3 [5d] 2016-01-09 19×19 Komi 0.50 W+Resign
28 low darkfmcts3 [5d] 2016-01-09 19×19 Komi 7.50 W+0.50
29 darkfmcts3 [5d] haha123 2016-01-10 19×19 Komi 7.50 B+Resign
30 darkfmcts3 [5d] haha123 2016-01-10 19×19 Komi 7.50 B+Resign
31 darkfmcts3 [5d] Zen19S [5d] 2016-01-10 19×19 Komi 7.50 W+Time
32 darkfmcts3 [5d] haha123 2016-01-10 19×19 Komi 7.50 B+Resign
33 DoctorNo [4d] darkfmcts3 [5d] 2016-01-10 19×19 Komi 0.50 B+23.50
34 AyaMC [3d] darkfmcts3 [5d] 2016-01-10 19×19 Komi 7.50 W+Resign
35 haha123 darkfmcts3 [5d] 2016-01-10 19×19 Komi 7.50 W+Resign
36 GoRockets [4k] darkfmcts3 [5d] 2016-01-10 19×19 Komi 0.50 W+Time
37 DoctorNo [4d] darkfmcts3 [5d] 2016-01-10 19×19 Komi 0.50 W+Resign
38 WeakBot darkfmcts3 [5d] 2016-01-10 19×19 Komi 7.50 W+Resign
39 darkfmcts3 [5d] TOSHI1011 [5d] 2016-01-11 19×19 Komi 7.50 B+Resign
40 darkfmcts3 [5d] Zen19 [5d] 2016-01-11 19×19 Komi 7.50 W+44.50

The bold player is the victor in particular games, the player we analyzed is marked by an arrow (and is always the same).

Based on the patterns and other information extracted from the moves played, we estimated your strength and playing style. If you want to learn more about the methodology, please see the research section of the homepage. Below, we give you the results:

Please keep in mind, that the stuff here may be wrong and it is not – yet :-) – a substitute for a teacher you can interact with. We will keep this result webpage for at least 2 months (before deleting it).


Strength

The KGS equivalent of strength of the player: {{res['str']['val']}} ± {{res['str']['sigma']}}

The following image shows the strength (red line) with 68% confidence interval (blue line). The confidence is accurate only when the sample is large enough.
Strength: {{res['str']['val']}} ± {{res['str']['sigma']}}

Style

Please bear in mind, that the style information is not very reliable for weaker players, it might be completely off.

{{questionare.long_names[key]}} {{questionare.left[key]}} {{questionare.long_names[key]}}: {{res[key]['val']}} ± {{res[key]['sigma']}} {{questionare.right[key]}}

Based on this style evaluation, we recommend to review games of the following professional players. We list both proffesional players who have similar style as you and whose style is very different. The first group might serve to improve your style, the second to give inspiration what other styles of play are possible.

Professionals who have similar style as you:

Professionals whose style is farthest from yours:

Study material recommendations

This section lists study materials we believe are relevant for your improvement. The list is constructed by computing a suitability measure, which takes into account your strength and style. The measure is expressed as estimated percentual match. Brought to you in cooperation with GoGameGuru.

Generally speaking, we recommend Advanced books. More detailed tips follow.

Series

We find the following series of books to be suitable:

Books

Apart from the series, we recommend the following single books:

Distinctive patterns and tips

Bad things you play

Hmm, we've got nothing to say to you..

Other notable stuff

The following table shows some typical patterns that stronger players play more than you (on average). The scales on the right show the relative frequency of the moves: "The move is played every Xth game.". The strong players are on the left, weak on the right, your frequency estimated from the sample is the red bar.

You can get some inspiration here! ;-) Do not take this too seriously, though...



Do you like this app? Please, tell your friends!


Your feedback

Is greatly welcome. Do you think that your strength is different or your playing style is estimated wrongly?

You can help us to improve this application, by submitting correct information about you!!


If unsure what your KGS strength equivalent is, see the rank comparison.

And fill in what you consider to be your style:
{{radio_id}}
{{questionare.long_names[key]}} {{questionare.left[key]}} {{questionare.right[key]}}

Finally, you can send us some feedback if you want to. Tips, praise :-), etc..



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