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Professor Glickman on Glicko Scores - Shared screen with speaker view
Lucas Chu
15:30
Feel free to drop questions here! If you're curious, learn more about Dr. Glickman here: http://www.glicko.net/
Juan Moreno
19:16
there's some blinking in the top part of the presentation, is that on purpose or maybe some connection issues?
Mason Kadem
19:36
I’m having the same issue
Daniel
19:37
yeah can we fix that? It's giving me a headache
Char'les
19:38
bad screen capture from zoom on the slide show setting; yeah it’s painful.
Mason Hall
19:52
A bit better now
Lucas Chu
19:56
I think it's the connection. Btw if you have a question u want to say out loud raise ur hand. If you want to invite others, use https://harvard.zoom.us/my/coviz
Juan Moreno
20:26
Thank you very much!
jseen
20:48
Try to share the "powerpoint presentation" not the full screen
jseen
21:01
better!
Eric Wong
21:16
Hey, just curious if this webinar will be posted anywhere afterwards. I have a work meeting in about half an hour but I don't want to miss anything
Lucas Chu
21:37
Yup! We'll post the recording in /r/statistics, /r/chess, and on our newsletter
Daniel
22:00
Will it be emailed to people who registered?
Lucas Chu
22:22
Yup!
s
22:52
So right now we are talking about elo rating system right?
Daniel
23:57
Not really. We are talking about USCF ratings which are currently done on the Glickman system. In an informal sense, all ratings are 'elo' because the entire rating system was invented by Arpad Elo (mentioned in an early slide).
s
24:17
oh ok thanks!
Mason Hall
24:57
why the horizontal lines of dots?
Danny
25:16
most participants are within that age range
Juan Moreno
26:05
Some ranges in rating are apparently very repetitive no matter the age
Lucas Chu
26:27
I believe those are the rating cutoffs (Senior master 2400–2599Master 2200–2399Expert 2000–2199Class A 1800–1999, etc)
Mason Hall
27:00
That would make sense, nice
Daniel
27:21
Also the USCF has floors
Daniel
27:27
which causes people to eventually hit that floor
Juan Moreno
29:25
why the curve is not a sigmoid? just out of curiosity
Lucas Chu
31:27
the formula We = (1/(1+10(Rb-Ra)/400) graphs to a logistic curve
Lucas Chu
31:50
wait it is a sigmoid so I think you're right
Juan Moreno
34:40
Thanks for the answer
Juan Moreno
34:50
sorry didn't wrote anything
Daniel
42:37
So how would this graph handle correspondence ratings which have such a high draw level even between high rating differences?
Juan Moreno
42:47
some overestimation
Jimmy
44:02
This is similar to calculating alpha in finance
Jimmy
44:08
very interesting
nedal
44:52
what does 0.735 mean?
Juan Moreno
45:08
I assume its an adjustment
Jimmy
45:26
how is the .735 calculated?
nedal
45:37
so that number came by luck?
Juan Moreno
45:39
but it'll be nice to see some residuals plot of both curves and the actual results
Ioannis Asimakopoulos
45:47
it's not calculated. it is tested
Jimmy
45:52
ah
Juan Moreno
46:10
I think mark did a lot of tests to came to that number
Daniel
46:11
Thanks!
Jimmy
46:35
he could make a lot of money applying this to finance lol
Benedikt
47:22
is there really no way to fit a logistic regression to this without having to test numbers?
Sikdar Rohan
47:25
Following up on the previous question, do different implementations of the elo system normally tailor the We functions? Chess.com vs csgo, etc…
nedal
48:14
is the estimation done by ML ? (Maximum likelihood)
Juan Moreno
49:00
That would have to be done with ROC and a matrix
Benedikt
49:17
.5
Juan Moreno
49:18
I'm assuming he's summarizing his results.
Lucas Chu
49:18
i mean if its meaningless, .5?
woumo
49:18
.5
nedal
49:22
Ah thank you
nicholas teoh wen hao
49:23
0.5?
Ioannis Asimakopoulos
50:01
Has he shown whether this 0.64 would result to a rating gain and basically how rating gain correlates with the winning expectancy?
Benedikt
51:29
the ratings would stay the same
Ioannis Asimakopoulos
51:41
Let's say, if you face opponents that are always lower rated than you, would you gain rating?
Eric Wong
51:55
I think he's about to transition into Glicko rating talks, get excited!
Benedikt
52:10
if you win more than you are expected, yes
Eric Wong
53:29
@ioannis this is actually an exploit that has happened before in fide. They capped the maximum rating difference to 200 elo but several players began to play exclusively with players much much weaker than them. But without this cap you can only gain rating if you win more than expected, which would be a fairly high rate
Jimmy
54:19
makes sense. someone in the comment section was explaining that.
Ioannis Asimakopoulos
54:27
thanks
Eric Wong
54:46
If anything you would likely lose rating if you kept playing with low rated players because the expected curve demands a higher win rate than what we see in reality
Ioannis Asimakopoulos
55:07
yes that's what I thought
Ioannis Asimakopoulos
01:01:19
that sounds like Kalman filters
Benedikt
01:01:38
is it possible for the standard deviations to increase with more games being played?
LV
01:03:08
you mean when the results are unexpected?
Benedikt
01:03:09
for example when you lose against someone much lower rated or win against someone much higher rated
Benedikt
01:03:15
yes
Lucas Chu
01:04:05
https://www.wikiwand.com/en/Glicko_rating_system
Vivian Duong
01:04:55
Thank you!! I need to leave now, but I really enjoyed this seminar!
Ioannis Asimakopoulos
01:08:53
So the rating updates after every game in the tournament, or you hold the R and s for the whole tournament? This affects pairings
Ioannis Asimakopoulos
01:13:05
ok answered
Danny
01:13:32
I have to head out too, Thanks! I enjoyed it.
Lucas Chu
01:13:33
Are there any ways to exploit either the elo or Glicko system? e.g. given the elo system overpredicts win expectancy, would playing against higher rated players (with higher standard deviations) on average raise your ranking?
Benedikt
01:16:01
i guess you would need to find people willing to play a lower rated player continously. Additionally, a lot of tournaments have entry requirements for your rating.
Lucas Chu
01:17:16
still around! http://freechess.org/
LV
01:17:51
how does using absolute values for the calculation of the standard deviation effect the predictability of the model? (instead of the normal sd formula)
Mason Hall
01:20:37
Are their any applications of Glicko/ELO that you wish existed?
Benedikt
01:20:50
underlords did for a while, but i think they changed it back to elo for whatever reason.
Jimmy
01:20:52
I love how he's showing games I've never heard of that use his system
Adit Seth
01:21:12
Don't valve competitive games also use glicko? TF2 and CSGO?
Lucas Chu
01:22:00
CS:GO and Overwatch use Match Making Ranks, which according to a leak is initially based on the Glicko-2 ranking system. They have millions of players, for reference
Benedikt
01:22:28
isnt that basically what irt and rasch/Birnbaum-models are About?
Jimmy
01:22:51
thank you for allowing us chess nerds join in!
Mary Davis
01:22:52
Thanks!
Diogo Koch Alves
01:22:55
Thank you!
nedal
01:22:58
Thank you
LV
01:22:59
so many questions!
Daniel
01:23:00
We are all muted
Mason Hall
01:23:04
Are their any applications of Glicko/ELO that you wish existed?
Daniel
01:23:07
So are you familiar with ICCF and its deflation?
Daniel
01:23:17
If so, how would you solve for deflation/draw rate
nicholas teoh wen hao
01:23:31
Are there any aspects of the glicko system that is inferior to the traditional elo system?
RL
01:24:13
are there any rating differences for playing as white or black? is an adjustment in the rating difference ever applied?
Lucas Chu
01:29:56
last two questions
Mason Hall
01:33:05
Thanks again!