Classic Tetris World Championship Elo ratings Options

[caffeine]

CODE

2017 NES Power Rankings

492 Jonas_N
409 Harry_H
332 Alex_K
310 Eli_M
306 Quaid
285 Koryan
234 Mike_W
228 Matt_B
224 Jeff_M
222 Bo_S
173 Ben_M
158 Trey_H
146 Jani_H
128 Terry_P
123 Chad_M

Edit: Recalculated without adding days between tournament due to more accurate figures using this method.

I was curious what it would look like to compute the Elo ratings of players based on historical CTWC win/loss data. I used this data for input to the program. If you find any mistakes, please let me know. I thought it would be best to use the Whole-History Rating method. It's more computationally expensive, but creates slightly more predictive results. Using the open source GoShrine library, here is the script I used to compute the ratings. Also, the raw output.

Generally, Elo ratings need several games before they are accurate. That's the main drawback here. The more tournaments played, and the more times a player makes it to the later rounds, the more accurate his or her ratings should be.

[wizard944]

This is cool! I kinda wanna do something similar for guideline tetris. Maybe I'll compile all the TTO results and try and make a rating ladder out of that. Any other tournaments that should be included? Maybe some of the HDO ones.

[caffeine]

I recomputed the ratings with the 2018 match results added in. Here is the input I used for the program. Please let me know if there are any errors. The format is [winner] vs [loser] [Winner wins = 'W', Winner loses = 'L']. For matches I could not find info on, I used "WLW."

CODE

2018 NES Power Rankings

569 Joseph_S
478 Jonas_N
399 Harry_H
387 Green_T
384 Koryan
313 Alex_K
306 ZZYZX
291 Eli_M
233 Svavar_G
230 Matt_B
172 Terry_P
169 Josh_T
165 Jeff_M
160 Ben_M
155 Trey_H
149 Jani_H
112 Chad_M

Edit: I ran the algorithm this time with 0 days elapsing between tournaments. It seems to be a more accurate method than adding 365 days between tournaments.
Edit2: Updated with more accurate 2018 round 0 info factored in.

[XaeL]

Wow, great work caffeine!

I think next year there will be 3-4 new players who will all place top 8, knocking out a lot of the old players.

[caffeine]

Out of curiosity, I wrote a Monte Carlo simulation for a hypothetical 16-player knock-out tournament. I modeled it using CTWC's format with the Elo ratings derived from the previous 7 CTWC tournaments as well as 2018/2019 Westcoast, Mideast, Eastcoast, Southern, and Desert Qualifiers. Got the data for many of the qualifier events that I couldn't find on video or FB from Chris_F's excellent database on the CTWC discord. Here's the program, and here's the output:

CODE

1st 2nd 3rd or more
28% 11% 61%  Joseph_S
19% 11% 70%  Jonas_N
11% 10% 79%  Green_T
9%  9%  81%  Harry_H
9%  9%  82%  Koryan
7%  8%  85%  DanQZ
4%  7%  89%  Alex_K
4%  6%  90%  Quaid
2%  5%  92%  Svavar_G
2%  5%  93%  Eli_M
2%  4%  94%  Noztrom
1%  4%  95%  Jeff_M
1%  4%  95%  Matt_B
1%  2%  97%  Bo_S
0%  2%  98%  Beastinshen
0%  2%  98%  Shakil_A

Edit: corrected method for finding probability of a win using WHR and reran the program.
Edit2: reran but with best of 5 matches for top 8.