Logiqx
Member
Latest update (2020-02-13)
Updated charts - https://docs.google.com/spreadsheets/d/1ZnClqXZ1dHVvFIoBk0SCSl-5m34tV6mNtc2vldHhEXM/edit?usp=sharing
SQL - https://github.com/Logiqx/wca-stats/blob/master/sql/misc/relative_solve_times.sql
Original Post
I wondered if there might be a rule of thumb which can be used to calculate comparable solve times (e.g. 4x4x4 vs 3x3x3, 5x5x5 vs 4x4x4, etc). I decided to see what I could find out using the WCA data and I've producing the graph below using peoples best average in each event.
The horizontal axis splits everyone into "vigintiles" (20 groups, 5% in each) based on their ranking for a particular puzzle. For example: The green line (4x4x4 vs 3x3x3) tells us the top 5% in the 4x4x4 rankings take 4 times longer to solve a 4x4x4 than they do a 3x3x3, based on their best average for each event. Conversely the slowest 5% have a 4x4x4 average which is almost 7 times their 3x3x3 average.
Aiming for the ratio towards the left hand side seems like a good goal for people looking to improve at a specific event.
Here are some high-level ratios across the categories (2x2x2/3x3x3, 4x4x4/3x3x3, 5x5x5/4x4x4, 6x6x6/5x5x5, 7x7x7/6x6x6):
Min: 0.30, 4.04, 1.86, 1.98, 1.43
IQM: 0.39, 4.89, 2.03, 2.18, 1.57
Mean: 0.41, 5.01, 2.07, 2.20, 1.57
Max: 0.60, 6.79, 2.51, 2.58, 1.73
I've found this graph quite interesting so I figured one or two of you might like it as well!
Updated charts - https://docs.google.com/spreadsheets/d/1ZnClqXZ1dHVvFIoBk0SCSl-5m34tV6mNtc2vldHhEXM/edit?usp=sharing
SQL - https://github.com/Logiqx/wca-stats/blob/master/sql/misc/relative_solve_times.sql
Original Post
I wondered if there might be a rule of thumb which can be used to calculate comparable solve times (e.g. 4x4x4 vs 3x3x3, 5x5x5 vs 4x4x4, etc). I decided to see what I could find out using the WCA data and I've producing the graph below using peoples best average in each event.
The horizontal axis splits everyone into "vigintiles" (20 groups, 5% in each) based on their ranking for a particular puzzle. For example: The green line (4x4x4 vs 3x3x3) tells us the top 5% in the 4x4x4 rankings take 4 times longer to solve a 4x4x4 than they do a 3x3x3, based on their best average for each event. Conversely the slowest 5% have a 4x4x4 average which is almost 7 times their 3x3x3 average.
Aiming for the ratio towards the left hand side seems like a good goal for people looking to improve at a specific event.
Here are some high-level ratios across the categories (2x2x2/3x3x3, 4x4x4/3x3x3, 5x5x5/4x4x4, 6x6x6/5x5x5, 7x7x7/6x6x6):
Min: 0.30, 4.04, 1.86, 1.98, 1.43
IQM: 0.39, 4.89, 2.03, 2.18, 1.57
Mean: 0.41, 5.01, 2.07, 2.20, 1.57
Max: 0.60, 6.79, 2.51, 2.58, 1.73
I've found this graph quite interesting so I figured one or two of you might like it as well!
Last edited: