| Step | Algs | Move Count | MCC |
| 1st Layer | 0 | 4.03 | 6.03 |
| CLL | 40 | 9.25 | 12.65 |
| AUF | 0 | 1.5 | 1.5 |
| Total | 40 | 14.78 | 20.18 |
| Step | Algs | Move Count | MCC |
| EG Layer | 0 | 2.97 | 4.97 |
| EG-1 | 40 | 9.67 | 12.72 |
| AUF | 0 | 1.5 | 1.5 |
| Total | 40 | 14.14 | 19.19 |
| Step | Algs | Move Count | MCC | |
| EG Layer | 0 | 4.03 | 6.03 | |
| EG-2 |
| 9.62 | 14.75 | |
| AUF | 0 | 1.5 | 1.5 | |
| Total | 40 | 15.15 | 22.28 |
| Step | Algs | Move Count | MCC |
| EG Layer | 0 | 3.32 | 5.32 |
| CLL/EG-1/EG-2 | 120 | 9.59 | 13.04 |
| AUF | 0 | 1.5 | 1.5 |
| Total | 120 | 14.41 | 19.86 |
| Step | Algs | Movecount | MCC |
| Guimond Layer | 0 | 0.16 | 0.16 |
| Guimond CO | 15 | 4.13 | 5.11 |
| NLL-1 | 36 | 7.41 | 10.79 |
| AUF | 0 | 2.25 | 2.25 |
| Total | 51 | 13.95 | 18.31 |
| Step | Algs | Move Count | MCC |
| Guimond Layer | 0 | 0.16 | 0.16 |
| Guimond CO | 15 | 4.13 | 5.11 |
| NLL-2 | 36 | 7.71 | 11.5 |
| AUF | 0 | 2.25 | 2.25 |
| Total | 51 | 14.25 | 19.02 |
| Step | Alg | Move Count | MCC |
| Guimond Layer | 0 | .16 | .16 |
| Guimond CO | 15 | 4.13 | 5.11 |
| NLL-1/NLL-2 | 72 | 7.56 | 11.14 |
| AUF | 0 | 2.25 | 2.25 |
| Total | 87 | 14.1 | 18.66 |
Notes:
All of these stats are based off of Cubestuff's average movecount distribution for 1st step per method. Algs were taken from speedcube database for CLL/EG-1/EG-1. NLL algs have be redeveloped by me which will be released shortly.
MCC was not developed for 2x2 algs so that calculation may be subject to change. A good amount of NLL algs have double turns so I'm not sure if that is considered good or bad.
For CLL/EG-1/EG-2 I did not go through to find the most ergo-optimal algs for each case unlike I've done with the NLL re-development. The CLL/EG algs are chosen off of the first alg listed on speedcube database. For CLL/EG MCC could be subject to change. Also of note is that I have no way of calculating the MCC of a CLL/EG face so I just added a +2. I feel that is relatively fair but you guys can let me know if I need to change that.
Based off the current calculations HD-G is statistically both the most efficient and ergonomic. Again I would take the MCC with a grain of salt although I am rather confident of the movecount stats.
Thoughts:
Overall this has been a rather exciting comparison of methods. It has confirmed my suspicions that HD-G is a competitive with CLL/EG-1/EG-2. Another large advantage of HD-G is the ease of 1-looking as the average movecount of the first step is only 0.16 moves and at most 2 moves. This allows you to consistently look farther into the solve during inspection. There is of course also the fact that HD-G boasts only 51 algs compared to 120 of CLL/EG-1/EG-2 combination.
I am rather surprised that not only HD-G held up well against the top level method but also that it surpassed it in both movecount and ergonomics. The good news for all cubers that hate learning algs is that there is now confirmed a highly competitive method that has a much fewer algs to learn!!
Though, criticism, input are welcome. Let me know your thoughts!!
Cheers!
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