CriticalCubing
Member
No More PLL 3x3 Rubik's Cube Method (decided on a name xD).
*NMP* is a speedcubing method which uses 4c instead of PLL. You make your cross differently, solve F2L (the same way you do CFOP), COLL and 4c.
It has all the advantages of CFOP (doesn't handicap the CFOP flow), is more efficient than CFOP on average (I'm getting 45-47 stm solves), and the speedsolve can be done pauselessly since 4c is easily predicted, and during F2L, you can predict your corners case (CP). You can also achieve the same TPS that you get with CFOP, using this method and lookahead is similar to CFOP lookahead (so you won't need to re-learn lookahead)
Why is this method good?
This method provides an alternate finish to CFOP which has a lower move count, yet still allows for fast TPS and lookahead/prediction ability. Solving with PLL gives rise to bad cases like F/V/Y/N perms which you’ll never get with this approach. Plus, the worst 4c cases are 8 moves which just requires 8.08 TPS to sub 1. Since, these cases are all alg based (like U perm), you can achieve much faster TPS than 8 TPS. Let’s take a detail look.
3 Last-Step Methods
CMLL + LSE
This is standard for Roux. Avg movecount: 10 CMLL (computed from avg of all the algs in my cmll sheet + 0.25 AUF) + 13 LSE (assuming 8 EOLR/EOFB and 5 4c, essentially the most advanced LSE there is) = 23 STM total
OLL + PLL
This is standard for CFOP. Avg movecount: 10.3 OLL (algdb OLL sheet + AUF) + 13.7 PLL(using all of the fingertricky good algs(15 move G perms, RU U perms, J perm setup N perm, T perm setup F perm etc)) +2.25 AUF = 26 Moves
COLL + 4c
Standard for this method. Avg movecount: 11.2 COLL (taken from algdb + AUF) + 6-7 4c (0.25 move for AUF before M2, 1 move for initial M2, 1 move for AUF, 4 move avg for 4c) = 17-18 STM total
Not only is the proposed COLL+4c approach more efficient than CMLL+LSE and OLL+PLL, but COLL+4c can reach high TPS too, as COLL is recognize case, and spam TPS to solve. Predict 4c and you can pauselessly transition to 4c and spam MU once more. Since, 4c is pretty algorithmic (it can have 3 move solution, or a 5 move solution), you can spam TPS here like you do for U perms. MU U perms average 7 STM and 4c also averages 7 STM. U Perm can be done around 0.6 on average, and 4c can also be done around that that.
Overall, this method has its merits and can be equally fast as CFOP. You can use your current CFOP techniques, for this method (like X-Cross, CN, etc) and 4c is consistent and pretty short on cases, which is predicted with relative ease and solved like MU U perms MU algs.
Example Solve (more in the doc)
L2 B2 L2 D2 L2 F' R' F2 D R' F2 R U' R' D' L' R
z2
F' U' R D U' M' U2 l D // Mixed XX-Cross
y' R U2 R' U2 y' R' U R // F2L 3
U2 R U' R' // F2L 4 + EO
x' R U R' D R U' R' D' x y // COLL
U2 M2 U M' U2 M' // 4c
34 Moves STM
*NMP* Method Document: http://bit.ly/idknamemethod
Thank you
Edit: Bolded out certain texts.
Edit 2: Added proper move count for OLL/PLL and COLL after counting and verifying using python program. Thanks to Tao Yu for verifying
*NMP* is a speedcubing method which uses 4c instead of PLL. You make your cross differently, solve F2L (the same way you do CFOP), COLL and 4c.
It has all the advantages of CFOP (doesn't handicap the CFOP flow), is more efficient than CFOP on average (I'm getting 45-47 stm solves), and the speedsolve can be done pauselessly since 4c is easily predicted, and during F2L, you can predict your corners case (CP). You can also achieve the same TPS that you get with CFOP, using this method and lookahead is similar to CFOP lookahead (so you won't need to re-learn lookahead)
Why is this method good?
This method provides an alternate finish to CFOP which has a lower move count, yet still allows for fast TPS and lookahead/prediction ability. Solving with PLL gives rise to bad cases like F/V/Y/N perms which you’ll never get with this approach. Plus, the worst 4c cases are 8 moves which just requires 8.08 TPS to sub 1. Since, these cases are all alg based (like U perm), you can achieve much faster TPS than 8 TPS. Let’s take a detail look.
3 Last-Step Methods
CMLL + LSE
This is standard for Roux. Avg movecount: 10 CMLL (computed from avg of all the algs in my cmll sheet + 0.25 AUF) + 13 LSE (assuming 8 EOLR/EOFB and 5 4c, essentially the most advanced LSE there is) = 23 STM total
OLL + PLL
This is standard for CFOP. Avg movecount: 10.3 OLL (algdb OLL sheet + AUF) + 13.7 PLL(using all of the fingertricky good algs(15 move G perms, RU U perms, J perm setup N perm, T perm setup F perm etc)) +2.25 AUF = 26 Moves
COLL + 4c
Standard for this method. Avg movecount: 11.2 COLL (taken from algdb + AUF) + 6-7 4c (0.25 move for AUF before M2, 1 move for initial M2, 1 move for AUF, 4 move avg for 4c) = 17-18 STM total
Not only is the proposed COLL+4c approach more efficient than CMLL+LSE and OLL+PLL, but COLL+4c can reach high TPS too, as COLL is recognize case, and spam TPS to solve. Predict 4c and you can pauselessly transition to 4c and spam MU once more. Since, 4c is pretty algorithmic (it can have 3 move solution, or a 5 move solution), you can spam TPS here like you do for U perms. MU U perms average 7 STM and 4c also averages 7 STM. U Perm can be done around 0.6 on average, and 4c can also be done around that that.
Overall, this method has its merits and can be equally fast as CFOP. You can use your current CFOP techniques, for this method (like X-Cross, CN, etc) and 4c is consistent and pretty short on cases, which is predicted with relative ease and solved like MU U perms MU algs.
Example Solve (more in the doc)
L2 B2 L2 D2 L2 F' R' F2 D R' F2 R U' R' D' L' R
z2
F' U' R D U' M' U2 l D // Mixed XX-Cross
y' R U2 R' U2 y' R' U R // F2L 3
U2 R U' R' // F2L 4 + EO
x' R U R' D R U' R' D' x y // COLL
U2 M2 U M' U2 M' // 4c
34 Moves STM
*NMP* Method Document: http://bit.ly/idknamemethod
Thank you
Edit: Bolded out certain texts.
Edit 2: Added proper move count for OLL/PLL and COLL after counting and verifying using python program. Thanks to Tao Yu for verifying
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