One of the most common and important questions people ask when they become interested in learning ZBLL is “How do/should I recognize ZBLL?” Eventually I decided to create an all-in-one resource to link people that compares the 5 main systems people use to recognize ZBLL. The 5 main recognition systems are Blocks, Baum-Harris(BH), No-CP(NCP), Tran Style(V1 and V2), and Twisty PLL(2 types). This guide will explain how each system works, and list the pros and cons of each one so that you can make an informed decision about which recognition system you want to use. Be sure to read about each one in order, as later explanations may reference info introduced earlier in the guide!
Also, this guide will explain how the recognition systems work as well as show examples of the systems being applied to actual ZBLL cases. It will use the same few ZBLL cases for each system so you can see and compare how each one feels in practice. Ultimately, the recognition system you choose won’t matter much in the long run as you will eventually reach a point of simply seeing a case and recognizing it without thinking from seeing it enough over time.
Blocks or block-based recognition is one of the most common ways people recognize ZBLL, especially if they start learning without any prior knowledge of recognition systems as it is the most intuitive approach. Many solvers recognize PLL from 2 sides using blocks, so using blocks for ZBLL recoginition is a natural extension of this. As the name suggests, with block-based recognition solvers simply recognize any blocks or recognizable/distinguishing patterns a ZBLL case may or may not have.
First, let’s take a look at an easy case to recognize with blocks:
There are 2 nice 2x1 blocks of opposite colors, which can make recognizing this case relatively easy.
Conversely, let’s look at a difficult case to recognize with blocks:
There aren’t very many blocks to recognize in this case to the untrained eye aside from an opposite color bar.
Here are the pros and cons of using block-based recognition:
Pros:
+Block-based recognition can be incredibly fast when you have large or easy to identify blocks or patterns
+Easy and intuitive
Cons:
-Many cases do not have nice blocks or patterns, which makes recognition a lot harder for some cases than others
-Can require looking at 3 or even 4 sides to identify the case
-Not a consistent/systematic recognition system
Within the ZZ community, Baums-Harris, or BH, has become regarded as the optimal method to recognize ZBLL. The reason for this is that BH is a systematic way to recognize any case from any angle, and can be applied to other algsets such as PLL, TTLL, and CFOP 1LLL (with the added consideration of EO) just to name a few.
As stated earlier, BH let’s you recognize any case from any angle in a systematic way. However, this requires you to learn a lot of information about a case. The way most people will get started is by using BH recognition from only one angle per CO case and then learn other angles later.
The steps to recogize a case are as follows:
That is all the information necessary to recognize a case. Now let’s look at the example cases from earlier.
Let’s choose to recognize this case from this angle for simplicity.
We see the system break down into recognizing:
Which identifies the unique ZBLL case shown.
In total, there are 36 BH patterns, 24 of which are derived from a base set of 12.
If you know 2-Side PLL recognition for EPLL, these patterns will be very familiar.
The other 24 are from twisting the corner (anti)clockwise, as shown in the example below:
Here are the pros and cons of using BH recognition:
Pros:
+BH is completely systematic and works the exact same way for any case
+Consistency of recognition across sets
+Recognition is fast as you always look at the same 3 pieces to identify the BH pattern
Cons:
-Relatively high barrier to use as one has to learn to recognize COLL and the BH patterns
-More complicated/less intuitive and takes time to get used to
No-CP, or NCP, is a relatively unique system to recognize ZBLL as it does not use CP recognition for any case. This system was originally created as an alternative system to BH to mainly use for Sune and Antisune since many cubers find S/AS CP recog more difficult than for other sets. The system does work for any set of course.
This system is very familiar recognition wise to BH.
The steps to recognize a case are as follows:
Now let’s look at that same U case ZBLL from earlier and see how this applies to a real case:
From the perspective of the green face being the F face, the BH pattern around the UFL corner is a nice solved 2x2x1 block.
Now checking the pattern around the UFR corner, the BH pattern is a vertical checker pattern that touches an opposite color.
That is all the information needed to recognize any ZBLL case using this system.
This system can be considered “double BH” or “optimal blocks” due to the fact 2 BH patterns are recognized.
Here are the pros and cons of using NCP recognition:
Pros:
+The only thing one needs to be learned are the BH patterns
+Even greater consistency than BH since the same 5 pieces are used to recognize any case
+Also a systematic recognition method
+CP information can be picked up over time
Cons:
-Requires looking at 3 sides instead of 2 like BH
-Usefulness decreases as CP recognition becomes easier. It is especially weak for H and Pi since CP is recognized only from the U layer
There are 2 versions of Tran-Style recognition, which will be referred to as V1 and V2 respectively. V1 is the original system proposed by Chris Tran and V2 is a modification that improves the system. This guide will explain both versions and show how V2 is a direct upgrade over V1. V1 and V2 share the same first step then differ afterwards.
The steps to recognize a case are as follows:
This system is can be confusing in written form, particularly V2, so let’s see both systems applied to the U ZBLL case from earlier. Because of the nature of this system, additional images will be shown portraying the same case.
Just like BH we start with identifying the COLL case:
Now, this is where the new images begin, starting with this top view showing all 4 sides.
Using the V1 system, the UFR corner is used as a reference and then the edges that belong around it must be located to recognize the case. In this image the UFR corner has green on F and orange on R. Looking at the UF, UR, and UL edges allows a solver to deduce the edge in the back. Here the green edge is in UR and the orange edge is in UL. This has now identified the case. An image showing the edge positions is shown below.
Using the V2 system, the next step after COLL recognition is to look at the reference sticker on the U layer. Each OCLL will have a U layer sticker used as a reference. The reference sticker for U is marked as shown below:
In this case, the reference sticker is red, so the red and orange edges are located instead, which identifies the case. This is shown in the next image.
The 12 possible edge location patterns are shown below:
The reason V2 is an improvement is because the reference sticker is only on the U layer. If you use V1 recognition, you first have to AUF to the angle you chose to recognize ZBLL from to then use the stickers on the UFR corner as the reference. By using a sticker on the U layer as the reference, the reference is visible from any angle which allows a solver to then start looking for the corresponding edges immediately instead of having to AUF first to know what edges to find. Because of this, the pros and cons will only cover V2 as it should be used over the V1 system.
Here are the pros and cons of Tran-Style V2 recognition:
Pros:
+Post-COLL recognition is simple, as only 2 edges need to be located
+Potential for EP case prediction from last slot (more details momentarily)
+Any angle recognition should be easier to learn than for other systems
+Systematic
Cons:
-Not very intuitive system compared to what one may be familiar with for PLL
-Not consistent as 3 sides may be required to identify the positions of the edges (more details momentarily)
-Also requires COLL recognition to be learned
At a glance, TSV2 may seem like a worse version of BH. However, this recognition system has a lot of potential due to last slot look ahead. If a solver is able to track what edge is going to end up in either UL or UB, then the ZBLL case could be recognized completely AUFless, which has attracted interest. It is possible the system may develop into a V3 revision over time.
There are two styles of recognition that fall under the term Twisty PLL recognition. Each one will be explained and demonstrated, just like the previous systems. The main idea is using PLL recognition to recognize ZBLL. The two systems do not have conventionally agreed upon names. For the purpose of this guide, they will be refered to as pure-twist recognition and CP-relative recognition.
Pure-twist is exactly as it sounds. A solver would mentally twist the corners to recognize a given ZBLL case using 2-side PLL recognition.
Referring to the same U case from the previous examples:
For this case from this angle, the recognition is relatively easy. Just a mental swap of the red sticker on the U layer allows the solver to recognize the case as a V perm, as shown below.
The problem with this style of recognition becomes apparent when twisted corners are present. This is especially problematic for H, Pi, and to a lesser degree Sune and Antisune cases.
Returning to the H case from the blocks section,
it becomes a lot more complicated to mentally twist the 3 corners to recognize this case to recognize this as an A perm. For the UBR corner, a solver would need to tilt the cube or AUF to see the back sticker as well, which somewhat defeats the point of using 2-side PLL recognition to recognize ZBLL since looking at more than 2 side faces can be required.
Here are the pros and cons of Pure-Twist Recognition:
Pros:
+U and L set can be recognized identically to 2-side PLL recognition from 1 angle
+CP information can be used to deduce non-visible stickers to allow more angle coverage for sets
Cons:
-Most angles of a given ZBLL case will require tilting the cube to see a non-visible sticker, an AUF to see a non-visible sticker, or use CP information to deduce the non-visible sticker
-Very inconsistent style of recognition
CP-Relative recognition is very similar to BH recognition. In order to use this system, a solver first has to learn to do 2-side PLL recognition using BH and recoginize where headlights are for adjacent-swap CP PLL. Now a solve will recognize ZBLL using the same system as BH, with 2 modifications. The solver mentally twists the UFR corner, and the solver recognizes where headlights are (if any) relative to the BH block around UFR.
Returning to the H case that was a problem for Pure-Twist recognition,
Mentally twisting the UFR corner produces the following pattern:
Recognizing the COLL informs the solver that the headlights are on the right:
This is enough information to allow the solver to identify the case as an Ab perm with the headlights on the right.
Here are the pros and cons of CP-Relative Recognition:
Pros:
+Can make recognition from any angle easier to learn
+Similar to BH, a very good recognition system
+Systematic
Cons:
-Requires a solver to learn 2-side PLL recognition using BH first
-Requires a solver to associate headlight positions to COLL recognition
I hope this relatively short guide was helpful for anyone interested in ZBLL about the different ways to recognize it. Hopefully it made it easier for you to decide what system you want to use to recognize ZBLL. As stated earlier, it shouldn’t matter too much in the long-run what system you use as you’ll see cases enough over time to just see it and know what case it is. Get out there and start learning!