CFOP stage percentages by skill level
Smart-cube stage timestamps turn a general training rule into an observed benchmark for distinct skill brackets.
Loading sample…Living annual report · 2026
State of Speedcubing 2026
Smart-cube practice, algorithm training and online competition—published only when each evidence cell is large enough to support a real statement.
Publication dashboard
What the 2026 sample can support today
Cards marked “collecting” have a complete method and permanent URL but no public estimate yet. Published cards show their real sample and date range.
Typical TPS by solve-time bracket
Move-aware solves show how turning rate and move count vary across real solve-time bands.
Loading sample…Most commonly failed OLL and PLL cases
Trainer outcomes reveal which cases create persistent recognition or execution mistakes instead of relying on anecdotal difficulty lists.
Loading sample…Recognition time versus execution time
Separated trainer phases reveal whether identifying a case or turning it is the larger part of the delay.
Loading sample…Average pauses between CFOP stages
Move timestamps around detected stage boundaries quantify the transitions that a stopwatch total hides.
Loading sample…Most practised speedcubing algorithms
Aggregate attempt volume shows which cases attract the most deliberate work across the training community.
Loading sample…Smart-cube connection success by browser and device
Coarse anonymous outcomes reveal where browser-based Bluetooth succeeds and where setup still creates friction.
Loading sample…Most common Bluetooth smart-cube connection errors
Validated error buckets show whether unavailable APIs, permissions, GATT state or initialization failures dominate.
Loading sample…Improvement after 100, 500 and 1,000 solves
Milestone cohorts connect sustained practice volume to the change in a player’s own rolling performance.
Loading sample…Manual versus smart-cube timing
Immutable timer-source labels make it possible to describe two timing populations without mixing them into one average.
Loading sample…Average daily speedcubing practice volume
User-day totals describe the practice dose people actually record when they open a session.
Loading sample…Online tournament participation and completion rates
Entry and submission records reveal which event windows turn interest into a completed competitive average.
Loading sample…Practice
How solves are structured
CFOP stage shares, TPS and transition pauses use move-aware smart-cube records. Manual solves are analyzed only where the timer source itself is the research question.
Learning
How algorithms are trained
Attempt volume, failure outcomes and recognition/execution components show the cases people choose and the phase that consumes time.
Reliability
How browser Bluetooth behaves
Coarse anonymous outcomes track connection success, failure categories and later disconnections without retaining personal or hardware identifiers.
Competition
How entries become completions
Independent SupaKewber tournaments provide participation and completion evidence. Official competition performance stays in the WCA-labeled section.
Citation rule
Quote the number, sample, period and source together.
The downloadable JSON keeps all four attached. This prevents a benchmark from turning into context-free speedcubing folklore.