Performance Over Time
Latest 20 Solves
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Daily AO12
Daily AO100 & Mean
Monthly Stats
Includes historical & solve-based data
Growth Prediction
🎯 Chasing Sub-8.5
Consistency is strong, but improvement has stalled. Sub-optimal move efficiency or technique ceiling is likely limiting further AO100 drops.
Sub-10 → Sub-8
🧭 Typical at this level
- • Consistent Full Cross+1 inspection
- • Efficient F2L (pseudo-slotting/keyhole)
- • Strong 1-look PLL recognition
🎯 Recommended focus
- • Improve Cross+1 success rate
- • Reduce move count in F2L
- • Eliminate micro-pauses through advanced look-ahead
~5,000
solves remaining
≈ 44 sessions at your current pace
Sub-8s
~5,000
solves to next milestone
≈ 44 sessions
Your improvement rate is the biggest variable. A slower rate dramatically increases the estimate even when the gap is smaller.
You're entering advanced-level gains. Progress naturally slows.
This estimate is based on stable long-term trends.
Based on solve data as of Apr 17, 2026
Performance Trend & Forecast
AI Performance Insight
Current performance is 8.59 seconds, which is 0.33 seconds below the target time. A decreasing standard deviation of 1.015s, down from the prior measurement by 0.136s, indicates improved consistency. However, the 30-day slope of -0.009864 s/day suggests a slowing rate of improvement compared to the 14-day slope of -0.004286 s/day.
The ‘efficiency_bottleneck’ state, coupled with a ‘structural_plateau’, indicates that further time reduction requires optimizing execution rather than learning new algorithms. The current performance level is consistent with the goal tier, but the plateauing improvement rate suggests diminishing returns from current practice habits.
Implement a slow, deliberate practice routine focusing on look-ahead and fingertricks.
Perform 3 sets of 20 solves, each set targeting a specific aspect of execution, such as minimizing pauses or optimizing turning angles.
Record and analyze each set to identify and address recurring inefficiencies.
The data indicates a stable performance level with a consistent solve time. While improvement is slowing, the reduction in solve standard deviation demonstrates effective consolidation of existing skills. Continued focused practice is likely to yield further, albeit incremental, gains.
The plateau in improvement rate, despite decreasing standard deviation, suggests a potential for stagnation. Ignoring the efficiency bottleneck could limit further progress towards the sub-8 second goal.