Milestones
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
Recognition and execution are aligned within the expected range. Improvement here comes from technique refinement rather than raw speed development.
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
~155,491
solves remaining
≈ 866 sessions at your current pace
Sub-9s
~14,166
solves to next milestone
≈ 79 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 Jun 2, 2026
Performance Trend & Forecast
AI Performance Insight
You are averaging 9.98s and have recently improved your performance by 0.35s. Your 14-day improvement rate of -0.045429 s/day confirms you are in an acceleration phase. Despite this, you are efficiency_limited, meaning your raw speed is outstripping your technical precision.
You must prioritize algorithm efficiency and recognition. Your stddev of 1.241s shows a lack of consistency that will prevent you from hitting sub-8. Reducing this variance requires optimizing your move count and transition flow.
Complete 50 slow-turn solves per session focusing on zero-pause transitions between cross and F2L.
Spend 30 minutes daily on targeted algorithm drilling for your slowest cases to reduce the 1.241s stddev.
This shifts your focus from TPS to efficiency.
Your momentum is accelerating, evidenced by a 14-day improvement rate of -0.045429 s/day that is nearly triple your 30-day rate. The data shows your current approach is working.
You are projected to need 155491 solves to reach your target. At 1350 solves per week, you risk burnout before reaching sub-8 if you do not improve your efficiency.