Progress Dashboard

104 sessions tracked · 13054 solves · 3x3 Speed Solving

Current AO12

10.44s

Last 12 solves

Current AO100

10.96s

Last 100 solves

Best Single

1.59s

All-time best

Progress to Goal10.96s / 10.00s
95% to sub-10

Performance Over Time

Latest 20 Solves

Click a dot to see scramble

Daily AO12

Daily AO100 & Mean

Monthly Stats

Includes historical & solve-based data

MonthBest SinglePeak AO12Closing AO100
May 2026Latest2.34s8.44s10.96s
April 20261.59s4.54s11.01s
March 20262.67s4.28s14.03s
February 20269.90s13.68s15.46s
January 20263.06s11.41s16.06s
December 20253.00s8.93s17.19s
November 20254.72s8.78s25.36s
October 202511.07s12.92s
September 202519.28s24.18s

Growth Prediction

🎯 Chasing Sub-10

Stability Status
Efficiency Ceiling
gap 0.1sbench 0.81.6s14d +68.5ms/day

Consistency is strong, but improvement has stalled. Sub-optimal move efficiency or technique ceiling is likely limiting further AO100 drops.

Phase

Sub-15 → Sub-10

Regression Risk

🧭 Typical at this level

  • Strong F2L look-ahead
  • Low-rotation solving
  • Consistent Full PLL
  • Cross occasionally planned with +1

🎯 Recommended focus

  • Eliminate all visible pauses during F2L
  • Track the next pair before finishing the current insertion
  • Reduce rotation count
Sub-10s goal

~5,923

solves remaining

45 sessions at your current pace

Why ~5,923 solves?
Gap to close10.6s → 10.0s = 0.6s
Improvement rate0.23ms / solve(60d, 11,731 solves)
Base estimate0.6s ÷ 0.23ms = 2,407
Difficulty scaling×2.461.8 wall included)
Estimate~5,923 solves

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.

high confidence

This estimate is based on stable long-term trends.

Based on solve data as of May 9, 2026

Performance Trend & Forecast

AI Performance Insight

Performance Interpretation

Your AO100 is 10.55s, but your recent session average of 10.44s is associated with a regression_risk. The efficiency_bottleneck label shows that your current solve structure is limiting your potential.

Primary Focus

You must prioritize algorithm efficiency. The efficiency_limited label indicates that your move count is too high, which is the primary cause of your current regression_warning.

Practice Strategy

Perform 50 slow-turn solves per session focusing on zero-pause transitions.

This trains your lookahead to eliminate the efficiency_bottleneck by removing the pauses between algorithm sets.

Mindset

Your 14-day improvement rate of 0.068464 s/day shows you are still trending toward your goal. The data confirms you are making measurable progress.

Risk

Your solve consistency pattern is worsening. You risk a plateau if the efficiency_limited issue is not corrected before you complete the estimated 5923 solves to reach your target.