"Ganpati Special" Chart Performance Analysis
Playlist by Radio City
Executive Summary
AI-generated performance analysis
Average
This playlist achieves a C+ (Average) chart performance rating, currently ranked #24.
"Ganpati Special" by Radio City demonstrates moderate chart performance on Apple Music.
The playlist has spent 11 days on the Top 100 chart.
- Peak: #24
- Current: #24
- 11 days on chart
- Curator: Radio City
Performance Factors Analysis
Breakdown of key metrics driving performance
Chart Performance
Peak position achieved on the charts
- Peak position: #24
- Peak date: Sep 14, 2026
- Currently ranked #24
Chart Longevity
Total duration on the charts
- 37% of average chart run
- 11 total days on chart
- 11 max consecutive days
Chart Stability
Consistency of chart position
- Very stable chart performance
- Stability index: 98/100
Current Momentum
Recent chart movement trend
- Stable chart position
- Consistent performance
- Today's change: +2
Moderate performance. Some factors could be stronger.
Benchmark Comparison
Performance compared to Apple Music Playlist Average average
1.5x higher than avg
63% below avg
2.0x higher than avg
Above average performance compared to Apple Music Playlist Average content.
Ranking History & Insights
Performance over time
Currently ranked #24 in the Top 50. This is the peak ranking. Ranking is stable.
Peak reached on Sep 14, 2026
Current Streak
11d
Best: 11d
Avg Position
#25
Last 30 days
7-Day Trend
—
Stability
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Apple Music Reference
Source content being analyzed
Ganpati Special
Radio City
in India
points
Ranked #172 all-time
About Rankings
Rankings are based on Apple Music Top 100 charts in India. Updated daily.
About This Analytics Report
This report is generated by Top1Trend's analytics engine, which tracks Apple Music trending data across 30+ regions since 2024. All metrics are derived from official chart positions via the official Apple Music API.
Top1Trend is an independent analytics service and is not affiliated with, endorsed by, or sponsored by Apple Music. All trademarks belong to their respective owners. Data accuracy depends on platform API availability and may have slight delays from real-time values.