Ghaziabad Chart

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Game
Result
Time

Disawar

73
22-09-2026
05:15 AM
Disawar
73
05:15 AM

Gali Disawar Mix

45
22-09-2026
08:15 PM
Gali Disawar Mix
45
08:15 PM

Delhi Bazar

03
22-09-2026
03:15 PM
Delhi Bazar
03
03:15 PM

Shri Ganesh

98
22-09-2026
04:45 PM
Shri Ganesh
98
04:45 PM

Faridabad

42
22-09-2026
06:17 PM
Faridabad
42
06:17 PM

Ghaziabad

70
21-09-2026
09:20 PM
Ghaziabad
70
09:20 PM

Gali

32
21-09-2026
11:58 PM
Gali
32
11:58 PM

Milan Day

468.8 6.349
22-09-2026
03:20 - 05:00 PM
Milan Day
468.8 6.349
03:20- 05:00

Kalyan

169.6 5.140
22-09-2026
04:10 - 06:10 PM
Kalyan
169.6 5.140
04:10- 06:10

Milan Night

190.0 6.178
21-09-2026
09:05 - 11:05 PM
Milan Night
190.0 6.178
09:05- 11:05

Kalyan Night

225.9 4.167
21-09-2026
09:35 - 11:35 PM
Kalyan Night
225.9 4.167
09:35- 11:35
Weekly Ghaziabad Results for
Date MON TUE WED THU FRI SAT SUN
23/09/2026
to
27/09/2026
##############

Ghaziabad Chart: Prime Evening Historical Log, Daily Outcome Tables & Trend Analysis

The Ghaziabad Chart forms the core of mid-evening record keeping. Positioned between the opening evening entries and midnight regional logs, the Ghaziabad database offers a critical benchmark for evaluating sequential patterns. This page provides a verified, mobile-optimized repository of daily records, monthly registers, and long-term trend data for data analysts and statistical hobbyists.

Because mid-evening figures reflect shifts following early-evening timelines, examining long-term Ghaziabad records allows observers to study frequency variance across continuous operational cycles. To compare Ghaziabad entries with earlier evening or late-night figures, visit the Gali Disawar Mix homepage to review integrated tabular summaries across all daily categories.

Understanding the Ghaziabad Ledger Format

  • Chronological Date Logging: Continuous date sequencing ensures historical audits remain seamless across all 12 calendar months.
  • Consolidated Outcome Entry: Clear two-digit standardized numerical entries that facilitate automated sorting and manual auditing.
  • Weekly Frequency Categorization: Identifies persistent digit runs and common clusters across specific operational weekdays.

Analytical Methods Applied to Ghaziabad Data

  • Quadrant Division: Splitting values into four quartiles (01–25, 26–50, 51–75, 76–00) to observe whether numbers balance evenly across 60-day cycles.
  • Tens-Place Repetition Analysis: Tracking how many operational days elapse before the tens-place digit repeats itself.
  • Inter-Market Correlation: Reviewing historical data to evaluate whether preceding evening entries show statistical alignment with Ghaziabad records.