Ghaziabad 2020 Chart

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Game
Result
Time

Disawar

97
17-10-2026
05:15 AM
Disawar
97
05:15 AM

Gali Disawar Mix

06
16-10-2026
08:15 PM
Gali Disawar Mix
06
08:15 PM

Delhi Bazar

16
17-10-2026
03:15 PM
Delhi Bazar
16
03:15 PM

Shri Ganesh

55
17-10-2026
04:45 PM
Shri Ganesh
55
04:45 PM

Faridabad

29
16-10-2026
06:17 PM
Faridabad
29
06:17 PM

Ghaziabad

42
16-10-2026
09:20 PM
Ghaziabad
42
09:20 PM

Gali

51
16-10-2026
11:58 PM
Gali
51
11:58 PM

Milan Day

579.1
17-10-2026
03:20 - 05:00 PM
Milan Day
579.1
03:20- 05:00

Kalyan

250.7
17-10-2026
04:10 - 06:10 PM
Kalyan
250.7
04:10- 06:10

Milan Night

235.0 3.490
16-10-2026
09:05 - 11:05 PM
Milan Night
235.0 3.490
09:05- 11:05

Kalyan Night

670.3 2.200
30-09-2026
09:35 - 11:35 PM
Kalyan Night
670.3 2.200
09:35- 11:35
Weekly Ghaziabad Results for 2020
Date MON TUE WED THU FRI SAT SUN
01/01/2020
to
05/01/2020
0801490556##79
08/01/2020
to
12/01/2020
84404385989992
15/01/2020
to
19/01/2020
511125790264##
22/01/2020
to
26/01/2020
04198931530352
29/01/2020
to
02/02/2020
1575##77698171
05/02/2020
to
09/02/2020
99233521033108
12/02/2020
to
16/02/2020
39430417290501
19/02/2020
to
23/02/2020
72411816559285
26/02/2020
to
01/03/2020
049046##358717
04/03/2020
to
08/03/2020
21021836088951
11/03/2020
to
15/03/2020
68058772013262
18/03/2020
to
22/03/2020
66304780107422
25/03/2020
to
29/03/2020
711142951081##
01/04/2020
to
05/04/2020
94316256973711
08/04/2020
to
12/04/2020
95873873848077
15/04/2020
to
19/04/2020
13592998185949
22/04/2020
to
26/04/2020
55265500595075
29/04/2020
to
03/05/2020
20##6068009994
06/05/2020
to
10/05/2020
84542254142129
13/05/2020
to
17/05/2020
64008014449711
20/05/2020
to
24/05/2020
58312411802400
27/05/2020
to
31/05/2020
19138599##8590
03/06/2020
to
07/06/2020
91979023933063
10/06/2020
to
14/06/2020
20164504065225
17/06/2020
to
21/06/2020
95331338153837
24/06/2020
to
28/06/2020
201277964493##
01/07/2020
to
05/07/2020
26277457813712
08/07/2020
to
12/07/2020
74221922051815
15/07/2020
to
19/07/2020
36311956597062
22/07/2020
to
26/07/2020
67392838028717
29/07/2020
to
02/08/2020
0503##44479430
05/08/2020
to
09/08/2020
51165616144289
12/08/2020
to
16/08/2020
26473403631266
19/08/2020
to
23/08/2020
08935068082417
26/08/2020
to
30/08/2020
3094932408##41
02/09/2020
to
06/09/2020
07234458159185
09/09/2020
to
13/09/2020
33361700844542
16/09/2020
to
20/09/2020
52964294219633
23/09/2020
to
27/09/2020
71132786836972
30/09/2020
to
04/10/2020
##440063252607
07/10/2020
to
11/10/2020
80710257754135
14/10/2020
to
18/10/2020
20379272136290
21/10/2020
to
25/10/2020
74632301381209
28/10/2020
to
01/11/2020
685410##422126
04/11/2020
to
08/11/2020
41537738303045
11/11/2020
to
15/11/2020
07093131350995
18/11/2020
to
22/11/2020
36047998567470
25/11/2020
to
29/11/2020
8548874563##53
02/12/2020
to
06/12/2020
31919810815621
09/12/2020
to
13/12/2020
8959979740##81
16/12/2020
to
20/12/2020
30356610602011
23/12/2020
to
27/12/2020
80473743113691
30/12/2020
to
03/01/2021
84############

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.