Ghaziabad 2017 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 2017
Date MON TUE WED THU FRI SAT SUN
01/01/2017
to
08/01/2017		59539139528515
08/01/2017
to
15/01/2017		72732313437142
15/01/2017
to
22/01/2017		37103185039032
22/01/2017
to
29/01/2017		15531348400278
29/01/2017
to
05/02/2017		7832**4879034
05/02/2017
to
12/02/2017		79501811981194
12/02/2017
to
19/02/2017		91709704294797
19/02/2017
to
26/02/2017		26021662814150
26/02/2017
to
05/03/2017		1615**70965026
05/03/2017
to
12/03/2017		90590308776524
12/03/2017
to
19/03/2017		08663699384806
19/03/2017
to
26/03/2017		48481824271214
26/03/2017
to
02/04/2017		2168304729**61
02/04/2017
to
09/04/2017		03261097453798
09/04/2017
to
16/04/2017		22625201915375
16/04/2017
to
23/04/2017		85446790072764
23/04/2017
to
30/04/2017		11918030419415
30/04/2017
to
07/05/2017		**681604931990
07/05/2017
to
14/05/2017		15656358736871
14/05/2017
to
21/05/2017		36138346677382
21/05/2017
to
28/05/2017		13704306127705
28/05/2017
to
04/06/2017		515976**301188
04/06/2017
to
11/06/2017		20878311718068
11/06/2017
to
18/06/2017		21026667042838
18/06/2017
to
25/06/2017		13558201853728
25/06/2017
to
02/07/2017		2770012405**43
02/07/2017
to
09/07/2017		30368558920489
09/07/2017
to
16/07/2017		593410027819351
16/07/2017
to
23/07/2017		91217481757262
23/07/2017
to
30/07/2017		02324661425052
30/07/2017
to
06/08/2017		28**6306101937
06/08/2017
to
13/08/2017		03629719846893
13/08/2017
to
20/08/2017		76932034089513
20/08/2017
to
27/08/2017		81064107211486
27/08/2017
to
03/09/2017		61089380**8744
03/09/2017
to
10/09/2017		27448486129677
10/09/2017
to
17/09/2017		16902390865067
17/09/2017
to
24/09/2017		25907633446361
24/09/2017
to
01/10/2017		405390483326**
01/10/2017
to
08/10/2017		71107175924676
08/10/2017
to
15/10/2017		58953329667173
15/10/2017
to
22/10/2017		681006433539325
22/10/2017
to
29/10/2017		301008015302290
29/10/2017
to
05/11/2017		0798**78492307
05/11/2017
to
12/11/2017		75221251064229
12/11/2017
to
19/11/2017		18424239352139
19/11/2017
to
26/11/2017		32183801175199
26/11/2017
to
03/12/2017		93150349**5906
03/12/2017
to
10/12/2017		36356751872683
10/12/2017
to
17/12/2017		91787231852596
17/12/2017
to
24/12/2017		05891487788402
24/12/2017
to
31/12/2017		96290794312492
31/12/2017
to
07/01/2018		**############

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.