DISAWAR - Monthly Record Chart 2016 wise

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DATE MON TUE WED THU FRI SAT SUN
01/01/16
TO
03/01/16
92773644267641
08/01/16
TO
10/01/16
58304557725125
15/01/16
TO
17/01/16
21593512701389
22/01/16
TO
24/01/16
60421143997995
29/01/16
TO
31/01/16
3390**49928942
05/02/16
TO
07/02/16
91713971259286
12/02/16
TO
14/02/16
15844133664688
19/02/16
TO
21/02/16
43064612493335
26/02/16
TO
28/02/16
203176**725817
04/03/16
TO
06/03/16
83849096814038
11/03/16
TO
13/03/16
86239449256623
18/03/16
TO
20/03/16
36656893159387
25/03/16
TO
27/03/16
094009551946**
01/04/16
TO
03/04/16
879982032238100
08/04/16
TO
10/04/16
17902290822876
15/04/16
TO
17/04/16
83470736950192
22/04/16
TO
24/04/16
64622838073504
29/04/16
TO
01/05/16
27**4821702529
06/05/16
TO
08/05/16
75471513087927
13/05/16
TO
15/05/16
98477282621521
20/05/16
TO
22/05/16
38989469259858
27/05/16
TO
29/05/16
99629476**0276
03/06/16
TO
05/06/16
07794119298771
10/06/16
TO
12/06/16
65199939550467
17/06/16
TO
19/06/16
33312423307623
24/06/16
TO
26/06/16
845731605379**
01/07/16
TO
03/07/16
69062750411562
08/07/16
TO
10/07/16
49039763242090
15/07/16
TO
17/07/16
12011917691445
22/07/16
TO
24/07/16
54803493015709
29/07/16
TO
31/07/16
8663**91869441
05/08/16
TO
07/08/16
86986352603403
12/08/16
TO
14/08/16
50913386870332
19/08/16
TO
21/08/16
76715779726763
26/08/16
TO
28/08/16
4085613358**62
02/09/16
TO
04/09/16
41627098464522
09/09/16
TO
11/09/16
93468450950895
16/09/16
TO
18/09/16
38659732193098
23/09/16
TO
25/09/16
34456232143988
30/09/16
TO
02/10/16
**585128577073
07/10/16
TO
09/10/16
05653716374608
14/10/16
TO
16/10/16
78071291319692
21/10/16
TO
23/10/16
51960269449369
28/10/16
TO
30/10/16
719465**756551
04/11/16
TO
06/11/16
35438592383507
11/11/16
TO
13/11/16
01163428083127
18/11/16
TO
20/11/16
47880258434422
25/11/16
TO
27/11/16
1454350183**44
02/12/16
TO
04/12/16
753710015165790
09/12/16
TO
11/12/16
87976672326077
16/12/16
TO
18/12/16
44274582349157
23/12/16
TO
25/12/16
16624066486197
30/12/16
TO
01/01/17
20############
📊 Weekly Disawar Results for 2016

Disawar Chart Record: Early-Morning Declarations and Statistical Archives

Disawar holds a distinct position among regional markets due to its early-morning declaration schedule. As the opening event of the daily numerical calendar for many tracking enthusiasts, Disawar results set the baseline for each day's records. The Disawar chart is a structured compilation of these daily two-digit declarations, arranged into a chronological database that stretches across months and previous operating years.

Maintaining precision in an early-morning archive requires continuous verification. Because declarations occur while many informational feeds are inactive, inaccurate initial postings are common across low-tier forums. Through Satta Matka Main, the Disawar chart is updated using dual-verification protocols, ensuring that the number appearing on your screen is accurate and free from transcription discrepancies. This reliability makes the chart an indispensable reference for mathematical hobbyists and daily record-keepers alike.

Key Features and Structural Layout of the Disawar Table

The Disawar archive is structured specifically to make historical cross-referencing intuitive and efficient:

  • Sequential Day Mapping: Every entry is linked to its exact day, date, and calendar year, preventing any confusion during leap years or 31-day transitions.

  • Single-Pair Simplicity: Since Disawar functions on a 00-to-99 index, each row displays a streamlined two-digit outcome, making large blocks of data easy to scan.

  • Cross-Market Benchmarking: Many analysts place Disawar records directly alongside late-night markets from the preceding evening (such as Gali or Ghaziabad) to study inter-market distribution patterns.

This layout allows readers to immediately assess high-frequency digits, identify prolonged absence periods for specific pairs, and track digital sum characteristics without having to calculate values manually.

Applications of Historical Disawar Records

A reliable archive serves multiple practical purposes for different types of users:

  1. Long-Term Probability Studies: Data scientists and hobbyist mathematicians frequently pull long-term Disawar datasets to test uniform pseudo-random distributions across large sample sizes (e.g., 1,000+ draws).

  2. Pattern Verification: Independent researchers use the archive to verify whether historical numbers truly support recurring cycle theories or if declarations follow pure entropy.

  3. Reference Point for Combined Metrics: Because Disawar opens the day, its value is often factored into combined composite tables used by cross-market analytical models.

Having access to clean, tabular data ensures these evaluations rest on verified historical facts rather than hearsay.