Kalyan Historical Analysis
Explore Kalyan historical results through organized data, frequency observations, result distributions and period comparisons, with a clear explanation of what historical analysis can and cannot show.
Reviewed & Maintained
By FixResult Editorial Team
Kalyan Historical Results Overview
Kalyan historical analysis uses previously recorded Kalyan results to examine how the market's documented results are distributed across dates and historical periods. The analysis on this page is based on the site's historical Kalyan archive rather than on isolated examples or manually selected results.
The current archive contains 1,199 recorded Kalyan sessions covering 31 October 2022 through 1 September 2026. Each available record is organized around its recorded date and the corresponding Open, Jodi, and Close values. This provides a consistent historical dataset that can be examined both as individual records and as grouped periods.
Looking at the records as a complete dataset makes it possible to study more than the result recorded on a particular day. The historical data can be used to measure how frequently individual Open or Close digits occurred, examine recorded Jodi combinations, review how results were distributed, and compare measurements between defined periods.
A useful distinction is maintained throughout this page: a historical record is the documented result itself, while a historical observation is a measurement or comparison derived from multiple records. For example, counting how many times a particular digit appears in the archive is a frequency observation; it does not change or reinterpret the underlying historical records.
The analysis also depends on the scope of the available archive. Date ranges, record counts, and any limitations in the underlying data need to remain clear when a calculation or comparison is presented. This prevents a result from being taken out of context or treated as representative of periods that were not included in the calculation.
The purpose of this page is therefore to make the historical Kalyan data easier to examine and understand through documented records and calculations. Frequency, distribution, and period comparisons describe the historical dataset available for analysis; they are not presented as predictions or guarantees of future results.
Kalyan Historical Result Data
The Kalyan historical archive currently contains 1,199 recorded Kalyan sessions, covering the period from 31 October 2022 through 1 September 2026. The records are organized chronologically and include the recorded Open, Jodi, and Close values for each available session.
The archive is presented as a historical dataset rather than as a prediction tool. Each row represents a previously recorded Kalyan result, allowing individual sessions to be reviewed against their recorded date and result components.
For practical analysis, the archive can be viewed in different ways. The latest records provide a view of recent historical activity, while chronological ordering allows older sessions to be examined in sequence. The available search and display controls also make it possible to locate records by relevant result information without treating individual entries as isolated examples.
| Date | Open | Jodi | Close |
|---|---|---|---|
| ⏳ Fetching Kalyan historical records... | |||
Archive Status: Synchronizing available Kalyan historical records...
The historical dataset is useful because the same structure is maintained across the available records: date → Open → Jodi → Close. This consistent format makes it possible to perform calculations across multiple sessions, including digit-frequency measurements, Jodi counts, result distributions, and comparisons between selected historical periods.
Not every analytical calculation necessarily uses all 1,199 sessions. Frequency and comparison measurements depend on whether a record contains the required usable value for that particular calculation. Therefore, record coverage should always be considered alongside any statistic presented on this page.
The purpose of maintaining the historical dataset in this format is to make previously recorded Kalyan results easier to examine systematically. The archive provides the underlying records, while the sections that follow use those records to measure frequencies, distributions, and differences across historical periods.
Kalyan Results by Date and Period
Historical Kalyan results are most useful when they are examined in relation to their recorded dates rather than as an undifferentiated list. The archive provides a chronological sequence of sessions, making it possible to review individual results and observe how the recorded data changes across different parts of the historical record.
Kalyan Results by Date
A date-based view connects each recorded Kalyan session with its Open, Jodi, and Close values. This allows a specific historical result to be checked directly against the date on which it was recorded.
For example, the current archive begins its displayed recent records with 1 September 2026 — Open 190, Jodi 05, Close 249, followed by 31 August 2026 — Open 600, Jodi 69, Close 360. These entries are historical observations tied to their respective dates; they are not treated as indicators of what a later result should be.
Reviewing results in chronological order is also important when calculating frequencies or comparing periods. It preserves the sequence of the underlying records and reduces the risk of selecting individual results simply because they appear interesting.
Kalyan Results Across Historical Periods
Period-based analysis groups multiple dated records into a defined portion of the archive and then compares measurements calculated from those records. This is different from looking at a single day's result because the measurement represents a collection of sessions.
The current page includes a recent-versus-prior period comparison using the historical archive. The comparison records 583 Open values in the recent period versus 585 in the prior period, while Close values total 582 versus 585. It also reports 98 distinct Jodis versus 99 for the two comparison periods.
These figures demonstrate why the period definition matters. A comparison should always be interpreted within the specific records included in each period, rather than being generalized to the entire history. Differences between two historical periods describe differences in those datasets; they do not establish a permanent characteristic of the Kalyan market.
For this reason, the analysis on this page treats dates as the foundation of the dataset and periods as defined groups of those dated records. Frequency and distribution measurements can then be compared against the underlying record coverage instead of being presented without context.
Kalyan Open, Jodi and Close Historical Data
The Kalyan archive records each available session through three primary result components: Open, Jodi, and Close. Examining these components separately allows the historical dataset to be measured at different levels instead of treating every result as a single combined value.
Kalyan Open Historical Data
Open values provide one part of the historical record for each available session. Across multiple dates, these values can be grouped by their final digit to calculate how often each Open digit appears in the archive.
In the current default frequency dataset, observations show variation between the recorded Open digits. Digits 0, 3, and 9 each account for 127 observations (10.88%), while digit 8 accounts for 102 observations (8.74%). These figures describe the distribution within the records included in the current calculation; they should not be interpreted as evidence that one digit is more likely to occur in a future result.
Kalyan Jodi Historical Data
Jodi values can be examined as two-digit historical combinations. Instead of reducing the result to a single digit, the archive preserves the recorded combination, allowing individual Jodis to be counted across the available historical data.
In the default Jodi frequency calculation, 51 appears 21 times (1.80%), followed by 72 with 19 occurrences (1.63%). Jodis 33, 95, and 00 each appear 18 times (1.54%). These are historical counts from the available calculation, not rankings of future probability.
Kalyan Close Historical Data
Close values form the other principal digit-based component of the historical result. Like Open values, they can be grouped by their final digit to measure their frequency across the available records.
In the default Close frequency calculation, digit 4 records 134 observations (11.48%) as the highest count in that table, while digit 9 has 100 observations (8.57%). The difference represents how those digits are distributed within the historical records used for the calculation, rather than a prediction about subsequent results.
Using the Three Components Together
Keeping Open, Jodi, and Close separate preserves more information than combining them into a single historical figure. Open and Close can be examined through digit frequencies, while Jodi can be examined as a two-digit combination.
This separation also makes comparisons easier to interpret. A frequency observation for an Open digit answers a different question from a Jodi frequency count, and neither should be treated as interchangeable with a Close-digit measurement.
The historical value of the dataset therefore comes from examining these components consistently across dated records. The measurements describe what is present in the recorded archive and should remain tied to the date range and usable records included in each calculation.
Kalyan Historical Frequency Analysis
Frequency analysis measures how often a particular digit or Jodi appears within the historical Kalyan records included in a calculation. It converts the underlying result records into count-based observations, making it possible to compare the distribution of recorded values without changing the original historical results.
Open Digit Frequency
In the current default Open frequency calculation, the records show:
| Open Digit | Occurrences | Share of Open Records |
|---|---|---|
| 0 | 127 | 10.88% |
| 1 | 113 | 9.68% |
| 2 | 111 | 9.51% |
| 3 | 127 | 10.88% |
| 4 | 109 | 9.34% |
| 5 | 125 | 10.71% |
| 6 | 109 | 9.34% |
| 7 | 117 | 10.03% |
| 8 | 102 | 8.74% |
| 9 | 127 | 10.88% |
Within this default frequency calculation, digits 0, 3, and 9 have the highest recorded counts at 127 each, while digit 8 has the lowest at 102. The percentages show the same distribution from a proportional perspective.
Close Digit Frequency
In the default Close frequency calculation, the records show:
| Close Digit | Occurrences | Share of Close Records |
|---|---|---|
| 0 | 113 | 9.68% |
| 1 | 126 | 10.80% |
| 2 | 128 | 10.97% |
| 3 | 115 | 9.85% |
| 4 | 134 | 11.48% |
| 5 | 118 | 10.11% |
| 6 | 113 | 9.68% |
| 7 | 107 | 9.17% |
| 8 | 113 | 9.68% |
| 9 | 100 | 8.57% |
Digit 4 has the highest recorded Close frequency in the default calculation with 134 occurrences, while digit 9 has the lowest with 100. The difference between the highest and lowest displayed percentages is 2.91 percentage points.
Jodi Frequency
Jodi frequency is measured differently because the historical value is a two-digit combination rather than a single digit. In the default calculation, 51 is the most frequently recorded Jodi among the displayed top observations, with 21 occurrences (1.80%).
The next highest displayed count is 72 with 19 occurrences (1.63%). Jodis 33, 95, and 00 each appear 18 times (1.54%), while 14, 58, 96, and 06 each appear 17 times (1.46%).
| Recorded Jodi | Occurrences | Share of Jodi Archive |
|---|---|---|
| 51 | 21 | 1.80% |
| 72 | 19 | 1.63% |
| 33 | 18 | 1.54% |
| 95 | 18 | 1.54% |
| 00 | 18 | 1.54% |
| 14 | 17 | 1.46% |
| 58 | 17 | 1.46% |
| 96 | 17 | 1.46% |
| 06 | 17 | 1.46% |
These figures should be read as frequency counts within the historical dataset, not as evidence that a frequently recorded Jodi or digit has a greater chance of appearing in a future result.
Interpreting Historical Frequency
Frequency analysis is useful for describing the composition of the recorded archive. It can show which digits or Jodi combinations occurred more or less often within the measured dataset and can provide a consistent basis for comparing historical observations.
The figures also demonstrate why frequency should be reported together with its calculation scope. A frequency percentage describes the records included in that particular calculation; it does not establish a universal frequency for all Kalyan results or convert historical observations into future predictions.
Accordingly, the frequency tables on this page are presented as descriptive historical statistics. Their purpose is to measure the available records accurately and make differences in the dataset visible, while keeping those observations separate from prediction or probability claims.
Kalyan Historical Result Distribution
Historical result distribution looks at how the recorded Kalyan values are spread across the available digits and Jodi combinations. While frequency analysis counts individual occurrences, distribution analysis considers the difference between higher- and lower-frequency observations and whether the recorded values are concentrated within a narrow range.
Open Result Distribution
In the default Open frequency dataset, observations show a relatively narrow spread across the ten digits. The highest recorded frequencies are 0, 3, and 9, with 127 occurrences each, while digit 8 has 102 occurrences.
The difference between the highest and lowest Open frequencies is therefore 25 observations. In percentage terms, the displayed range extends from 8.74% to 10.88%, a difference of 2.14 percentage points.
This shows that the measured Open-digit distribution is not concentrated in a single digit. The individual counts vary, but the displayed frequencies remain within a comparatively limited percentage range.
Close Result Distribution
In the default Close frequency dataset, observations show a somewhat wider spread than the Open table. Digit 4 records the highest frequency with 134 observations (11.48%), while digit 9 records the lowest with 100 observations (8.57%).
That creates a difference of 34 observations, or 2.91 percentage points, between the highest and lowest displayed Close frequencies.
The comparison is useful because it shows that Open and Close distributions do not have to follow the same historical pattern. Each component should therefore be measured separately before any comparison is made.
Jodi Result Distribution
Jodi distribution is more granular because each observation is represented by a two-digit combination. In the default frequency calculation, 51 is at the top with 21 occurrences (1.80%), followed by 72 with 19 occurrences (1.63%).
The leading Jodi therefore represents only a small proportion of the observations shown in the frequency analysis. Several other Jodis are close behind in recorded frequency, including 33, 95, 00, 14, 58, 96, and 06.
This is an important distinction from single-digit analysis: a Jodi distribution contains many possible two-digit combinations, so individual combinations can represent a much smaller share of the historical dataset.
Reading Distribution Differences
Distribution differences are descriptive measurements of the historical archive. A higher recorded frequency means that the corresponding value occurred more often within the measured records; it does not establish that the value is inherently stronger, due, or more likely to occur later.
The distribution should also be considered alongside the coverage of the calculation. The current archive contains 1,199 recorded sessions, while the Open and Close frequency tables contain 1,167 observations. The distribution figures therefore describe the records included in those frequency calculations rather than automatically representing every archived session.
For historical analysis, the useful question is not which value should occur next, but how the recorded values were distributed within the defined dataset and how that distribution changes when different historical periods or result components are examined.
Comparing Kalyan Historical Periods
Comparing historical periods helps identify whether the distribution of recorded Kalyan results changes between two defined groups of sessions. Instead of examining individual results, the comparison measures the same variables across separate portions of the historical dataset.
In the default Recent Period versus Prior Period comparison, the available measurements show 583 Open records in the Recent Period compared with 585 in the Prior Period, a difference of 2 records. For Close values, the comparison contains 582 records versus 585, a difference of 3 records.
The comparison also measures the number of distinct Jodis recorded in each period. The Recent Period contains 98 distinct Jodis, compared with 99 distinct Jodis in the Prior Period. This indicates that the number of different Jodi combinations represented in the two measured groups is very similar.
| Measure | Recent Period | Prior Period | Difference |
|---|---|---|---|
| Open records | 583 | 585 | -2 |
| Close records | 582 | 585 | -3 |
| Distinct Jodis | 98 | 99 | -1 |
Reading the Period Comparison
The small difference in record coverage is important when interpreting the measurements. Open and Close calculations do not contain exactly the same number of records in either period, so the figures should be compared with their respective record counts rather than treated as perfectly identical samples.
Likewise, the difference between 98 and 99 distinct Jodis describes the number of different combinations recorded within the respective comparison groups. It does not indicate that one period has a stronger or more favorable Jodi pattern.
A period comparison becomes more meaningful when the same measurement is applied consistently to both groups. For example, Open-digit frequency can be calculated separately for each period, as can Close-digit frequency and Jodi frequency. The resulting differences can then be described as changes within the historical dataset.
What Period Differences Mean
A difference between two historical periods is an observation about those periods only. It can show that the composition of the recorded data was different, but it cannot establish why the difference occurred or whether the same pattern will appear in another period.
The purpose of period comparison is therefore to provide a controlled way to examine historical change. The comparison should remain connected to the records, measurement type, and period definition used to produce it.
Where the underlying dataset changes as additional historical records become available, period-based statistics may also change. Historical analysis should consequently be treated as a measurement of the archive at a defined point in time rather than as a permanent characteristic of Kalyan results.
What Kalyan Historical Data Can and Cannot Show
Historical Kalyan data can show how previously recorded results were distributed within a defined dataset. It can be used to count digit frequencies, measure Jodi occurrences, compare Open and Close distributions, and examine differences between selected historical periods.
These measurements are useful because they are based on recorded results rather than isolated examples. They provide a consistent way to describe what occurred within the available archive and to identify differences between groups of historical records.
However, historical frequency does not establish future probability. If a digit or Jodi occurred more frequently within the measured archive, that observation does not by itself demonstrate that the same value will occur again or that another value is less likely to occur.
Historical data also cannot establish a guaranteed sequence between past and future results. A previous result remains a historical record even when a later result differs from a pattern observed in the archive.
Limits of the Available Dataset
The scope of the dataset also affects every analysis. The current archive contains 1,199 recorded Kalyan sessions, while the Open and Close frequency tables currently contain 1,167 observations. Therefore, a frequency percentage should be understood as a measurement of the records included in that calculation, not automatically as a statistic covering every archived session.
Period comparisons have their own coverage limits. The current Recent Period and Prior Period measurements contain slightly different numbers of Open and Close records, so differences should be interpreted together with the record counts used to calculate them.
Historical Observation vs Prediction
There is a clear distinction between describing historical data and predicting a future result.
A statement such as “digit 4 occurred 134 times in the current Close-frequency calculation” is a historical observation supported by the recorded dataset. A statement such as “digit 4 is more likely to occur next” would be a prediction that is not established by that frequency count alone.
This page therefore uses historical statistics to describe the archive, not to provide guaranteed outcomes. Frequency, distribution, and period comparisons should be interpreted as measurements of previously recorded data within their stated scope.
The value of historical analysis is consequently in understanding and documenting the available records accurately. It should not be confused with a method for determining future Kalyan results.
Kalyan Historical Analysis Methodology
Kalyan historical analysis begins with the recorded result archive and then applies the same measurement method to the relevant records. The purpose is to keep each observation connected to the underlying historical data rather than relying on selected examples or subjective pattern descriptions.
1. Define the Historical Dataset
The first step is to establish the available archive and its date coverage. The current Kalyan dataset contains 1,199 recorded sessions from 31 October 2022 through 1 September 2026. This provides the base collection from which the page's historical measurements are derived.
2. Separate Result Components
Each usable historical record is examined through its recorded Open, Jodi, and Close values. Keeping these components separate allows different types of measurements to be performed without combining unrelated values.
Open and Close can be measured by their individual digits, while Jodi can be counted as a complete two-digit combination.
3. Calculate Frequencies
Frequency analysis counts how many times each relevant digit or Jodi appears within the records included in the calculation.
The resulting count can then be expressed as a percentage of the records used for that calculation. This creates a consistent basis for comparing values that have different historical counts.
4. Examine Distribution
Distribution analysis compares the resulting frequencies to understand how closely or widely the observations are spread.
For example, the current Open frequency data ranges from 8.74% to 10.88%, while the Close frequency data ranges from 8.57% to 11.48%. These ranges describe the observed distribution within the current frequency calculations.
5. Compare Defined Periods
Period analysis separates historical records into defined comparison groups and applies the same measurements to each group.
The current page compares a Recent Period with a Prior Period, including Open-record coverage, Close-record coverage, and the number of distinct Jodis represented in each group. This makes it possible to describe differences between the two historical datasets without treating either period as a prediction model.
6. Record the Calculation Scope
Every statistic needs to be interpreted according to the records actually included in its calculation. The full archive contains 1,199 sessions, while the current Open and Close frequency tables contain 1,167 observations.
This distinction is retained because a calculation should not appear to cover more records than it actually uses. It also makes the historical analysis easier to audit when the underlying archive changes.
7. Interpret Results as Historical Measurements
The final step is interpretation. The measurements describe what was recorded in the available dataset: how often values occurred, how they were distributed, and how selected periods differed.
They do not establish future outcomes, guaranteed patterns, or predictive certainty. Keeping this distinction throughout the methodology ensures that the analysis remains focused on documented historical data rather than unsupported prediction claims.
Related Kalyan Resources
The historical analysis page is part of the wider Kalyan information cluster. The resources below cover different aspects of the market so that historical analysis remains separate from current-result information, timing information, and individual result components.
- Kalyan Matka Market Guide — For the main Kalyan market page, current result information, market structure, historical record access, and general Kalyan resources.
- Kalyan Result Timing Guide — For information about the recorded Kalyan result schedule and timing-related details.
- Kalyan Jodi Records — For historical Kalyan Jodi records and Jodi-specific reference data.
- Kalyan Panel Records — For historical Kalyan Panel/Panna records and panel-specific reference data.
- Satta Matka Chart Guide — For understanding how historical result records are organized through chart-based references.
These resources serve different purposes. While the Satta Matka Result Today main hub provides live daily updates and the Kalyan market page provides broader market context, the timing guide focuses on schedule information, Jodi and Panel pages focus on their respective historical result components, and this page focuses specifically on historical analysis through frequencies, distributions, and period comparisons.
Frequently Asked Questions
Kalyan historical analysis is the examination of previously recorded Kalyan results using an organized historical dataset. It can include frequency calculations, result distributions, and comparisons between defined periods.
The core historical dataset can include the recorded date, Open result, Jodi, and Close result. These fields can then be examined individually or together, depending on the purpose of the analysis.
Yes. Historical records can be divided into clearly defined date ranges and the same measurements can be applied to each period. The comparison should identify the date ranges and record counts used so that the results can be interpreted in context.
No. A higher frequency only describes how often a value appeared within the historical dataset being examined. It does not establish that the value will occur again or provide a guaranteed future outcome.
The date range determines which records are included in a calculation. Changing the period can change the resulting frequencies and distributions, so each analysis should clearly state the historical period on which its observations are based.