Open Analytics - SWEAT

    The SWEAT token has launched, to great fanfare! Give us your best open analysis of SWEAT's launch and the role of SWEAT in the NEAR ecosystem

    What is the purpose of this dashboard?

    we want to analyze SWEAT's and know the role of SWEAT in the NEAR ecosystem because of this aim, we want to compare SWEAT with 1 random tokens and all other tokens With this strategy, we can have a good analysis of sweat and know its role in the near ecosystem

    The tokens selected for comparison are as follows

    1. app.nearcrowd.near

    Comparison of Sweat token with 1 randomly selected tokens and all tokens

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    Statistics related to SWEAT since its inception: In the graph on the right, you can see that SWEAT has allocated an 8% share of unique transactions since its inception, and the share of app.nearcrowd.near is almost 28%, and the rest of the transactions are about 63%.

    Statistics related to SWEAT in the last 30 days: As can be inferred from the chart above, the unique transactions related to the pool account for approximately 20% of the total transactions, the other has a share of about 25%, and the unique transactions related to the rest of the tokens are about 54%.

    A simple but important result

    As you can see, with the passage of time, the share of SWEAT becomes more and more widespread until it has reached more than 20% in the last 30 days. This indicates an upward trend in SWEAT and possibly a bright future.

    Daily Comparison of Sweat token

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    As you can see, on September 11th, the number of unique transactions related to SWEAT suddenly increased to the point where in some cases it even exceeded the total number of transactions of our remaining tokens. At the same time, we don't see this situation at all for app.nearcrowd.near.

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    What is the time of the first successful transaction?

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    Comparison Gas use

    Another thing that can be used to check the state of sweat is the amount of gas consumed. For this purpose, we want to compare the daily, monthly, and total gas used consumption with other tokens

    Interesting results were obtained from the gas consumption calculation.

    The daily gas consumption chart (upper left chart) shows that around September 9, SWEAT started to move, while before that it had less gas consumption than the rest of the tokens, even the amount of SWEAT consumption gas. It was less than app.nearcrowd.near, but suddenly, with its impressive start, in a very short period of time, it passed app.nearcrowd.near and the total gas consumption of the remaining tokens.

    Monthly gas consumption chart (upper right chart)

    In a way, it stabilizes the graph on the left side. If you pay attention, until September, the amount of SWEAT is so small that you don't see a bar, but all of a sudden, in September, the amount of SWEAT gas consumption appears on the chart in a powerful way.

    The third graph (bottom left) shows the percentage of SWEAT gas consumption from the beginning of work until today. The share of SWEAT from the beginning of its creation until today is about 14%, but since the upward movement of SWEAT has recently started, we decided to calculate the ratio of the last month as well (bottom right chart). The result of this chart is a 57% share. SWEAT expresses the total ratio and this clearly shows the powerful movement of SWEAT

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    final conclusion

    When we look at the charts above, everything points to a SWEAT move since around September 11th Analysis of app.nearcrowd.near In addition to SWEAT and comparing SWEAT with all tokens, it is clear that this mutation is not universal and is only for SWEAT.