![image.png](https://files.peakd.com/file/peakd-hive/muratkbesiroglu/23ynKkBCZ9SBUK4eHBjxj5hGnhuRmZPYR6jRd6u8EdteF623ZYYdUw1x8gDc3z6GQ3SXw.png)

The phrase “you can't manage it if you can't measure it” pointing out the importance of data was once very popular in the business world. Relying on numbers rather than opinions is a reasonable approach. After all, data don't lie, unless you torture them.

When it comes to data, the first method that comes to mind is technical analysis. It is also necessary to learn the history and utility of the crypto asset we will invest in. Tradingview, Coingecko, Coinmarketcap are the main sources of information on these issues.

There is also on-chain data that fewer investors use. From time to time, the people on various Youtube channels give us hints on this subject. Like “The amount of Bitcoin on central exchanges has decreased,” or “Small investors are selling, while whales are buying Bitcoins”.

In today's article, I would like to talk in detail about https://messari.io/, an important resource that I benefit from. Although the site is free to use, they offer more in-depth information to members. For those who are curious about the paid information, there is a 7-day free trial subscription option.

The information I use most in Messari is the **Current Inflation**. Whatever coin I have invested in, which has high inflation, has not made me happy. Anyway, if I wanted to invest in hyperinflationary assets, I would invest in fiat currencies. Link for crypto inflation information on the site: https://messari.io/screener/340B7D0D

Although the current inflation information gives a general idea about the coin supply, I prefer to see the development. You can see the Hive **Circulating Supply** price relationship in the chart below. The inverse relationship seems obvious. Link to chart: https://messari.io/asset/hive/chart/sply-circ


![image.png](https://files.peakd.com/file/peakd-hive/muratkbesiroglu/23tGRVNAgb7ZhRjnaeLH3SMTXUUabhBkHXiTCJZA3KAz7M57MCkXvz5KRXshghUsGMGn5.png)


I would like to point out that whether the circulating supply downtrend on the chart will continue or not will be important for the direction of the Hive price. (Here, there may be a cause-effect relationship as well as a mutual determination relationship. However, I think that the cause-effect relationship is more dominant.)

Another interesting piece of information Messari provides is **Real Volume**. It will be very useful for those who do technical analysis on the transaction volume.

Under the heading **Addresses**, Messari gives the evolution of the number of wallets holding a particular cryptocurrency over time. It is possible to see this information of whales and small account holders separately. Considering that the market is mostly driven by those with excess money, it is useful to see the preferences of whales through data.

Under the heading **Network Activity** there is also information about what percentage of Proof-of-Stake coins are staked. A high staking rate is preferable for a coin. In addition, the amount of coins available on centralized exchanges for major coins such as Bitcoin and Ethereum is also important data. The small amount of coins on centralized exchanges indicates that HODLers are in control.

Messari only gives Reddit user counts of chains or tokens. It may be more accurate to follow social media trends on https://lunarcrush.com/.


![image.png](https://files.peakd.com/file/peakd-hive/muratkbesiroglu/EpCFDVD9Fca4EdgcvRzqJS9jkMFkETyeNJj4txa2vX81iipsv4xgBjoGKYiUF9oBLmV.png)


Each category in the crypto market has its own data sources. https://defillama.com/ is a leading reference resource on Defi. I follow which games are popular in the crypto world on https://dappradar.com/. I'm looking at the statistics of NFT collections on https://opensea.io/.

I don't know of a site that provides comprehensive information on Metaverses, which is the rising trend of recent days. 

I am working on a forecasting model that will relate the data I listed above to prices. I conducted the first experiments using logistic regression. The results are not bad at all. Of course, new data needs to be added to the model and the validity of the results needs to be tested over time. I'm not in a rush on this. I will take firm steps forward.

Thank you for reading. 

**Image Sources:** https://unsplash.com/ and https://unblast.com/