Trend Towards Data Integrity Continues as On-Chain Analysis Study Highlights Centralization in Mining Pool Payouts

Recent research demonstrates a high degree of concentration in the payouts made by mining pools. Exchanges and wallet providers were found to account for a high percentage of payouts. Furthermore, the research delves into the hash rate share of mining pools over time.

Quick take;

  • Ambiguous methodology for data provided by services sparked the need for a transparent on-chain analysis of mining hash rate shares
  • Hash rates shares have at times exhibited high degrees of centralization but have recently been more widely distributed when compared with early 2018
  • An analysis of payouts made by mining pools reveals that the majority of payments are made to a small number of entities with exchanges and wallet providers noted to be among these

A research paper (Romiti et al. 2019) published in May has revealed that the majority of payouts made by major mining pools in the Bitcoin network goes to a small number of entities, exchanges and wallet providers chief among them. The study was completed by researchers at the Austrian Institute of Technology, SBA Research, and the Imperial College London.

The research further explored the historic shares of hash rate among mining pools. The study confirmed that the distribution of the hash rate in Bitcoin has been at times highly centralized with three to four pools commonly accounting for over 50% of the hash rate.

A Wider Trend Towards Data Integrity

There has been a wider trend toward data transparency and integrity in 2019. There have been numerous revelations that data sources have been inaccurate and unreliable. For example, a study completed by BitWise Asset Management found strong evidence that the volume reported by the majority of exchanges is likely to be artificially generated through practices such as wash trading.

As a result of this trend, numerous companies have been tailoring their model to provide accurate and trustworthy data to their users. Messari has established a tokens registry whereby projects registered with their service have to comply with high transparency standards. CoinMetrics have expanded their operations to providing premium data services after fundraising. Circle Research recently noted the need for data analysis companies in the cryptocurrency industry to move industry data towards being comprehensible, trustworthy, and accessible.

The quality and reliability of data lie at the core of why this research is needed. Services such as and have provided data on the distribution of hash but there have been no clear disclosures on how this data is constructed.  The Romiti et al. study used on-chain analysis to examine hash rate distribution over a 5-year period highlighting times when there were high levels of centralization.

The study further delved into the distribution of payouts from mining pools. There were some limitations on the analysis of payouts with the time frame studied only spanning a month. However, the study managed to shine a light on degrees of centralization also present in the payouts mining pools deliver.

Hash Rate Centralization

It is no surprise that high levels of centralization have at times been present in the hash rate distribution of the Bitcoin network. This has been a widely reported topic which has sparked much debate about the true degree of decentralization in the Bitcoin network.

The below graphic illustrates the evolution of hash rate shares among mining entities. The red line illustrates the 50% mark. The black line tracks the Gini coefficient, a metric used to quantify inequality.

(Romiti et al., 2019, p.8)

With Bitmain controlling AntPool and and also being an investor in ViaBTC, the combined hash rate of these entities is of particular relevance to the topic of centralization. Three mining pools, two of which are controlled by Bitmain, managed to acquire over 50% of the hash rate from early to mid-2018. The distribution of the hash rate has been shifting toward a wider distribution since. The share attributable to Bitmain associated pools has declined while the share attributable to smaller mining pools and unknown mining entities has been increasing.  These findings are consistent with recent data released by publication Diar. The Diar report showed the share attributable to small mining pools roughly doubling since the start of 2018 while the share attributed to Bitmain-related pools declined from over 50% to less than 40%.

Another phenomenon noted in the Romiti et al. paper is the changing dominance of mining pools. The pools which control the largest shares of hash rate today are different from the ones which were dominant in 2016. BTCC, Bitfury, and BW Pool were the largest pools in 2016 but are relatively small players today.

The Gini coefficient graphed in black on the Romiti et al. graph shows changes in the degree of inequality of mining hash rate share. The Gini coefficient ranges from 0 to 100 with 100 representing complete inequality and 0 representing complete equality. The below table compares the Gini coefficient of mining share on the Bitcoin network to the distribution of the wealth Gini coefficient in some major economies. The Gini coefficient of mining on the Bitcoin network indicates high levels of inequality with the major pools representing the vast majority of mining power. The recent increases in shares attributable to small mining pools as well as the changing dominance of major pools may suggest that the equality distribution will become more egalitarian with time. However, such an outlook is highly contentious as markets also tend to develop in a manner where an increasing amount of a resource concentrates in an increasingly small number of entities.

The Gini Coefficient of mining on the Bitcoin network compared to the Gini coefficient of wealth distribution in major economies

Mining Pool Payout Centralization

The most unique angle explored in the research is the nature of payouts made by mining pools. This area has not been examined before and the findings demonstrated that the payouts also exhibit high degrees of inequality.

On-chain payments executed by the Antpool,, and ViaBTC mining pools were analysed over the course of one month in 2018. Various payment structures were identified for each of the pools. AntPool exhibited the greatest tendency to change the addresses which payments were executed from. This demonstrates that they likely have the greatest emphasis for privacy of the three pools.

Across the three pools, less than 18% of the entities were found to receive greater than 50% of the payments. Cryptocurrency exchanges and wallet providers were found to hold high shares in each pool. Huobi, Xapo, and Bittrex were listed among the businesses holding large shares in the three pools examined. These exchanges and wallet providers tended towards being in close geographical proximity and there was also a high degree of cross-pool mining whereby the noted entities mined in two or more of the three pools analysed.

There were some significant limitations to the payout analysis. The study examined only three pools over the course of just one month. Nonetheless, the study serves to reveal some information on the nature of payouts made by mining pools. The methods applied by the research were also described in detail enabling other researchers to reproduce the findings or use a similar methodology for a wider exploration of the nature of payouts made by mining pools.