Who You Fund From Matters More Than You Think in Seed Rounds For founders, knowing which venture capitalists (VCs) often co-invest can save time and refine their financing strategy. Each deal is a fingerprint. Once these stories are visualized, the narratives behind them can be unlocked.

In other words, you can track the nodes responsible for most of the financing in the crypto space and try to find the "ports" in today's trade networks, not unlike the merchants of a thousand years ago.

This will be an interesting experiment for two reasons:

The current venture capital (VC) network operates somewhat like a "fight club," with about 80 funds. And in the past year, about 240 funds have invested over $500,000 in seed rounds. This means the network maintains direct contact with one-third of these funds.

But tracking the actual deployment of funds is difficult. Sending the latest information to each fund would only cause disturbance. This tracking tool is a filtering tool that can understand which funds have made investments, in which areas, and with whom.

For founders, understanding the capital allocation is just the first step; more valuable is understanding the performance of these funds and who they usually co-invest with. To understand this, the historical probability of follow-on investments by funds was calculated, but this probability becomes blurry in later stages (such as Series B rounds) because companies usually issue tokens instead of traditional equity financing.

The first step is to help founders identify which investors are active in the crypto venture investment field. The next step is to understand which sources of capital actually perform better. Once this data is grasped, you can explore which funds' co-investments can lead to better results. Of course, this is not rocket science. No one can guarantee a Series A round of financing just because someone has written a check. Just as no one can guarantee marriage after the first date. But understanding the situation you are about to face, whether it is dating or investing, undoubtedly has great benefits.

The Path to Success You can use some basic logic to identify the funds with the most follow-on financing rounds in their portfolios. If a fund's invested companies have secured financing after the seed round, then that fund is likely doing something right. When a company raises financing at a higher valuation in the next round, the value of the VC's investment increases. Therefore, follow-on financing rounds can serve as an important indicator of performance.

This article selected the 20 funds with the most follow-on financing in their portfolios, then calculated the total number of companies they invested in at the seed stage. Based on this number, the probability of founders securing follow-on financing can be calculated. If a fund invested in 100 companies at the seed stage, and 30 of them secured follow-on financing within two years, then the calculated "graduation" probability is 30%.

It should be noted that the screening criteria set here is a two-year period. Often, startups may choose not to raise financing, or only do so after two years.

Even among the top 20 funds, the law of the few is extremely pronounced. For example, securing financing from a16z means you have a 1/3 chance of securing follow-on financing within two years. That is, one out of every three startups supported by a16z will secure Series A financing. Considering the probability at the other end is only 1/16, this is quite a high graduation rate.

Funds ranked near 20th (on this list of the top 20 funds with follow-on investments) have a 7% chance of seeing a company continue to raise financing. These numbers may seem similar, but to facilitate understanding, a probability of 1/3 is equivalent to rolling a die and getting a number less than 3, and a probability of 1/14 is roughly equivalent to the chance of having twins. These results are significantly different in terms of both words and probability.

Joking aside, this demonstrates the degree of aggregation within crypto venture capital funds. Some VC funds can arrange follow-on financing for their portfolio companies because they also have growth funds. So they will invest in the same company at both the seed and Series A rounds. When a VC fund doubles down on the shares of the same company, it usually sends a positive signal to subsequent investors. In other words, within VC firms, the presence of growth funds can greatly affect the company's chances of success in the coming years.

In the long run, crypto venture capital funds in the crypto field will gradually evolve into private equity investments in projects that already have substantial revenues.

We have a theoretical basis for this transformation. But what does the data reveal? To study this, the number of startups with follow-on financing among investor groups was examined. Then, the proportion of companies in which the same venture fund participated in follow-on financing was calculated.

That is to say, if a company received seed financing from a16z, how likely is it that a16z will invest in its Series A round?

It quickly becomes apparent that there is a clear pattern. Large funds managing over $1 billion in capital are more inclined to frequently participate in follow-on financing. For example, in a16z's portfolio, 44% of the companies received follow-on investments from a16z. Blockchain Capital, DCG, and Polychain have followed up on one-quarter of their investments. In other words, at the seed or pre-seed stage, financing from whom is much more important than you might think because these investors tend to support their projects again.

Habitual Co-investment These patterns are the results of post-event summaries. They do not imply that companies financed by non-top-tier VCs are doomed to fail. All economic activities aim for growth or profit creation. Companies that achieve either goal will see their valuations rise over time. But this does help improve your chances of success. If you cannot finance from this group (the top 20 VCs), then one way to improve your chances of success is to leverage their network. Or rather, to establish connections with these capital hubs.

The image below shows the network of all crypto venture investors over the past decade. There are 1,000 investors with about 22,000 connections between them. If one investor co-invests with another, a connection is formed. This may seem crowded, even overwhelming with too many options.

However, it covers funds that have shut down, never returned funds, or no longer invest.

The clearer image below shows the future direction of the market. If you are a founder seeking Series A financing, there are about 50 funds with a pool of over $2 million. The investor network participating in such rounds consists of about 112 funds. Moreover, these funds are becoming increasingly concentrated, more inclined to co-invest with specific partners.

As time goes on, funds seem to form co-investment habits. That is to say, funds that invest in a particular entity often introduce another peer fund, either because their skills are complementary (for example, in technology or providing help in market promotion) or based on partnership relationships. To study how these relationships work, this article explored the co-investment patterns between funds over the past year.

For example, in the past year:

• Polychain and Nomad Capital have 9 co-investments.

• Bankless and Robot Ventures have 9 co-investments.

• Binance and Polychain have 7 co-investments.

• Binance and HackVC have the same number of co-investment projects.

• Similarly, OKX and Animoca have 7 co-investments. Large funds are becoming increasingly strict about their co-investors.

For instance, last year, Robot Ventures participated in three of the 10 investments made by Paradigm.

DragonFly co-invested with Robot Ventures and Founders Fund in three rounds, with these three institutions making a total of 13 investments.

Similarly, Founders Fund co-invested with Dragonfly three times, accounting for one-third of the latter's 9 investments.

In other words, we are transitioning into an era where few funds make large investments, and co-investors are becoming fewer and fewer. And these joint investors are often some of the well-established institutions with a long history.

Entering the Matrix Another way to study this data is to analyze the behavior of the most active investors. The matrix above considers the funds with the most investments since 2020, as well as their relationships. You will notice that accelerators (such as Y Combinator or Outlier Venture) rarely co-invest with exchanges (such as Coinbase Ventures).

On the other hand, exchanges often have their own preferences. For example, OKX Ventures has a high rate of joint investments with Animoca Brands. Coinbase Ventures has made over 30 investments with Polychain, and 24 with Pantera.

What can be seen are three structural issues:

• Despite high investment frequency, accelerators rarely co-invest with exchanges or large funds. This may be due to stage preferences. Accelerators tend to invest in early stages, while large funds and exchanges prefer growth-stage investments.

• Large exchanges often have a strong preference for growth-stage venture funds. Currently, Pantera and Polychain dominate.

• Exchanges tend to cooperate with local participants. OKX Ventures and Coinbase show different preferences when choosing co-investment partners. This highlights the global nature of today's Web3 capital allocation.

So, if venture capital funds are clustering, where will the next marginal capital come from? It can be noticed that there is an interesting pattern: corporate capital also has its own clusters. For example, Goldman Sachs has co-invested with PayPal Ventures and Kraken in two rounds. Coinbase Ventures has made 37 co-investments with Polychain, 32 with Pantera, and 24 with Electric Capital.

Unlike venture capital, corporate funds are usually aimed at established long-term businesses with substantial PMF. Therefore, the performance of this fund pool remains to be seen as early-stage venture financing declines.

The Evolving Network A few years ago, after reading Niall Ferguson's "The Square and the Tower," I began to study the relationship networks in the crypto space. This book reveals how the spread of ideas, products, and even diseases is related to networks. It wasn't until a few weeks ago, after building a financing dashboard, that I realized it was possible to visualize the network of connections between sources of capital in the crypto field.

Such datasets and the nature of these entities' economic interactions can be used to design (and execute) M&A between private entities and token acquisitions. Both of these tasks are being explored internally. They can also be used for business expansion and partnership plans. We are still researching how to allow specific companies access to these datasets.

Back to the topic at hand.

Do networks really help funds achieve better performance?

The answer is a bit complex.

The ability of a fund to choose the right team and provide sufficient funding will be more important than its relationships with other funds. However, what really matters is the personal relationships between general partners (GPs) and other co-investors. Investors do not share deals with company logos, but with people. When partners change funds, these connections only transfer to their new funds.

I have a sense of this, but lack the means to verify it. Fortunately, a 2024 paper studied the performance of the top 100 VC firms over time. In fact, they studied 38,000 financing rounds of 1,084 companies, even breaking it down by market seasonality. The core of their argument can be summarized into a few facts.

Past co-investments do not represent future cooperation. If previous investments fail, funds may choose not to cooperate with other funds again. For example, think of the network that broke when FTX went bankrupt. During boom periods, due to funds wanting to deploy capital more actively, co-investments tend to increase. In boom periods, venture capitalists rely more on social signals rather than due diligence. During bear markets, due to lower valuations, funds will deploy cautiously and often act alone. Funds choose peers based on complementary skills. Therefore, if all investors in a round focus on the same field, it often leads to problems. As mentioned earlier, ultimately, co-investments do not occur at the fund level, but at the partner level. In personal careers, I have seen some people jump between different institutions. Their goal is often to collaborate with the same person, regardless of which fund they join. In an era where artificial intelligence is gradually replacing human work, understanding interpersonal relationships remains the foundation of early-stage venture investment, which is very helpful.

There is still much work to be done in the study of how crypto venture capital networks are formed. For instance, it would be interesting to study the preferences of liquidity-focused funds in capital allocation, or how later deployment evolves with market seasonality. Or how M&A and private equity fit into this. The answers may be hidden in the existing data, but all of this will take time.

Who You Fund From Matters More Than You Think in Seed Rounds For founders, knowing which venture capitalists (VCs) often co-invest can save time and refine their financing strategy. Each deal is a fingerprint. Once these stories are visualized, the narratives behind them can be unlocked.

In other words, you can track the nodes responsible for most of the financing in the crypto space and try to find the "ports" in today's trade networks, not unlike the merchants of a thousand years ago.

This will be an interesting experiment for two reasons:

The current venture capital (VC) network operates somewhat like a "fight club," with about 80 funds. And in the past year, about 240 funds have invested over $500,000 in seed rounds. This means the network maintains direct contact with one-third of these funds.

But tracking the actual deployment of funds is difficult. Sending the latest information to each fund would only cause disturbance. This tracking tool is a filtering tool that can understand which funds have made investments, in which areas, and with whom.

For founders, understanding the capital allocation is just the first step; more valuable is understanding the performance of these funds and who they usually co-invest with. To understand this, the historical probability of follow-on investments by funds was calculated, but this probability becomes blurry in later stages (such as Series B rounds) because companies usually issue tokens instead of traditional equity financing.

The first step is to help founders identify which investors are active in the crypto venture investment field. The next step is to understand which sources of capital actually perform better. Once this data is grasped, you can explore which funds' co-investments can lead to better results. Of course, this is not rocket science. No one can guarantee a Series A round of financing just because someone has written a check. Just as no one can guarantee marriage after the first date. But understanding the situation you are about to face, whether it is dating or investing, undoubtedly has great benefits.

The Path to Success You can use some basic logic to identify the funds with the most follow-on financing rounds in their portfolios. If a fund's invested companies have secured financing after the seed round, then that fund is likely doing something right. When a company raises financing at a higher valuation in the next round, the value of the VC's investment increases. Therefore, follow-on financing rounds can serve as an important indicator of performance.

This article selected the 20 funds with the most follow-on financing in their portfolios, then calculated the total number of companies they invested in at the seed stage. Based on this number, the probability of founders securing follow-on financing can be calculated. If a fund invested in 100 companies at the seed stage, and 30 of them secured follow-on financing within two years, then the calculated "graduation" probability is 30%.

It should be noted that the screening criteria set here is a two-year period. Often, startups may choose not to raise financing, or only do so after two years.

Even among the top 20 funds, the law of the few is extremely pronounced. For example, securing financing from a16z means you have a 1/3 chance of securing follow-on financing within two years. That is, one out of every three startups supported by a16z will secure Series A financing. Considering the probability at the other end is only 1/16, this is quite a high graduation rate.

Funds ranked near 20th (on this list of the top 20 funds with follow-on investments) have a 7% chance of seeing a company continue to raise financing. These numbers may seem similar, but to facilitate understanding, a probability of 1/3 is equivalent to rolling a die and getting a number less than 3, and a probability of 1/14 is roughly equivalent to the chance of having twins. These results are significantly different in terms of both words and probability.

Joking aside, this demonstrates the degree of aggregation within crypto venture capital funds. Some VC funds can arrange follow-on financing for their portfolio companies because they also have growth funds. So they will invest in the same company at both the seed and Series A rounds. When a VC fund doubles down on the shares of the same company, it usually sends a positive signal to subsequent investors. In other words, within VC firms, the presence of growth funds can greatly affect the company's chances of success in the coming years.

In the long run, crypto venture capital funds in the crypto field will gradually evolve into private equity investments in projects that already have substantial revenues.

We have a theoretical basis for this transformation. But what does the data reveal? To study this, the number of startups with follow-on financing among investor groups was examined. Then, the proportion of companies in which the same venture fund participated in follow-on financing was calculated.

That is to say, if a company received seed financing from a16z, how likely is it that a16z will invest in its Series A round?

It quickly becomes apparent that there is a clear pattern. Large funds managing over $1 billion in capital are more inclined to frequently participate in follow-on financing. For example, in a16z's portfolio, 44% of the companies received follow-on investments from a16z. Blockchain Capital, DCG, and Polychain have followed up on one-quarter of their investments. In other words, at the seed or pre-seed stage, financing from whom is much more important than you might think because these investors tend to support their projects again.

Habitual Co-investment These patterns are the results of post-event summaries. They do not imply that companies financed by non-top-tier VCs are doomed to fail. All economic activities aim for growth or profit creation. Companies that achieve either goal will see their valuations rise over time. But this does help improve your chances of success. If you cannot finance from this group (the top 20 VCs), then one way to improve your chances of success is to leverage their network. Or rather, to establish connections with these capital hubs.

The image below shows the network of all crypto venture investors over the past decade. There are 1,000 investors with about 22,000 connections between them. If one investor co-invests with another, a connection is formed. This may seem crowded, even overwhelming with too many options.

However, it covers funds that have shut down, never returned funds, or no longer invest.

The clearer image below shows the future direction of the market. If you are a founder seeking Series A financing, there are about 50 funds with a pool of over $2 million. The investor network participating in such rounds consists of about 112 funds. Moreover, these funds are becoming increasingly concentrated, more inclined to co-invest with specific partners.

As time goes on, funds seem to form co-investment habits. That is to say, funds that invest in a particular entity often introduce another peer fund, either because their skills are complementary (for example, in technology or providing help in market promotion) or based on partnership relationships. To study how these relationships work, this article explored the co-investment patterns between funds over the past year.

For example, in the past year:

• Polychain and Nomad Capital have 9 co-investments.

• Bankless and Robot Ventures have 9 co-investments.

• Binance and Polychain have 7 co-investments.

• Binance and HackVC have the same number of co-investment projects.

• Similarly, OKX and Animoca have 7 co-investments. Large funds are becoming increasingly strict about their co-investors.

For instance, last year, Robot Ventures participated in three of the 10 investments made by Paradigm.

DragonFly co-invested with Robot Ventures and Founders Fund in three rounds, with these three institutions making a total of 13 investments.

Similarly, Founders Fund co-invested with Dragonfly three times, accounting for one-third of the latter's 9 investments.

In other words, we are transitioning into an era where few funds make large investments, and co-investors are becoming fewer and fewer. And these joint investors are often some of the well-established institutions with a long history.

Entering the Matrix Another way to study this data is to analyze the behavior of the most active investors. The matrix above considers the funds with the most investments since 2020, as well as their relationships. You will notice that accelerators (such as Y Combinator or Outlier Venture) rarely co-invest with exchanges (such as Coinbase Ventures).

On the other hand, exchanges often have their own preferences. For example, OKX Ventures has a high rate of joint investments with Animoca Brands. Coinbase Ventures has made over 30 investments with Polychain, and 24 with Pantera.

What can be seen are three structural issues:

• Despite high investment frequency, accelerators rarely co-invest with exchanges or large funds. This may be due to stage preferences. Accelerators tend to invest in early stages, while large funds and exchanges prefer growth-stage investments.

• Large exchanges often have a strong preference for growth-stage venture funds. Currently, Pantera and Polychain dominate.

• Exchanges tend to cooperate with local participants. OKX Ventures and Coinbase show different preferences when choosing co-investment partners. This highlights the global nature of today's Web3 capital allocation.

So, if venture capital funds are clustering, where will the next marginal capital come from? It can be noticed that there is an interesting pattern: corporate capital also has its own clusters. For example, Goldman Sachs has co-invested with PayPal Ventures and Kraken in two rounds. Coinbase Ventures has made 37 co-investments with Polychain, 32 with Pantera, and 24 with Electric Capital.

Unlike venture capital, corporate funds are usually aimed at established long-term businesses with substantial PMF. Therefore, the performance of this fund pool remains to be seen as early-stage venture financing declines.

The Evolving Network A few years ago, after reading Niall Ferguson's "The Square and the Tower," I began to study the relationship networks in the crypto space. This book reveals how the spread of ideas, products, and even diseases is related to networks. It wasn't until a few weeks ago, after building a financing dashboard, that I realized it was possible to visualize the network of connections between sources of capital in the crypto field.

Such datasets and the nature of these entities' economic interactions can be used to design (and execute) M&A between private entities and token acquisitions. Both of these tasks are being explored internally. They can also be used for business expansion and partnership plans. We are still researching how to allow specific companies access to these datasets.

Back to the topic at hand.

Do networks really help funds achieve better performance?

The answer is a bit complex.

The ability of a fund to choose the right team and provide sufficient funding will be more important than its relationships with other funds. However, what really matters is the personal relationships between general partners (GPs) and other co-investors. Investors do not share deals with company logos, but with people. When partners change funds, these connections only transfer to their new funds.

I have a sense of this, but lack the means to verify it. Fortunately, a 2024 paper studied the performance of the top 100 VC firms over time. In fact, they studied 38,000 financing rounds of 1,084 companies, even breaking it down by market seasonality. The core of their argument can be summarized into a few facts.

Past co-investments do not represent future cooperation. If previous investments fail, funds may choose not to cooperate with other funds again. For example, think of the network that broke when FTX went bankrupt. During boom periods, due to funds wanting to deploy capital more actively, co-investments tend to increase. In boom periods, venture capitalists rely more on social signals rather than due diligence. During bear markets, due to lower valuations, funds will deploy cautiously and often act alone. Funds choose peers based on complementary skills. Therefore, if all investors in a round focus on the same field, it often leads to problems. As mentioned earlier, ultimately, co-investments do not occur at the fund level, but at the partner level. In personal careers, I have seen some people jump between different institutions. Their goal is often to collaborate with the same person, regardless of which fund they join. In an era where artificial intelligence is gradually replacing human work, understanding interpersonal relationships remains the foundation of early-stage venture investment, which is very helpful.

There is still much work to be done in the study of how crypto venture capital networks are formed. For instance, it would be interesting to study the preferences of liquidity-focused funds in capital allocation, or how later deployment evolves with market seasonality. Or how M&A and private equity fit into this. The answers may be hidden in the existing data, but all of this will take time.