This is a really interesting question. Humans tend to be pretty good at accepting things that are mostly random, or mostly skill-based, but have a surprisingly

This is a really interesting question. Humans tend to be pretty good at accepting things that are mostly random, or mostly skill-based, but have a surprisingly hard time with things that involve a combination of skill and luck. For a great example of this, watch amateur poker players. This is just as true in investing-people tend to espouse either "all skill" (e.g. Warren Buffett") or "all luck" (one common interpretation of the Efficient Market Hypothesis.) Even defining skill in investing is difficult. High-risk investments tend to have a high return, so skill is getting an outsized return compared to the amount of risk involved. But the simple measures of risk (e.g. Beta) are not good actual measure of risk. For example, a company whose stock price suddenly plummeted is often a good investment since the market tends to overreact to bad news. Furthermore, the stock is now lower-risk because it has less to lose. But it will appear extremely high risk by most common measures. I think it's a decent assumption in VC to treat all investments at stage X as equally risky. E.g. angel investments are one category, series A as another. This is obviously not 100% perfect but is a decent approximation. Then we can ask the following question: how did Sequoia Capital's series A investments in a certain time period (say 2000-2005) perform compared to all other series A investments? It's important that you look at all of a VC's investments and not just a particular fund, because firms will often bury their bad funds. I have no idea if that kind of data is available anywhere, though.