This is a good and interesting question. Since YCombinator depends on finding Dropbox and AirBnB scale startups, I imagine one of the most important metrics to

This is a good and interesting question. Since YCombinator depends on finding Dropbox and AirBnB scale startups, I imagine one of the most important metrics to them is whether they've rejected a business that went on to achieve that scale. Of course being in YCombinator can increase a venture's chance of hitting that type of success, so keeping track of who they rejected is just a proxy for how well their applications strategy is. They may have rejected a company that _could have become_ AirBnB or Dropbox. But this is less important since in this case that would indicate that this ability lies with YC, not the startup, and so it's less important which companies they pick. If true, this would run counter to the founder-centric model they profess, so I'm skeptical it's how they feel. This question of who to let in reminds me of the tradeoff of precision and recall in IR. A large class can reasonably be termed higher recall, while a class where they actively exclude companies with predictors of failure increases the precision. THe two metrics are inversely related, but it's possible to have high precision and recall if you're only looking for a very few number of things and you pick them all. It seems to me that culling out likely failures would only make sense if the partners had determined that the presence of these likely-to-fail companies negatively impacted their ability to help other companies reach their potential. This seems a likely rationale to me based on PG's comments about how dying startups take up so much of their time. So what it really seems to represent is a vote of confidence in the partners' ability to help startups increase their chance of massive growth. And/or a recognition that likely-to-fail startups have deleterious effects on the rest of their batch that outweigh the likelihood that they'll be successful outliers. Either way it doesn't seem to have much impact on companies that apply. It will be interesting to see if PG writes a How Not to Apply essay. Such an essay might destroy the predictive value of these behaviors, but if it stops the behaviors and they were causally linked to bad outcomes then it's a net gain.