"Peer" scouting is based on the same premise as economic markets: the wisdom of crowds. Stock market prices represent the summary judgment of millions of opinions of a particular stock. Using this analogy with respect to scouting, imagine if stock prices were the summary judgment of only 2 or 3 investors. Large inefficiencies would exist. Qualitative scouting suffers from too few observations.

While the wisdom of crowds is the basis of "Peer" scouting, the greatest value comes from the wisdom of experts. While most professional scouts have expert scouting “tools,” their limited exposure to players limits their effectiveness. So who are the true experts in evaluating players? Other players.

Anyone who has ever played on a baseball team understands that the players know better than outsiders who has what tools, who is a gamer, and who projects the highest ceiling. If you asked 25 players to independently and objectively rank all of the players on a team, there would be a very high rankiorder correlation. Furthermore, players are experts at evaluating the competition: they face them day in, day out. They know the precise movement of a pitcher's two-seam fastball as it breaks in on his hand and can rank that relative to a flat pitch served up on a tee. Flat out, ballplayers know ballplayers best.

Fair and objective scouting? Since PeerScout is open to any player, any individual "peer" scout could over or under rate a player, either on purpose or just by misjudging the player. In fact, in pre-launch testing we have found biases to be limited. First, players at this level don’t get there by being dishonest; make-up matters. Second, professional teams want to see not only how players scout you, but also how you scout other players. Third, the law of large numbers eliminates the small number of biased projections. Finally, statistical software can eliminate outliers to improve the quality of the scouting report. When scouting reports are compared to a player’s statistical history, outliers are easily identified and eliminated.