The superficial take on the World Series is that it pits a new school, "Moneyball"-style Rays team versus an old school, by the book Phillies team. After all, Rays' General Manager Andrew Friedman, 31, got his start in the business world and relies on statistical analysis to construct his roster, while Phillies' General Manager Pat Gillick, 71, is a classic old school talent evaluator; USA TODAY's Bob Nightengale writes, "If you want to really get to know a player, Gillick says, you don't look at numbers. You look at his heart and soul." However, as Nightengale points out elsewhere in the same piece, a major reason that these two teams are so successful is that they have blended old and new approaches instead of blindly relying solely on observation or exclusively on statistics: "There's an obvious age difference between Pat and Andrew," Rays scouting director R.J. Harrison tells Nightengale. "But they are more alike than people think, and, I think, so are the philosophies of the two organizations. Pat Gillick is the ultimate general manager and is a traditional scouts' man, but Andrew has an incredible foundation of old-school ideas in this game, too. It's just that he incorporates statistical analysis to go along with it. You have to stay current and have to remain flexible to survive in this game and that's what we've done."
Some people try to create a schism between those who primarily believe in the value of observing players firsthand versus those who primarily believe in the value of using statistical analysis to evaluate players. The reality is that any organization that is intelligently run utilizes the best aspects of both of these approaches. I have never criticized statistical analysis in theory but only specific examples of faulty statistical analysis; I definitely think that it is important to incorporate statistics into the player evaluation process but I fervently disagree with anyone who says that any set of numbers can wholly replace the input of a scout who has an "educated eye." It also must be said that it is much simpler to effectively and meaningfully apply statistical analysis to baseball than basketball; baseball is a game that is played station to station and consists of a series of discrete one on one showdowns between the pitcher and the hitter, while basketball is a game of constant motion involving 10 players interacting in ways that are not easy to quantify and, indeed, are frequently quantified inaccurately even with regard to the simple box score numbers that "stat gurus" simultaneously deride for being insufficiently descriptive and yet use as the foundation for their more sophisticated metrics: the old phrase "garbage in, garbage out" applies here, because to the extent that the box score numbers are subjective and/or simply wrong, the metrics that are based on those numbers are also skewed.