03-04-2010, 02:47 AM
I think anyone who works in a profession that requires specific knowledge, understands, that a person with knowledge will provide a better evaluation than statistics. I think so many people, spend so much time with baseball stats, that they don't think baseball is like the rest of the world.
People have no problem understanding human evaluation is far superior to stats in football. That is because even a moderate sports fan, will see a lot of players in action, spend little time going over stats, but still be able to form opinions about who will make a good pro. Even a moderate sports fan can see that stats are not comparable from conference to conference, and there is no formula to correlate college stats to pro.
The very best amateur players make the majors. The best players will tend to have the best stats. By reverse engineering that stats of players that have made the Majors, you can show how their stats predicted their ML success. However since most players in an amateur league do not make the Majors, you can not use any given amateur stat line to predict pro performance.
Stats also leave a lot to be desired when evaluating ML talent. What any given stat measures, may not be the best way to evaluate any given player. Most of them are best at evaluating the best players and the performance of better players tends to very less from year to year. Stats do a worse job on marginal players, there tends to be less data and more variance.
People have no problem understanding human evaluation is far superior to stats in football. That is because even a moderate sports fan, will see a lot of players in action, spend little time going over stats, but still be able to form opinions about who will make a good pro. Even a moderate sports fan can see that stats are not comparable from conference to conference, and there is no formula to correlate college stats to pro.
The very best amateur players make the majors. The best players will tend to have the best stats. By reverse engineering that stats of players that have made the Majors, you can show how their stats predicted their ML success. However since most players in an amateur league do not make the Majors, you can not use any given amateur stat line to predict pro performance.
Stats also leave a lot to be desired when evaluating ML talent. What any given stat measures, may not be the best way to evaluate any given player. Most of them are best at evaluating the best players and the performance of better players tends to very less from year to year. Stats do a worse job on marginal players, there tends to be less data and more variance.
I like you guys a lot.