Most Accurate MLB Experts Past 4 Years
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RynMan wrote:I like their theories and articles, and as far as accurate projections go, I dont think you can do much better. But at the same time they tend to be a little pessimistic when it comes to projections.
For hitters:
[The PETCOA] Forecast is a representation of the hitter's expected performance in the upcoming season at various levels of probability. For example, if a hitter's 75th percentile EQA forecast is .296, this indicates that he has a 75% chance to post an EQA less than or equal to .296, and a 25% chance to post an EQA better than .296. Higher percentiles indicate more favorable outcomes.
PECOTA runs a series of regressions within the set of comparable data in order to estimate how changes in peripheral statistics are related to changes in equivalent runs. For example, if it first estimates that Pat Burrell will produce 100 equivalent runs next year, it then tries to determine what home run total, walk total, and so on are most likely to be associated with a 100 run season.
A player's [projected] numbers are adjusted to the park and league context associated with the team listed at the top of the forecast page. Park factors are based on a three-year average over the period [2002-2004], except for teams that have changed ballparks.
PECOTA forecasts playing time (plate appearances) in addition to a player's rate statistics. These forecasts are based on a player's previous record of performance, and the comparable player data, and do not incorporate any additional information about managerial decisions.
For Pitchers:
[The PETCOA] Forecast is a representation of the pitcher's expected performance in the upcoming season at various levels of probability. For example, if a pitcher's 75th percentile ERA forecast is 3.52, this indicates that he has a 75% chance to post an ERA of 3.52 or higher, and a 25% chance to post an ERA less than 3.52. Higher percentiles indicate more favorable outcomes.
PECOTA runs a series of regressions within the set of comparable data in order to estimate how changes in peripheral statistics are related to changes in ERA. For example, if it first estimates that Woody Williams will produce an ERA of 4.29 next year, it then tries to determine what strikeout rate, walk rate, and so on are most likely to be associated with a 4.29 ERA season.
A player's [projected] numbers are adjusted to the park and league context for the team listed at the top of the forecast page. Park factors are based on a three-year average over the period [2002-2004], except for teams that have changed ballparks. In addition, the pitcher forecasts include an adjustment for team defense which affects the pitcher's H/BIP.
PECOTA forecasts playing time (games and innings pitched) in addition to a player's rate statistics. These forecasts are based on a player's previous record of performance, and do not incorporate any additional information about managerial decisions.
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