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I'd like to run a small experiment. There are many systems for projecting a baseball player's future production. Most of these are regression based. One that's a little bit different is Tom Tango's Fan projections, which asks fans of each team to rate the players they watch every day, with the hope that en masse, we fans are pretty smart.
I'd like to try a slightly different approach by incorporating human intelligence and intuition into the computer models. When I read The Signal and the Noise, by Nate Silver, I was struck by the chapter on weather predictions. Modern weather predictions aren't simply a weighted average of different computer models. Instead, expert humans are tasked with manually making small adjustments to the models' output. The result is more accurate than either human or computer alone.
I've gone ahead and made a spreadsheet with a separate sheet for every team in the American League East. You can download it here: AL East Cyborg Projections. It includes every player likely to get significant playing time in the second half of the season, along with the ZiPS RoS projection for their AVG, OBP, SLG, and wOBA. The human adjustment column is a dropdown box that allows you to adjust the wOBA projection up or down, by 10%, 5%, 2.5%, or not at all.
So download the spreadsheet, make your adjustments, and email it back to me (you can find my email by clicking on my name). Fill in as many of the teams as you want, but make sure to let me know what team you're a fan of.
I know there's a more elegant way to do this, but I haven't gotten it to work well as any type of survey form yet. I'm open to suggestions of a better way to present it in the future. And if the response is good, I'll expand this experiment to include other divisions as well.
Thanks a bunch, everyone.