June 19, 2013
THT Essentials:
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Saturday, March 31, 2012
How to estimate playing time
Posted by Dave Studeman
The real key to forecasting performance in any year is getting a player's playing time right. Sure, averages and percentages rise and fall, but they remain outside our best efforts to make them more predictable. Playing time is tough to predict too, but something can be done here. This is where you come in.
People who follow teams have real insight into who is most likely to play where. So Tangotiger has started his annual Playing Time Survey to get your input. Just head on over to his site, pick your favorite team, and enter your best guess as to who is going to play how often during the season. This is a community project; the results are available to all. So please help by contributing. It will just take a couple of minutes.
Dave was called a "national treasure" by Rob Neyer. Seriously. Comments about this article can be sent to him through the miracle of e-mail.
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Hey, Dave,
There’s a theory in science-fiction that polling very large numbers of people results in remarkably accurate estimates. Some questions (How much did a WW II battleship cost?) draw absurb answers ($50,000), but the final result is likely to be close to true.
I don’t endorse the theory, but it seems plausible.
Questions:
Have you heard of this theory? Or am I just out of my skull? (I can’t cite a source, but I think I’ve read it in a couple places, maybe called The Delphi Theory.)
Do experts do better at prognostication than semi-random, very large (on the order of millions), samples? (I would expect experts to do better than random people on questions of the past (or present), but maybe not better on the future. E.g., an expert would know a battleship cost $4,000,000 in 1935, but might be way low or high on predicting what it would cost to build one in 2035.)