And they eventually only gave up 693 runs.

So you were saying, Dirty Water?

It would be a prediction if I had some sort of methdology for figuring out why I’m selecting the stats I’m using in the first place. Or if I had a step where I considered how rule changes might alter RBI totals.

But yah, that’s a definition that people use too- but it’s a pretty junky one since then it’s all purely subjective and application specific.

Secondly, I still disagree with some of what you’re saying… particularly: “CircleChange is correct when he states that if we ask for predictions of what players of teams will do at this point, we will go thru the same process as we do for projections.”

While that may be true, that simply indicates that we’re just slapping the label of “prediction” on a projection. However, I don’t think that makes them the same thing, any more than if I took a 2-D square and labeled it a cube.

By my understanding of how projections seem to be defined versus predictions, a projection takes prior states from the system and attempts to project later states of the system. You’re treating a system as essentially endogenous, maybe with some error sources. So projection is like Projection = f(System History)

I would contend that a prediction is more like: Prediction = g(System History, Exogenous Data, Possible Changes to System). A prediction does not necessarily have to be bound by the prior performance of the system in question. It accepts the possibility of exogenous effects or qualitative shifts in dynamics. In my view, a prediction lifts the assumption that past dynamics remain valid (but may still apply such principles to the degree they are useful). This allows assumptions about dynamics or influences that would not make sense in a pure projection.

For example, if it was announced that all players in the MLB would now play with aluminum bats rather than wood, and superballs instead of cork/- a projection is not going to handle that. With that said, a prediction could still be made. By determining the impact of aluminum bats vs wood bats in other contexts, analogical inferences might be made (ex. aluminum causes 10% longer distance on FB and LD). If I make that adjustment to my estimates of ball distances, I’m not doing a projection.

I’d say that considering the possible impact of new exogenous influences or dynamics is a pretty major shift in process. Even if you end up saying “Oh, well, no major anticipated dynamics/exogenous factor changes this year”- considering that is an extra process step. Even if the outcome is the same, the process isn’t.

Of course, you can play games with what is a prediction and what is a projection by changing the scope of how you define your system versus your externalities- but that’s a whole other issue.

The moral of the story is that I think there are very important differences between predictions and projections with regards to the process (though not necessarily the outcome). There is also a difference in that predictions are implied to be more accurate than “forecasts” or “projections” but that has always seemed pretty subjective to me.

Moreover, the point that Cameron seemed to be making appeared to be that we’re not considering the factors exogenous to the system- even though we know it will happen and will have a driving force. That the projection systems implicitly hold factors constant by omission, because they’re not even addressed as part of the random error. And if we were predicting, we’d have to address in some way why we just hold those constant (i.e. everyone staying on the same teams, etc) as part of the process.

http://rlyw.blogspot.com/2009/04/2009-diamond-mind-projection-blowout.html

http://rlyw.blogspot.com/2009/04/2009-diamond-mind-projection-blowout_01.html

Tough to argue with such a cogent, well-thought out analysis like this. Vazquez is beter than the various starters he’ll replace, but I also doubt he’ll do better than how they performed. I see him matching Wang and Mitre’s 8+ ERA at best.