Part IV: Iterations

This is the fourth and final post in a series describing the methodology the Price Guide uses to come up with dollar values for players. The principal explanation can be found in the previous sections: Part I (standard scores), Part II (positional adjustments), and Part III (dollar values).

In Part I on this series, I explained how the first step of creating fantasy baseball values was finding standard scores based on the top 108 players (for our example 12 team league with 9 hitters per team). I also hinted how this presents a bit of a catch-22: We need to know who the top players are before we can rank them. But we need to rank them before we can determine the top players.

The Price Guide’s solution is to perform the valuations iteratively. Each time it processes, it feeds the top players from the previous iteration into the current one. It keeps going through that process until the results from a previous run are identical to the current run. At that point it has found the optimal player pool.

That means that the first time it runs, it assumes that the first 108 players it comes across must be the top players, regardless of how the list is initially sorted. If the list of players is in alphabetical order, the Price Guide will plug in guys like Reggie Abercrombie and (the humorously named) Andy Abad to come up with standard scores.

Even using these guys, the cream rises quickly to the top. Think of it this way: If you’re in a league where Andy Abad gets drafted in the first round, it still makes tons of sense for you to grab Pujols. In fact, Pujols looks even more valuable in this league, because the competition is even further below him than usual.

So after one iteration, the rankings already look decent. The first round players are mostly ranked somewhere in the first round, although at prices that are too high. Things start to drift a little bit after that, but we are definitely a lot closer than at the start.

The second time through, the extreme values it gave to the top tier players are toned down a bit, and the rankings look like something you could bring to a draft without embarrassment. Each successive valuation after that is really just tweaking the draft pool–moving guys up or down a couple of slots, balancing speed and power, switching around some of the bottom of the barrel players. Within 3 to 10 iterations, it has settled on the optimal draft pool.

Anyway, that pretty well sums up the methodology I’m using to come up with fantasy dollar values. Looking back at the posts, I realize that this isn’t the most interesting subject to discuss. However, my purpose for this series is to provide some reference material–not necessarily enjoyable reading. So consider this series as Appendix A sitting somewhere near the back of the Last Player Picked site.

Of course, if you managed to wade through all four parts of this explanation and have any questions or comments, feel free to let me know.


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