I think it’s a bit problematic to peg replacement level to a single 12th-best player (in a 12 team league).

For example, suppose that (prior to positional adjustment) the 12th-best SS is worth 3 and the 13th-best SS -2. If you draft the top SS and he gets hurt, he won’t be replaced by the 3, he’ll be replaced by the -2 — provided he’s the only one hurt. If other guys have gotten hurt first, he’ll be replaced by someone possibly much worse than -2.

The general problem is that pegging replacement level to a single player isn’t robust — a small change in the player pool, such as a guy getting hurt or a guy gaining positional eligibility, can change the values by a non-negligible amount.

I think a safer approach would be to average, in some intelligent way, the values of players near replacement. That way the positional adjustment would more closely reflect what one would expect to find on the waiver wire in practice.

I actually take this farther… if the last C has no value, does the second to last c? I actually think that for a player to have any value, they have to be a certain percentage better than replacement level. Your current model assumes that they can gave .001% better than replacement level, but if they are drafted are worth $1.
I probably did not explain my position well, but maybe will get the conversation started.

While I have not found a way to quantify this, I believe that multi eligibility is worth more than a 5% bump up in value. I mention 5% as a starting point for further discusion only.

FYI, I have been doing spreadsheet analysis for fantasy baseball for a decade, and was very pleased to find your site. I would caution about “value traps”, guys who the spreadsheet says are valueable, but whom your gut says are not. Russel Martin comes to mind, as both my spreadsheet, and your price guide, have him valued highly. Nobody who owned him last year would agree. I do understand that we are both using the popular forecaster’s projections. But not you, me, or anyone else who wants to compete this year should really be confident they will get double digit value out of russel martin, regardless of what the spreadsheet says. I would also say this: valuing players (or stocks as I do in real life) is more art than science. The guide can tell me that hanley is worth 39$, but that is merely a guidepost, and I need to overlay my thoughts, ‘the art part’, to adjust this, knowing that the band for his true worth is not exactly $39, but is probably somewhere between 30 and 50. As I have realized over the years, there are always factors I can add into the model, and those factors change the values of players, so clearly we never have a model that incorporates and values everything currently knowable. Our ability to create ‘true’ values for players is just not strong enough (nasa would not be able to get the figures exact, as wall street has not been able to).

Certainly. Once you fill your C spots, the remaining Cs don’t have any advantage over a 1B in a Util role.

You do need separate sets of values – players as position players and players as Util/MI/CI.

The price guide gives values for players at their most useful position, and Util is ranked last.

This is because a players value as a Util is always less than or equal to their value elsewhere because the baseline adjustment is equal to at most the smallest of the positional adjustments.

For half the teams, after each pick I removed the corresponding starter from the settings. For instance, if one of the “Change” teams picked ARod, I changed that team’s league settings to have 1 less starting 3B and regenerated the PG values for that team’s next pick. For the other half (“Static”), I used the static list generated at the beginning of the draft. I used a snake draft, alternating the “Change” teams with the Static teams, choosing the highest $ value player in a needed position remaining for that team.

In Comment 10, I noted that removing a catcher from the settings reduced Martin’s value from 36 to 16 (as he gets projected solely as a 3B). So, I was expecting positions to shoot up and down the list. I didn’t expect, that player’s relative value within a position would change. I expected that if Damon was ranked above Kemp initially, then Damon would always be above Kemp. That wasn’t the case though — those 2 flipped positions; and they were far from isolated cases. (and as Molson comments, it make sense, just requires deeper understanding)

The results of my drafts were not conclusive. The difference between the 1st and 6th team was only 6 place points. Three teams tied for second. The different team kinds alternated in the standings.

I think the primary reasons for this is that all the teams used the Price Guide pricing methodology. If some of the drafters took alternate valuation methodologies (rototimes/sgp/etc), probably would have seen a greater spread.

The original problem I was thinking of is how to choose the generic positions Util and P (and CI/MI). In a mock snake draft, I tried using the price guide values — my algorithm was to choose the highest value player available. Mays has noted that the PG tends to value Catchers higher than other people. My algorithm led me to choose the first catcher, then, not fully understanding that the values presented were for that specific position, I chose the next highest valued player, another catcher (as my util). Had that catcher been valued as a util, he would have been much, much lower.

Instead of the reduced player pool set (as I originally thought), I think a new list is needed — a ranking of all eligible players in each the generic positions. The (snake) draft algorithm would then change from “choose highest $ player from pitchers and hitters” to, “choose highest $ player from pitchers, hitters, and each generic position.” I’m going to see if I can test that hypothesis next.

Take SB. Once the top 3-4 SB guys are taken out, the SD for the stat goes way down and thus a 20 steal guy becomes a lot more valuable than before since there’s a dwindling pool of steals.

Two Price Guide spinoffs I would love to do if I could find the time to do them:

1) An In-Draft Price Guide. Basically, what you mention: a spreadsheet version of the Price Guide that adjusts prices as the draft progresses.

2) An In-Season Price Guide. A tool to display dollar values based on year-to-date stats, preferably right on a person’s league site (i.e. within Yahoo, ESPN, CBS, etc.).