In my last column, , I provided a general guideline for creating a cheat sheet. In this column, I expand on that by exploring how to generate dollar values for each player.
One way to get dollar values for each player is to use a pre-made cheat sheet such as those created by Baseball HQ, Baseball Prospectus Player Forecast Manager (PFM), ESPN, and Rotowire (note: Baseball HQ and PFM allow user customization).
Another way to get dollar values is by creating your own cheat sheet. If you have the time, I would recommend using this method because it allows you to customize your cheat sheet to your league’s settings.
The central challenge of creating a cheat sheet is determining the value of different categories. How much is one stolen base worth compared to one home run? There are two ways to calculate this. One way is to use the statistical concept of ; the other way is to use Marginal Standings Gain Points (SGPs).
If you are interested in using the z-scores methodology, this is a good read. If you are interested in using marginal SGPs, Art McGee’s book “” is a good read. As the title of the book suggests, SGPs is specific to roto leagues, and while z-scores can theoretically be used for any league, I believe, that like the SGPs method, it is best suited for roto leagues. Nonetheless, both methods can still provide a solid foundation for those in head to head leagues.
In the past, I’ve mentioned that projection systems often struggle to accurately predict players with limited pro-ball experience and players coming back from injury. It follows that cheat sheet values based on those projections contain the same shortcomings, typically by undervaluing those players. A way around this is to complement your projection based cheat sheet with a more subjective cheat sheet, such as those created by ESPN, Baseball HQ, or Rotowire. Typically those projections will be more bullish on prospects and talented players coming back from injury.
With any projection based cheat sheet, there will always be players whose value “looks wrong”, and it can be tempting to ignore those values. However, unless there is a clear reason why a projection system would mishandle a player, I encourage you to trust the projection based values.
While a cheat sheet is a necessary tool for the draft, it loses some accuracy once the draft begins. This is because a player’s value to your team is dependent on the players you already have. For example, if you own , will hold less value to you because owning Crawford gives you a head start in winning stolen bases, and as a result, you have lower remaining marginal gains in SB than in other categories.
Ideally, you will have a program or method capable of producing real-time player values based on who’s on your team and who’s available to be drafted. One program capable of doing this is PFM. If you choose to not use a program like PFM, you should at least set target levels for each category (e.g. 250 homeruns) and keep track of how close you are to those levels during the draft. You should also keep track of who remains in the player pool. If you follow these steps, you have a good chance of coming out of the draft with a team you like.