Maximizing your use of THTForecasts

Many of you are probably very well aware of how to use spreadsheets. Maybe, you’ve even been using them for fantasy baseball purposes. Until recently, I was not one of those people. This article is for those poor, unguided souls among us.

If you’re like me circa two weeks ago, you have no idea what you’re missing.

THT Forecasts (or Oliver, as it’s known) is obviously a great tool. It not only offers you a prediction of how almost every player in affiliated baseball will do, but it goes a step further and continues to estimate their performances as the season progresses.

But Oliver, is only as good as you allow it to be. For instance, Oliver is designed to predict how players will perform in specific statistical areas. It isn’t designed to specifically tell you which player best suits your fantasy baseball needs. That’s where downloading the spreadsheets comes in so handy. Think of Oliver as your fishing pole, what follows is a lesson on fishing.

The best thing about spreadsheets, as I’ve learned, is the amount of customization and calculation it allows the user to do with minimal effort and some pretty basic skills. From a fantasy baseball perspective, this essentially allows you to eliminate the noise and focus on how your league values players.

I’m in two leagues. One of them is points-based, with players receiving four points for home runs, one point for singles, etc. What spreadsheets allow me to do is to create a formula that gives me a predicted point value for every player. This kind of analysis gives me some obvious results (Albert Pujols and Hanley Ramirez are expected to be the two most productive players), but also yields some surprises (Oliver says Ben Zobrist is expected to be the 14th best offensive player and Cody Ross is predicted to be in the top 50). The analysis of pitchers yielded similar results with Tim Lincecum predictably topping the charts and Max Scherzer shooting up to No. 11.

My other league is head-to-head where each category counts as one “game” and we play 14 “games” against the same opponent every week. In leagues such as this, it’s much harder to get a clear picture of what to look for in players. Usually, I settle on judging every player by a stat like OPS, which even though it’s not one of the categories we use, does give a good overall picture of how a player is expected to perform. Using spreadsheets, I can devise a much more complicated system to rank players. In my case, the one I liked best was (Runs+RBIs+Home runs+Stolen bases) x (On-base percentage+Batting average). That analysis has the usual suspects at the top of the list with someone like Adam Dunn finishing a surprising 15th.

For pitchers, I created a formula which only factors in K/9, BB/9, ERA and IP that looks like this: ((K9/BB9)/ERA)xIP. This ranking system puts Dan Haren at the top of list, which shouldn’t come as much of a surprise given his historic performances in those areas. Of a much bigger surprise is Colby Lewis coming in at No. 2, Stephen Strasburg ranking No. 14, Kevin Slowey at No. 15 and teammate Scott Baker ranking 23rd. Obviously, this doesn’t mean you should make Lewis the second pitcher drafted in your league, but it does highlight an some easily overlooked players that Oliver absolutely loves.

I’m hoping that what you take away from this little exercise is not so much my specific formulas (I’m sure there are plenty of holes to be poked in those), but the general idea that Oliver can be your playground if you just take a little time to play around with spreadsheets. Oliver is a great tool, but it’s only as good as the person using it.

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  1. fjs said...

    It would really help me in my league of you had saves on the stats. I have to find a new closer after Wood hurt went down (don’t ask me why I have Wood in the first place—I know it was a gamble but I picked a closer late.)

    WHiP would be nice too but we can calculate that from the other data.

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