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Setting Up Spreadsheets (Part 2)

A guide to setting up spreadsheets for draft preparation. This time, a look at pitchers.


Everyone has a process for preparing for a draft. Some people print out cheat sheets like they're possessed by Hexxus. Others buy more magazines than a 15 year-old pop star wannabe. Pages of stats, sleepers, busts and top prospects get riddled with highlighter marks and underlines and notes. Some people focus on the categories that count for points in their leagues, while others prefer to look more in depth. Some listen to podcasts and read internet articles. And some just go on gut, what they've seen on highlights or even name value.

The first thing I do when I'm ready to start preparing for the next season is set up spreadsheets. These spreadsheets help me because I'm able to have all of the stats that I use to evaluate players right in one spot. I'm able to sort and compare stats, perform analysis and what-if scenarios and rank players easily. I'm going to explain how I set up my hitters spreadsheets in hopes that you can use them as a template to help you prepare for your draft.

First, allows users to customize reports with any and all of the stats that are available on their website. If you're not familiar with FanGraphs, I suggest you consider getting familiar with FanGraphs. Check out the Custom Leaderboards the site offers. You can select the player pool(s) you want to include, filter on several criteria and pick and format the stats you want to evaluate. After you've selected your player pool and the stats you want to include in your file, you can export the table to Microsoft Excel to further manipulate it.

You may find it helpful to group the statistics into categories and list them across the top. This makes comparing and ranking easy as you are able to view stats next to each other and move them about freely in your workbook. Here's how I group the stats:

Standard (SP)








Standard (RP)









These are the standard counting stats that most people look at when discussing baseball statistics. Games Started are used for starters rather than Games simply to differentiate and players that may have worked out of the bullpen as well. Innings Pitched is very important because the more innings a pitcher throws, the larger the effect. While pitcher wins and losses are difficult to predict and aren't always indicative of a pitchers performance or skill level, they are used in most fantasy formats. If they count for points, we need to pay attention to them somewhat. Similarly, there are improved metrics to determine a pitcher's performance but ERA and WHIP are still used in many leagues. These "Standards" are the stats that traditional leagues use for scoring and, thus, they are the statistics we attempt to predict.

Run Prevention




I call this group "Run Prevention" because they show us how well a pitcher does keeping runners off the bases and if runners aren't on base, they can't score. I like K% and BB% better than K/9 and BB/9 because they show a pitcher's performance against each batter faced rather than just in terms of innings. For example, if two pitchers both strikeout two hitters in an inning but Pitcher A walks two batters and gives up a hit while Pitcher B goes 1-2-3, who was the better pitcher? They both have a K/9 of 18.0, but Pitcher A struck out 33% of the batters he faced whereas Pitcher B struck out 67%. Swinging Strike Percentage is the total number of pitches at which a batter swings. A pitcher with a high SwSt% generates a lot of swings and misses.

Δ Expectations/Results







This is always the most interest group of statistics I pull in the offseason. These metrics help us determine what pitcher's numbers should have looked like and gives some insight to why expectations may not align with results. They are not generally used as predictive tools but they can be helpful when evaluating a player's numbers and they have shown better predictive abilities than ERA. As I touched on in the hitters' portion of this piece, BABIP stands for Batting Average on Balls In Play and can help explain a pitcher's ERA. The league average BABIP for pitchers usually sits between .290 and .300 but it's important to look at a player's individual career BABIP when talking about regression because some players may be able to influence their BABIPs more than others. For instance, strikeout pitchers usually have lower BABIPs because they are able to generate weaker contact. Left On Base percentage or strand rate can also tell us something about why a pitcher's ERA was what it was. Pitchers who allow more runners to score (lower LOB%) will have higher ERAs than those who are able to "strand" those runners. League average is about 72% so any player with a LOB% that varies greatly from that will probably regress some in the future and see his ERA affected. Much like LOB%, a pitcher's HR/FB rate will usually come in around league average and, if not, it's generally safe to expect it come in close the following year. Some pitchers, such as ground ball pitchers who do not allow many fly balls or pitchers who pitch in hitter-friendly ballparks, will have higher HR/FB ratios than others. FIP or Fielder Independent Pitching is an ERA estimator that takes into account only what the pitcher can control - strikeouts, walks, hit batters and home runs. It assumes that all other variables such are league average. xFIP takes FIP a step further and tries to estimate how many home runs a pitcher should have allowed as opposed to how many he actually allowed. This stabilizes the metric because home run rates can be volatile. Lastly, SIERA refines this metric even more by taking batted balls into account as well as the fact that some pitchers are able to control the hits and runs they allow. Each of these estimators tells us a little something different and I encourage you to research them further.

Batted Ball




Batted Ball data is a very simple tool to use when looking at pitchers. Pitchers who are able to keep the ball on the ground are less homer-prone than fly ball pitchers and also allow less extra base hits. This usually leads to a lower ERA however it should not be used in a vacuum. For instance ground ball pitchers Doug Fister and Rick Porcello were hurt last year by the Tigers terrible infield defense whereas Jason Vargas stands to gain some value as a fly ball guy in a pitcher friendly park with one of the best outfield defenses in the league. Not all pitchers can be categorized as either a ground ball or fly ball pitcher but it's important to know their tendencies. Also, LD% is important because line drives turn into hits more than other batted ball types and a high LD% may indicate reduced effectiveness of a pitcher's pitchers and/or velocity.

Again, keep in mind that everyone has their own ways of evaluating players and the preference for certain statistics is what makes fantasy baseball fun. If everyone looked at the same stats and felt the same way about them, it would be very difficult to make transactions or to hold an auction. These are the statistics I use and the way I use them. Use them as a reference for setting up your spreadsheet with the stats you like and that you find most helpful. Hopefully, this helps some of you prepare and I would love to hear any suggestions you may have or any feedback about your draft/offseason prep.