Archive for Meta Analysis

In lieu of a chat today, we’ll answer some questions over the course of the afternoon. This will allow us to answer more detailed questions, so make sure you give us the relevant information in your comment so we can help you. The RotoGraphs staff is here to help!

Oh, and ottoneu arbitration voting ends at midnight ET on 10/31 so remember that and ask us about those votes if you want.

On Saturday, I took a look at the five hitters whose HR/FB ratios increased the most from 2010 to 2011. This time I switch it up to check out the bottom of the list, those hitters who experienced the largest declines.

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Trying to decipher which breakouts are for real, or at least repeatable the following year, and which are mostly a fluke is one of the more enjoyable tasks during the off-season. Unfortunately, it is very difficult to be truly confident in our guesses, no matter how much supporting data we could find that validates our side. Of course, the easiest thing to do is just predict that every surger will regress. And more times than not, you will be right. But where’s the fun in that? Below are the 5 hitters who experienced the largest HR/FB ratio jumps from 2010. Note that only qualified hitters each year were looked at.

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Hey let’s talk about everything! Baseball, ugliness, burgers, beverages.

Pitchers tend to induce different types of batted balls. Some are fly ball pitchers. Others induce ground balls. While there are always pitchers at the extremes, a few pitchers go beyond the norms on a yearly basis. Today, I am looking at pitchers whose 2011 batted ball data was outside the normal range of values.

To get the extreme baselines, I took the the top and bottom values for a pitcher with over 400 IP total over the past 3 years. Here is a look at some pitchers that may be in store for some batted ball corrections in 2012

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With the core background work done on my hitter evaluations, I have decided to apply the process to second basemen for 2012. This ranking is based off of all player’s stats given the same number of PA. This a look to see which players are the most talented. You can follow the process with this spreadsheet.

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In my first two parts of this series, I looked at the stats to be examined when evaluating hitters and projecting Runs and RBIs. Today, I am going to take a look at projecting plate appearanes (PAs) and stolen bases (SBs).

Plate Appearances

With projections, I find the most error and room for improvement is with playing time. An owner needs to have a hitter playing and accumulating as many PAs as possible. The more PAs, the more counting stats they can hope to generate.

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In my last post, I looked at how often various categories are used in fantasy leagues and which core stats are used to predict them. Today, I am using those stats to predict Runs and RBIs

Run and RBI generation, except with home runs, require other players to either be on base or drive the player home. I ran many regressions and adjusted formulas using the inputs from my last article. I used some stats that weren’t listed (ISO, SLG, Spd). After many attempts, I came up with the following simple equation for projecting a player’s Run and RBI production:

Runs or RBI’s/PA = (AVG * 0.330 + BB% * 0.187 + HR% * 0.560)(yearly constant)

r-squared of 0.75 for 2011
yearly constant = 1 for 2012 for now. It will change depending if the run scoring environment changes.

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I stated a while back that I will be working on a method to predict and evaluate player’s fantasy stats. I will be using both the player’s talent and outside factors and will also combine several data points to get the player’s final value. I will try to keep the explanation as simple as possible and let me know if you have any questions. Let’s start with hitters and once done with them, move onto the pitchers.

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Prior to the All-Star break, four RotoGraphs writers — Eno Sarris, Jeff Zimmerman, Howard Bender and me — engaged in the just-for-fun activity of drafting Pick Six-style teams, with the pool of players limited to those available in 10% or less in ESPN leagues (at the time of the draft).

Given those parameters, the exercise proved to be challenging, but if you paid attention to our picks, you may have managed to snag a useful fantasy player or three off the waiver wire — no matter what kind of league you play in.

I took the temperature of our picks back in August, but now that the season is finished, let’s tally up the scoring to get the final results. And while we’re at it, we’ll rank the players based on their fantasy impact in 2012.

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