Archive for Meta Analysis

One might argue that xFIP is slightly misaligned. One might make that argument in blog form, on the website FanGraphs, today, here, now.

One only might argue that xFIP is slightly misaligned because xFIP is commonly understood to serve a purpose distinct from FIP. FIP, aka Fielding Independent Pitching, is calculated as a function of strikeouts, walks, and home runs — that is, outcomes over which fielders bear no influence. The equation that underpins FIP is derived from a linear regression equation intended to resemble ERA, for ease of interpretation. Because it is based exclusively on outcomes, its purpose is more descriptive than predictive. In other word, it finds greater purpose describing what should have happened but not necessarily what will happen.

xFIP, on the other hand, seeks to achieve the inverse. A large swath of evidence exists to suggest home run-to-fly ball rate (HR/FB) for pitchers is incredibly noisy season to season. Sure, certain pitchers might anecdotally buck the norm — apparently, Michael Pineda was born to be a cafeteria lunch lady, serving up meatballs and taters — but, by and large, HR/FB is a fool’s errand to predict. Accordingly, xFIP replaced home runs with expected home runs, by way of multiplying the number of fly balls allowed by a pitcher by the league-average HR/FB, thereby normalizing home run damage, making it, in theory, a better descriptor (and perhaps a better predictor) of pitcher performance over time.

And therein lies the rub, although, if you missed it, you mustn’t be blamed.

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A while back, I brought forward my thoughts on being 100% transparent about my weekly player acquisitions. The article started many discussions, but my thoughts kept coming back to one point. Does it matter that I have some skin in the game? I lucked into a position to provide fantasy content, does it matter if my ideas are successful when there is quite a bit on the line?

Note. For this article, I’ll use tout in place of an industry expert for consistency’s sake. Also, for the game’s participants, I will use owners.

I felt every tout should have some skin in the game and let their results do some of the talking. Some touts may disagree on this take, but I needed to find out and joined a few NFBC leagues. Besides just rostering a team, I felt I needed to be competitive.

Some of this belief may come from my own insecurities. I know I’m not close to the most entertaining personality, so I think my results may give me credibility. I have no idea if this is true.

Part of the belief comes from Ray Dalio’s book, Principles: Life and Work. In one section he states (p. 376):

“Remember that believable opinions are most likely to come from people 1) who have successfully accomplished the thing in question three times and 2) who have great explanations of the cause-effect relationships that lead them to the conclusions.”

So, do I need to be successful in all formats for others to believe me? So many questions.

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Yesterday, I shared and discussed the hitters who were leading in barrels per fly ball + line drive rate. Let’s now take a peek at the bottom dwellers. Of course, there are going to be your typical suspects, but there are some names that are surprising.

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With about a quarter of the season now in the books, let’s dive into some Statcast data. We know that power could ebb and flow each month and we have witnessed time and time again a hitter whose power is down early, but ends up going absolutely bonkers at some point and making up for the slow start. One of the best, most easily calculable metrics is barrels per fly ball + line drive rate. The problem with the barrels per batted ball event on the Statcast leaderboard is that it counts all batted ball types. It therefore ends up punishing ground ball hitters and doubly benefiting fly ball hitters. While that’s fine if you want to project isolated slugging, it’s a flawed metric if we only care about HR/FB rate. Barrels per plate appearance is even worse, as batters are now punished for walks and strikeouts, as those particular times to the plate failed to result in a barrel…well, duh! So Barrels/FB+LD it is.

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On Tuesday, I identified and discussed the hitters who have enjoyed the largest spikes in fly ball rate, firmly entrenching them as new or more senior members of the fly ball revolution. Today, let’s find out which hitters have departed the revolution as their fly ball rates have plummeted.

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I’ve been struggling this fantasy season when it comes to providing my best possible content. The root cause is that I’ve put more of my own skin in the game by joining a couple of NFBC leagues. Other owners deal with the same issue. For example, I had the following Twitter conversation this past weekend.

In a 15-team league, how much are you both bidding on Karter Kieboom?

😉

— Jeff Zimmerman (@jeffwzimmerman) April 28, 2019

In all fairness, it’s a legit question coming into the weekend’s FAAB period. Carter Kieboom just got promoted and bids were going to be high for him. What got my request denied was that both Al (in Tout Wars) and Matt (NFBC Main Event) are in 15-team leagues with me. If someone else would have asked the question, would they have given an honest answer? Maybe. Would I take their honest answer and use it against them? Maybe.

I never thought others would steal my suggestion to use against me in my leagues until last season. In The Great Fantasy Baseball Invitational, I had a strong feeling two owners checked out my Tout Wars bids which ran FAAB on Sunday at noon. There was plenty of time for the owners to analyze my bids before the evening bids ran. Every week the same two owners beat me out on each of my sleeper picks. It got a little annoying.

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Yesterday, I calculated my xHR/FB rate equation to identify and discuss 11 hitters who have most underperformed their xHR/FB rate marks. Today, I’ll look at the overperformers.

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With about a month of the season in the books, it’s time to start calculating my various xMetrics. We’ll start by calculating hitter xHR/FB rate and comparing it to his actual mark. Today, I’ll look at hitters who have most underperformed their xHR/FB rates, suggesting significant upside over the rest of the season assuming they sustain such underlying skills. In an attempt to reduce really small sample size weirdness, only batters who have hit at least 20 fly balls will be listed and discussed.

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On Tuesday, I shared some early Statcast statistic trends and compared them with historical marks going back to 2015. Unfortunately, I compared April 2019 numbers to full season marks from previous seasons, which wasn’t exactly apples to apples. I have corrected that error and spent some time collecting data only through the end of April for all previous seasons. So let’s try this again.

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Last Thursday, I discussed the early 2019 hitting trends and yesterday, I hopped over to the pitching trends. Today, I’ll return to the hitting trends, but this time from our good friend Statcast. With data going back to 2015, we now have a pretty good picture of what has been in the past and what is happening now.

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