Archive for Meta Analysis

The 2021 draft season may be the most unpredictable one … ever. While several rule changes (e.g. NL DH) can cause some evaluation inconsistencies, the biggest monkey wrench to deal with will be the lack of previous season stats. Projection systems will weight the 60-game 2020 season (37% of a normal season) to historical averages but what are those who don’t use traditional projections systems? Or read or listen to people who don’t care for them in order to create a compelling narrative? It’s time to anchor some historical context around those narratives.

All analyses “should” start with at least some set of weights. For those who start with one, they’ll have an advantage. For those who guess the correct one, they’ll have a huge edge. The issue with setting weights is how to create a short season one that fills all the narratives.

First, most of the players were rushed to get game-ready and were not 100% ready when the season started. So the beginning of the season stats could be used to replicate this ramping up period, but the weather was still warm at the season’s end increasing offensive output. Maybe the entire first month should be ignored with everything in flux. Possibly the last two because that were the 2020 regular season months. played. So, I decided to look into all the possible options including a horrible first attempt.
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This month last year, Connor Kurcon of Six Man Rotation set out to quantify the location aspect of command (or “LRP”). By establishing an accounting system that credited and debited pitchers for changes in ball-strike counts based on the attack zone of and hitter’s disposition (take? swing? ball in play?) for every pitch, he effectively created an alternative to Pitch Value (PVal) that rewards optimal movement through ball-strike counts but with much more pitcher and hitter context.

His findings are as you’d expect: Jacob deGrom and Justin Verlander lead the pack, with Gerrit Cole, Max Scherzer, and Clayton Kershaw not far behind. Other budding aces like Jack Flaherty and Mike Clevinger pepper the list, and some pleasant surprises (such as Brendan McKay, Caleb Smith, and, for those still thirsting, Jake Odorizzi) are scattered throughout as well. Out of the bullpen, newly anointed relief ace Nick Anderson led the pack followed by the underrated Emilio Pagán, breakout reliever Giovanny Gallegos, and others.

Near the end of his post, Kurcon includes a subhead dedicated to Kyle Hendricks where he highlights how Hendricks, widely respected as a command artist, fares lukewarmly by measure of LRP. He then reminds us “LRP doesn’t paint the full picture of command.” True that.

Fortunately, Kurcon has left the door open for me to tie up loose ends with find Gs I’ve been meaning to write up for a couple of months now. Never fear, Hendricks is the command artist we know and love — it’s just that he relies heavily on incurring contact in optimal pitch locations. It is a needle very few pitchers can thread, but Hendricks does it masterfully.

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I’m as competitive as hell. I hate not winning. Simply…

So is almost everyone else. While many people search for an edge, they aren’t looking into harmful habits that erode that edge. All the gains an owner could get from researching the best players can be lost if he constantly overspends rostering them. Many times what a person considers to be an edge can actually be a hindrance. Here are several ideas that help me back and now that I’ve changed my stance
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To say the least, the 2020 fantasy baseball season will go down as a one-of-kind. A late start led to a 60 game sprint. Seven-inning double-headers. Weeks of rescheduled games because of COVID-19 positive tests. The National League DH. Twenty-eight-man rosters in September. Each of these on its own would fill the headlines. With the changes coming all at once, they felt overwhelming. I’m hoping to calm everyone if any and hopefully not all of the changes happen again. Here is some advice on how to handle the changes.

The help divided up into league setting and individual manager focus. While I inserted plenty of my own advice, I wanted to make sure as many people as possible contributed so Tweeted out and asked during my chat for input.
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Yesterday, I identified and discussed the qualified hitters who had raised their fly ball rates (FB%) the most versus last season. All else being equal, more fly balls leads to more home runs. Fantasy owners like home runs. Unfortunately, not every hitter has decided they wanted to participate in the fly ball revolution. So let’s check out the hitters who have sadly departed and experienced the biggest declines in FB% versus last season. This could help explain disappointing home run totals so far.

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I think by now, we’re all familiar with the Statcast metric barrels. If not, Statcast defines it as thus:

The Barrel classification is assigned to batted-ball events whose comparable hit types (in terms of exit velocity and launch angle) have led to a minimum .500 batting average and 1.500 slugging percentage since Statcast was implemented Major League wide in 2015.

To be Barreled, a batted ball requires an exit velocity of at least 98 mph. At that speed, balls struck with a launch angle between 26-30 degrees always garner Barreled classification. For every mph over 98, the range of launch angles expands.

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Some previous research, including my own, has pointed to changes in Sprint Speed being a sign a player’s talent has changed. I decided to investigate changes from 2019 to 2020 to find who could be struggling and why. Many hitters are experiencing a drop and just a few are up.

In some way, the following information should be picked apart for a longer research article with some miraculous/groundbreaking/made-up claim that batters came to this season out of shape and that is why offensive production is down. I don’t care. All I want to know is who are the hitters who could be breaking out or down. Figuring out why is for the offseason. It’s now time to wins leagues.
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I spend a lot of time bothering Connor Kurcon. He’s a smart dude with a certain intuition about baseball and a certain ability to apply that intuition to produce tangible results that invariably reflect his hypotheses. He devised Predictive Classified Run Average (pCRA), an ERA estimator that outperforms the big three (FIP, xFIP, and SIERA). He also created a dynamic hard-hit rate which, to me, was astoundingly clever and a superior accomplishment to pCRA (although maybe he disagrees).

Anyway, like I said, I bother him a lot, he tolerates me, we bounce ideas off each other. The journey starts there, with my incessant annoyance of him, but also it starts here, with this Tom Tango axiom: exit velocity (EV) is the primary predictive element of hitter performance (as measured by weighted on-base average on contact, aka wOBAcon) — significantly more so than launch angle (LA). Some of the inner machinations of Tango’s mind:

That's not that interesting. What I was more interested is its relationship to NEXT YEAR's wOBA.

Not surprisingly, the performance of the 5% hardest batted balls is what indicates talent in the following year, and by a huge amount. If you've been following my barrels thread.. pic.twitter.com/hvLWr0rCSr

— Tangotiger 🍁 (@tangotiger) February 27, 2020

I won’t speak for Kurcon, but I think this finding helped guide his work on the dynamic hard-hit rate. I also think it inspired his foray into replicating this effort for pitchers or, at the very least, his attempts to determine the most predictive element of pitcher performance. Which leads us to this tweet that (spoiler alert) is actually not stupid at all:

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I usually don’t worry about schedule specific details during a regular season since so much can change in a month or two. This season is only going to last a couple of months, so it has some importance. I dug through all of the National League teams trying to find some stretches to stream players. I didn’t find a bunch of one to two-week stretches but I did come to some overarching themes.

I tried to digest as much of the information as possible and I’m sure I’ve missed something obvious. I started the analysis hoping to find a list of week-by-week targets to stream and came away with a new perspective.
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Note: About 95% of this article was finished before the news that MLB is going forward with a 60 game season.  I finished it knowing that more imporant work needs to be done. This series now comes to an abrupt end and I will return to the series once the season is over one way or the other.

I’m continuing my quest to predict pitcher injuries and their effects as best as possible. I started grinding through the process last week and found through some additional work that injuries from just the past two seasons drag down production. Today, I’m going to go over some other possible other injury causes and provide updated injury ranks.

While I’ve done quite a bit of my own work on pitcher injuries, I decided to scour the web come up with some new ideas. Here are some possible ideas ranked by how I’d like to investigate them.
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