Archive for Meta Analysis

Spin Rate: Batted Balls Missing Component

Quite a bit has been written about batted ball data the past few seasons since the information has become publicly available. Fantasy owners have taken notice and are trying to find that next hitter who is raising his launch angle to be part of the “Flyball Revolution”. One major issue which is not being publicly discussed is the major effects backspin has on the ball. By knowing a hit’s spin rate, some of the anomalies seen between launch angle and exit velocity can be explained. The spin rate is a major batted ball component but is generally an unknown factor.

The importance of batted ball spin comes down to this simple table and explanation by Dr. Alan Nathan in a piece he wrote at the Hardball Times.

Finally, I want to take advantage of the fact that we have an aerodynamic model that accounts for most of the features of the data to investigate how flyball distance depends on the amount of backspin, here for a fixed exit speed of 103 mph and launch angle of 27 degrees. The results are given in the table below. They show that distance increases rapidly as the backspin increases from zero but eventually saturates, with very little gain in distance for spin rates exceeding about 1,500 rpm. The reason for the saturation is partly because air drag increases with increasing spin, essentially canceling the increase in lift.

Same launch angle. Same exit velocity. And the ball travels an additional 64 feet of distance because of backspin. Simply, how is a factor which can add an additional 60+ feet in travel distance not be part of our analysis?

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10 HR/FB Rate Surgers for 2018

It’s time to unveil the list of 10 fantasy relevant hitters whose 2017 xHR/FB rates most exceeded their actual HR/FB rate marks. I use my Statcast-fueled xHR/FB rate equation to determine which hitters could enjoy a spike in HR/FB rate in 2018. Of course, this all assumes the hitter posts similar marks in the components of the xHR/FB rate metric — Brls/BBE, along with fly ball pull and opposite field percentages. All xHR/FB rates are the park-adjusted versions.

This list isn’t necessarily a sleeper list, unless your leaguemates are expecting a 2018 HR/FB rate like 2017 for the player. Rather, it’s simply a list of hitters with a better than average chance of enjoying an increase in HR/FB rate.

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Seven Surprising 2017 Brls/BBE Bottom Dwellers

Let’s shift back to the bottom of the Statcast leaderboard and discuss seven names you might be surprised to find down there. The surprise won’t be driven by a bunch of guys who just posted 20% HR/FB rates yet don’t have the barrels to explain such results, but rather one of “whoa, his power really did dry up in 2017, what happened?!”.

In 2017, league average Brls/BBE was 6.4%, while the median mark was 5.3%. The median is much lower because it includes the many hitters who recorded few plate appearances and batted ball events, a group which likely posted lower Brls/BBE marks. After all, more power equals more playing time, all else being equal. The average is weighted and so the 437 batted ball events from Giancarlo Stanton, who posted a 17.4% Brls/BBE is going to pull up that mark, but ends up counting the same as the 16 batted ball events from Brett Eibner, who posted a slightly better 18.8% Brls/BBE.

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Behavioral Economics & Fantasy Baseball: An Introduction

Gazing right back at you is someone who relentlessly falls prey to the law of small numbers; to hindsight bias; to over-reaction; to narrow framing; to mental accounting; to status-quo bias; to the inability to evaluate your own future regret; and, most of all, to overconfidence. – Jason Zweig

I’ve been digesting all the literature on behavioral economics I can find as I stated in an article earlier this week. This focus area has gotten quite a bit of attention in the past few years with Richard Thaler and Daniel Kahneman each winning the Nobel Prize in economics for their work in this field. Thaler (Misbehaving) and Kahneman (Thinking Fast and Slow) have each written must-read books on the subject. I recommend both books, they are loaded with information. To give a brief induction into the various behavioral economic concepts and their application to fantasy baseball, I will utilize a speech given by the Wall Street Journal’s Jason Zweig on the subject.

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Six 2018 Home Run Sleepers

Let’s continue diving into the Statcast leaderboard, sticking with my favorite metric, Brls/BBE (barrels per batted ball event). While it’s no surprise to find Aaron Judge atop the leaderboard, followed by Joey Gallo, and J.D. Martinez, there are other names that do surprise and provide actionable information. So let’s peruse the top 50 hitters (there are 540 players on the list, including pitchers, as the board simply includes everyone with at least 30 batted ball events) sorted by Brls/BBE and discuss six legit sleepers for home runs in 2018.

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2018 Research Projects: Known and Unknown

Fantasy baseball slowly evolves and with the start of 2018, I’m going to focus on some topics in which savvy and unconventional owners could utilize against their competition. Some of these topics I’ve been contemplating and researching for a while, others are still just dust in the air. The following contains some ideas I hope to have a better understanding of by the year’s end and frame it so owners and utilize it. I’m not the only source of ideas. I’m 100% positive I’ve missed some simple useful topics and would love to research those in presented in the comments.

StatCast Batted Ball Data

As a baseball community, we’ve been slow to adapt and utilize StatCast batted ball information. Besides major league baseball employees, no one is leading the change. Part of the problem is having an easy to access database for everyone to use. That barrier is being removed as tools like Bill Petti’s baseball-r package can be used to help scrape the needed information from Baseball Savant.

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The 2017 Brls/BBE Decliners

Yesterday, I shared 19 hitters whose Brls/BBE marks spiked from 2016 to 2017. A surge in this metric usually coincides with a jump in HR/FB rate, and sure enough, 18 of the 19 batters did enjoy an increase. Now let’s check in on the hitters who suffered a decline in their Brls/BBE marks. We shall assume that each of their HR/FB rates also declined. Was this actually the case?

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Exploiting Middle Infield Bias

“… pros were more likely to ride a wave of irrational exuberance than to fight it. One reason is that it is risky to be a contrarian. ‘Worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally’” – Richard Thaler in Misbehaving

At the root level, fantasy baseball is about acquiring more undervalued assists than your opponents. Everyone wants a first-round talent for a last round price (e.g. Aaron Judge). With teams clamoring to acquire every advantage, they are insistent on wasting away an early draft advantage. In early 2018 drafts I’ve participated in, an early emphasis on middle infielders is inflating their value way beyond their projected production. Is the observation wrong? If so why? If not, how can an owner take advantage of this mispricing?

Note: For this article, I will lump second basemen and shortstops together into one middle infield position. Neither position has more talent than the other and the bottom players will be used to fill a middle infield position.

For those who have recently created mixed-league valuations, positional scarcity doesn’t exist besides with catcher. I use the method outlined in Larry Schechter’s book, Winning Fantasy Baseball to determine my values. I’m not going to go into the process’s exact details but it’s the standard procedure used by fantasy experts to prep for auctions. Even a couple years ago a small amount of positional scarcity existed but a huge influx of good middle infielders has raised the group’s overall talent level up to the other positions.

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Counting Stat Estimator For Hitters On The Move

In leagues with Runs and RBIs as categories, predicting how a player’s mix will change with a new team can be guessing. Some clown at Fantrax yesterday wrote the following:

“As for Headley, his value drops by going to a worse offensive team in a pitcher-friendly park. Part of the decline could be offset by a move up in the lineup since he mainly batted seventh for the Yankees last season.”

It could go up, it could go down, who really knows? While writing the statement, I needed a better answer so I created a couple quick and simple tool. If an owner can estimate a few stats, they can predict changes in plate appearances, Runs, RBI when a hitter moves from one team to another.

The key was to be simple and quick. For simplicity, only the following stats are needed.

  • New likely lineup location
  • Estimate of projected home runs
  • Estimated games played such 150 out of 162 games as a percentage.
  • Estimated Runs scored by a team. Used over on-base percentage because team level runs scored is easier to find and remember.

The estimated runs scored is the toughest value to come up with. I’d just go to FanGraphs team projection page to get a decent idea. Just take that year’s RS/G and multiply it by 162. Another method is to take the previous season value and plug it into the following regression equation:

`RS in Y2` = .575 * `RS in Y1` + 311

The goal is just to get a basic idea of possible changes.

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Miguel Cabrera: Creating a Personal Drafting Plan

The projection systems love Miguel Cabrera. To them, he’s a hitter who performed decent in the first half and struggled in the second half. The projections don’t know that he has two herniated discs in his back. Because of the injury, his wOBA dropped from .339 in the first half to .274 in the 2nd half. Using projections, he’s the 54th highest ranked player but owners have pushed his ADP closer to 100th. It’s time to determine why the disconnect.

It was definitely a tale of two halves for Cabrera.

Miguel Cabrera’s 2017 1st & 2nd Halves
Monthly AVG OBP SLG BABIP BB% K%
1st Half .264 .357 .440 .307 12.1% 20.4%
2nd Half .230 .288 .342 .272 7.4% 21.4%

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