Yesterday, I discussed seven of last year’s breakouts and concluded with a verdict on whether I expect each to hold onto at least 80% of their 2018 end of season (EOS) dollar value this year. Today, I will discuss nine of 2018’s busts and conclude each blurb with a decision on whether they are likely to rebound.
A year ago during Fantasy Baseball Week at The Hardball Times, I researched whether last season’s breakouts were solid investments the following year. Spoiler alert: they are actually terrible investments. Of course, that’s as a group. That means that not every breakout from the previous season is going to fall flat the following year. So let’s discuss some of the big breakouts from 2018 and decide whether each ends up as part of the poor investment bust group or they hold onto their gains.
It’s Pod Projections time again, as the 2019 forecasts are now available and its forecasted player population keeps growing! As usual, I’ll dive into my projection methodology (detailed in Projecting X 2.0) by sharing my process on several hitters and pitchers.
2019 Pod Projection Index
Yusei Kikuchi
Yesterday, I compared my xBABIP to actual BABIP to identify eight hitters with significant BABIP upside this season. Today, I’ll check in on six of the biggest xBABIP outperformers from 2018. These guys are at serious risk of dramatic BABIP downside, which would pull down their batting averages without an improvement in strikeout rate and/or jump in home run rate.
While my xBABIP equation wasn’t developed to serve as a next season projection, you could certainly use it as a historical guide, just the way you would normally review actual BABIP marks. That’s precisely what I do to formulate my Pod Projections. One of the various ways to utilize xBABIP is to compare the hitter’s mark to his actual mark to determine how “real” the result was. Today, I’ll identify and discuss eight fantasy relevant hitters who posted xBABIP marks significantly higher than their actual marks, suggesting upside this season if they are able to maintain those underlying skills.
Every season, there’s another can’t-miss top prospect. This year, that honor has been bestowed upon Vladimir Guerrero Jr., who ranked third on last year’s list. Not only does he find himself atop the 2019 mountain, but he’s the only prospect graced with a 70 (out of 80) Future Value grade, which equates to a 5.0 to 7.0 WAR and a top 10 overall player. That’s pretty incredible. Essentially, Guerrero is expected to be elite, a near surefire superstar, and the hype has predictably spread to fantasy leagues.
Yesterday, I compared batter HR/FB rates to my xHR/FB rates to identify nine hitters who posted xHR/FB rates significantly higher than their actual marks, suggesting upside this season if they are able to maintain those underlying skills. Today, I’ll check in on those hitters on the opposite end of the spectrum, with a list of six batters who overperformed their xHR/FB rates most. If the underlying skills driving the xHR/FB rates stick in 2019, these hitters are at serious risk of HR/FB rate regression.
While my xHR/FB rate equation wasn’t developed to serve as a next season projection, you could certainly use it as a historical guide, just the way you would normally review actual HR/FB rate. That’s precisely what I do to formulate my Pod Projections. One of the various ways to utilize xHR/FB rate is to compare the hitter’s mark to his actual mark to determine how “real” the result was. Today, I’ll identify and discuss 9 hitters who posted xHR/FB rates significantly higher than their actual marks, suggesting upside this season if they are able to maintain those underlying skills.
We humans love to categorize and label things. Are you an extrovert or introvert? Does your favorite band play rock or pop music? Is that movie you saw last night a drama or romcom? Are pancakes a breakfast food or the best dinner ever? So it’s no surprise that this infatuation with ensuring everything fits into a box has spread to fantasy baseball. But I just don’t get it.
Yesterday, I discussed 10 hitters with big HR/FB rates whose marks were actually validated by their xHR/FB rates. Comparing HR/FB rate to xHR/FB rate helps guide my 2019 Pod Projections. Now let’s flip it and check on the hitters who posted surprisingly low HR/FB rates, but that were actually validated by low xHR/FB rates.
