Last week, I compared my Pod Projections to Steamer and calculated which hitters I was more bullish on and more bearish on for home runs. Today, I’ll do the same for stolen bases. Similarly to homers, I’m going to calculate a PA/SB rate first and then extrapolate that projection over 650 plate appearances so we’re only comparing stolen base projections and playing time forecasts don’t factor in.
Yesterday, I compared my Pod Projected home runs per 600 at-bats to Steamer’s forecast to identify and discuss a slew of hitters my projections are far more bullish on in the dinger department. Today, I’ll flip to the opposite end, those hitters who Pod forecasts for fewer home runs than Steamer, given 600 at-bats.
Every year, I pit my Pod Projections against the Steamer projections in various categories. Today I’m going to continue the annual smackdowns by calculating AB/HR rates and then extrapolating them over 600 at-bats. At that point, I’ll compare how many home runs each system is forecasting, given a 600 at-bat projection. I’ll start by sharing the names of hitters Pod is projecting for significantly more home runs than Steamer. Many of these players figure to be part-timers, so consider them sleepers in deeper leagues.
Finally, it’s Pod Projections time! The 2020 forecasts are now available and include over 500 player lines. As usual, I’ll dive into my projection methodology (detailed in Projecting X 2.0) by sharing my process on several hitters and pitchers.
I’ve got the draft and auction for two 12-team leagues coming. The Beat Jeff Zimmerman league is this Sunday night at 8 EST and also the mixed LABR auction in Florida. I’ve been grinding down the top-360 players (12 teams x 30 players per team). In these shallower formats, playing time is key for any mid to late-round targets. The following four teams are giving me pause when considering rostering some of their players.
The Reds have two or three too many players and several players will end up in the 450 to 550 PA range. When healthy, I believe Joey Votto, Mike Moustakas, Nicholas Castellanos, and Eugenio Suarez are safe. Freddy Galvis should be but his bat is so bad, he could lose playing time to possibly Nick Senzel.
The congestion starts in the outfield. Senzel is going to try to play center with Shogo Akiyama, Phillip Ervin, and Travis Jankowski as backup options. That leaves Akiyama along with Aristedes Aquino and Jesse Winker fighting it out for the right-field job.
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Last week, I used my hitter xBABIP equation to identify and discuss 8 hitters who could enjoy significant BABIP spikes this season, if they maintained the underlying skills driving those marks. Today, I’ll talk about the other side of the coin, those hitters whose xBABIP marks suggests serious downside this season, unless they improve their underlying skills.
Over this off-season, I have uncovered potential undervalued players by comparing the Steamer projections to the current NFBC ADP. So far I have gone through undervalued speedsters, power bats and outstanding batting average players. The exercise now continues for runs batted in.
In 2019, there were 57 players with least 85 RBI. There were 28 players who exceeded the 95 RBI mark, and 17 with at least 105. Anthony Rendon of the Nationals led all of baseball with 126 runs batted in. Jose Abreu led the American league with 123. Following them were NL East first basemen Freddie Freeman (121) and Rookie of the Year Pete Alonso (120).
As we have seen in batting average, prospective projections are more conservative. Steamer projects J.D. Martinez to lead baseball in the RBI category with only 119. Only six players are projected to knock in more than 110 runs.
For this year’s analysis, I will focus on all players with a Steamer projection of at least 85 RBI. This should give us a group of players who can greatly help your team’s RBI totals in the upcoming fantasy season.
For today’s draft value comparisons, I look at:
A little more than a year ago, Al Melchior had the brilliant and beautifully straightforward idea of investigating how strongly pretty much ever Statcast metric correlated with various traditional power metrics and compiling them in one post. He asked me to help out, which I was more than glad to do.
Recently, I saw folks talking about this again, and someone asked specifically about the 2019 season. I figured I could refresh the values from the original post quickly enough (certainly a lot more quickly than I did last time), and it would also help bring pertinent information to the fore for folks neck-deep in draft prep.
Spoiler alert: the results barely changed. But! I do feel more confident in this particular set of values, as I nerded out with programming instead of pulling dozens of different queries from the Baseball Savant search function and constantly getting frazzled.
OK, here’s the goods. For 2019 hitters:
Two years ago, I introduced you to the latest iteration of my hitter xBABIP equation, this time incorporating the effects of defensive shifts. Let’s find out which fantasy relevant hitters most underperformed their xBABIP marks in 2019, suggesting the potential for dramatic upside in 2020…if the hitter maintains those underlying skills.
Expected weighted on-base average (xwOBA) is one of Statcast’s most important additions to the Sabermetric sphere. It’s a simple premise — estimate a hitter’s deserved production based, simply, on his combinations of exit velocity (EV) and launch angle (LA) — with robust implications and applications. It’s remarkable how powerful the metric is with just two inputs.
However, the metric is not without its faults (or complaints from those who use it). Its simplicity is beautiful but inherently and knowingly lacking, accounting minimally or not at all for:
None of this necessarily serves as an indictment of xwOBA. The number of inputs you include affects the purpose you want it to serve. That is, do you want it to be descriptive or predictive? How about both? Maybe defense shouldn’t be included, then, if we can’t reasonably expect a hitter to face the same caliber of defense each year, something that is out of his control.
