Yesterday, I reviewed my comparison of starting pitcher spring training strikeout rates to Steamer projected strikeout rates and the list of pitchers with potential strikeout rate upside this past season. Now, let’s review the list of potential walk rate improvers based on the gap between spring walk rate and Steamer projected walk rate. Was Spring the first hint at an improved walk rate than expected? Let’s find out.

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At the end of March, I shared a list of starting pitchers who posted the largest gaps between their Spring K% marks and their Steamer projected K% marks. A many years old study I conducted confirms that Spring strikeout rate does convey meaning, so while 99% of Spring stats should be ignored, strikeout rate isn’t one of them. Small sample sizes and uneven competition caveats still heavily apply, though. Let’s find out how these Spring strikeout rate surgers actually performed. How many, if any, beat their Steamer projected strikeout rates?

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Yesterday, I reviewed the list of eight starting pitchers my Pod Projections were more bullish on ERA than Steamer. Today, let’s now flip to the starting pitchers I was more bearish on, suggesting downside versus Steamer. Overall, the Steamer ERA projections were more pessimistic than mine, so the gaps between the upside pitchers were much larger than the gaps between these downside pitchers. That means this list is more of a crapshoot. Let’s check out the results.

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Last week, I reviewed my hitter Pod Projections vs Steamer projections comparisons. Let’s now move along to the starting pitchers and ERA. As a reminder from my original post:

Though Steamer is the best pitching projection system out there, it struggles on pitchers that have shown consistent BABIP and HR/FB rate suppression skills and deficiencies, as what usually works for the majority of pitchers — projecting a heavy dose of regression to the MLB mean — means it misses on those uncommon exceptions. I use Statcast’s xBABIP now for my projections, so I’m not afraid to forecast a mark that strays from the league average. However, I certainly still include some regression as we don’t always have enough batted balls in a pitcher’s history for that mark to stabilize.

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Yesterday, I compared my Pod Projections in the stolen base category to Steamer and reviewed the five hitters I forecasted for a meaningfully higher stolen base total. Today, let’s now review the hitters I projected for fewer stolen bases than Steamer over a 650 plate appearance pace. As a reminder, stolen bases were down this year, so theoretically it should have been easier to hit on more of the downside guys.

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Today, I continue my Pod Projections vs Steamer battle reviews, this time moving along to stolen bases. Similarly to the way I compared our home run forecasts, I calculated a PA/SB rate first and then extrapolated that projection over 650 plate appearances, so we’re only comparing stolen base projections and playing time forecasts don’t factor in. We’ll start with the stolen base upside guys. For some context, the league stole the fewer bases per 650 plate appearances since…1971! So hitting on the upside guys is going to be a lot tougher than hitting the downside guys.

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Yesterday, I reviewed my Pod vs Steamer home run upside list results. Today, let’s now review my Pod vs Steamer home run downside list. As a reminder, the comparisons are AB/HR ratio and the table displays the implied home run totals over 600 at-bats. So the actual HR column isn’t necessarily what the player hit, but what his 600 at-bat pace actually was in order to truly compare home run rate projections without playing time factoring in.

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In mid-March, I listed and discussed the 10 hitters my Pod Projections forecasted for more home runs per 600 at-bats than Steamer. All that means is that I calculated the player’s projected AB/HR ratio from both systems and then extrapolated those projections over 600 at-bats, so I’m isolating the home run rate skill and keeping playing time constant. Let’s dive into the results.

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Earlier this week, I reviewed my imaginary cheapie NFBC pitching rosters, including the $9 staff, and the staff composed of pitchers not even bought in auctions. Today, let’s now review the incredible $244 staff I built.

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Last week, I reviewed my imaginary cheapie NFBC hitting rosters, including the $14 offense, and the offense composed of hitters not even bought in auctions. Today, let’s now review the incredible $251 offense I built. This exercise was probably even harder, as it’s more difficult to differentiate between top three round values than it is to pick out the best of the worst. Let’s see how this roster ended up performing.

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