Why do we care about a batter’s fly ball rate? Because all else being equal, a higher fly ball rate will result in more homers, so paying attention to a hitter’s batted ball profile is important. Typically, analysis centers around a hitter’s raw home run total and whether it’s higher or lower than expected at any point during the season. Sometimes, we see HR/FB rate thrown in as well to assess how real the home run surge or collapse might be. But fly ball rate, or FB%, is just as important, as it’s one of the three drivers of home runs, along with strikeout rate and the aforementioned HR/FB rate.
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Today, I complete my review of the early starting pitcher velocity changes to see how whether it was an early sign of what their velocities will be over the rest of the season. We’ll finish our reviews up with another set of velocity gainers.

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Let’s continue reviewing the early season starting pitcher fastball velocity changes. Today, we’ll look at the decliners through the first start and compare those velocity readings to what each posted through the rest of the season. Were these first start declines early warnings to sell while you can or did the pitchers quickly bounce back?

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Back during the first week of April, starting pitchers had made just one start…if they had taken the mound at all yet. So obviously, there wasn’t a whole lot to analyze. Rather than go dark for several weeks until there’s enough of a sample size to say anything, I decided to look at which starting pitchers had increased their velocity the most versus 2020 in that one and only start. Now I want to go back and find out if these pitchers actually sustained those increases, and if so, did it also result in a strikeout rate spike. Let’s find out.

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After just a few games this year, I decided to check in on batter maxEV. If a batter was already setting a new high only a couple of games into the season, I wondered if it was an early sign of a power and HR/FB rate surge over the rest of the year. So let’s now review those hitters who increased their maxEV the most at that point to see if it was indeed a hint of things to come. As a reminder, maxEV may have been recorded on a ground ball, which is far less exciting than one that comes on a fly ball. It doesn’t matter how hard a grounder is hit, as it cannot leave the park! A better look would have been to filter for only fly balls, so I’ll look at it that way next season.

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Today, I share the final review of my pre-season Pod Projections posts. This time, we shift to a starting pitcher, Zach Plesac, whose original writeup is here. Plesac did post a sub-4.00 ERA during his 2019 debut, but it wasn’t backed by his skills, as he handily outperformed his ugly 5.13 SIERA. During the short 2020, he enjoyed a true breakout as his strikeout rate surged thanks to pitch mix changes. Let’s see how he did for an encore and how it compared to the projections.

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Let’s continue reviewing the Pod Projections I shared early in the year. Today, I’ll review my Trent Grisham forecast. You can find the original writeup here. Grisham enjoyed somewhat of a fantasy breakout during the short 2020 season, as he went 10/10 over 252 plate appearances, putting him on a 20+/20+ pace over a full season. We fantasy owners salivate over that power/speed potential. Let’s see how he followed up and compare it to my projections and the rest of the forecasts.

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As you probably already know, I manually project player performance each and every year, and make the forecasts available on my Pod Projections page. It’s a seriously time-consuming task, but the manual process gives me some advantages versus a computer system, so I continue to create them. Early in the year, I share a couple of my Pod Projections, the individual forecasted metrics, and an explanation of the process I follow to arrive at each number. This year, the first projection I shared was that of Ha-seong Kim, who had just signed a four year contract with the Padres after spending seven seasons in the KBO (Korean Baseball Organization). Projecting veteran baseball players is challenging enough, so you can imagine the added layer of difficulty when working on a forecast for a player coming over from a foreign league. Let’s find out how Kim performed compared to my projection and the two that were published in early January.

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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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