Let’s dive into Statcast’s Home Runs Leaderboard to identify and discuss the hitters with the largest gaps, both positive and negative, between actual and expected home runs. I’m using the default “Adjusted” type which applies an environmental variable to the xHR total to account for ballpark effects. Also note that this leaderboard includes postseason home runs, which made me do a double take since I definitely didn’t remember Cal Raleigh hitting 65 home runs and Shohei Ohtani also clearing 60 homers!

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A couple of weeks ago, the Pirates acquired second baseman Brandon Lowe from the Rays as part of a three-team trade. The 31-year-old had spent his entire career in Tampa Bay, so it’ll take some getting used to seeing him don a new uniform and in a new league. He’s coming off the second best fantasy season of his career. Let’s dive into the park factors to determine how the park switch might impact his results.

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Gosh, isn’t Jorge Polanco cold by now?! Though he has gone from the middle of the country to the West coast and now the East coast, he has somehow managed to remain North. Polanco signed a two-year, $40 million contract with the Mets last Tuesday after his highest PA total since 2021 and highest ever wRC+. Regardless of whether you think the Mets are buying high here, let’s dive into the park factors to see how the move from Seattle’s home park, T-Mobile Park, to Citi Field might impact his results.

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You’ve no doubt heard by now that last Thursday, Pete Alonso signed a five-year, $155 million contract with the Orioles. That’s going to annoy those still rooting for Coby Mayo, but is obviously a big move for the team. It’s hard to picture the lifelong Met donning a different uniform, but we’re going to get used to it eventually. For now, let’s consult the park factors to find out how the move from New York’s Citi Field to Baltimore’s Oriole Park at Camden Yards might impact his results.

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It’s no secret that Jordan Walker has been a disappointment offensively since a solid debut back in 2023. He was formerly ranked as the Cardinals best prospect and the 11th best prospect in the game just a couple of years ago. With 55/80 Game Power and 70/80 Raw Power grades, he was an intriguing future fantasy contributor. Unfortunately, his performance has gone South, wayyyyyy South, since that rookie campaign. Acknowledging that something needed to be done to return to his former top prospect path, he visited Driveline Baseball back in October in order to overhaul his swing mechanics. We’ve seen a number of Driveline Baseball success stories. Will Walker be the next?

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At the beginning of April, I took a super early look at hitter maxEV gainers. Obviously, a hitter had all season to record that maximum exit velocity, so a lower maxEV than the previous year at the time was not a cause for concern. However, if a hitter had already posted a meaningfully higher maxEV than the previous season, did that turn out to be an early indicator of a power breakout? Let’s review the names and find out.

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At the end of March, I dove into the hitter average bat speed risers and fallers. I realized afterward that although the metric stabilizes rather quickly, it was still simply too early to conclude anything. So I then discussed risers and fallers again with two posts back-to-back in mid-May. Let’s find out if these hitters maintained their mid-May levels, and if so, if it impacted their performance in the same direction as the bat speed change.

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One of the most enjoyable things I’ve been doing over the last couple of years is creating imaginary NFBC teams based on their average auction values (AAV). It’s a fun way to identify potentially undervalued players since I’m using actual market values and not just speculating. Today, let’s review my $14 NFBC offense, which is comprised of, you guessed it, only players with an AAV of $1.

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In early February, I compared 2024 actual wOBA to xwOBA to identify players who might be in for a wOBA surge or decline in 2025, based on the gap between to the two metrics. Let’s now review these lists to find out how the players actually performed. Did the potential surgers actually surge and did the decliners actually suffer declines?

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This year, a new projection system called OOPSY by Jordan Rosenblum joined our preseason forecasts. I decided to put it to the test by comparing its wOBA projections to those of our Depth Charts to identify the hitters it was most bullish and bearish on. With the final numbers now in the books, let’s see which system more accurately forecasted these players’ wOBA marks.

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