Don’t you love it when a player’s name makes it super simple to create an absolutely brilliant title? I do! So yesterday, the Mariners continued their fantasy league moves by acquiring 27-year-old southpaw Drew Smyly. Up until 2016, Smyly enjoyed a fantastic beginning to his career, as he owned a 3.24 ERA/3.43 SIERA between the starting rotation and bullpen. But shoulder injuries hit in 2015 and he becaome afflicted with a severe bout of gopheritis during this past season. His ERA ballooned to 4.88 as his strikeout rate fell and he allowed the second highest fly ball rate in baseball among qualified pitchers. Now he moves to Seattle, where perhaps a change of scenery could do him some good. Will he benefit from the park switch? Let’s find out if such a possibility exists.

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In his ninth season, Colby Rasmus is set to join his fourth team, as he heads from one warm climate to another. But despite the fact he’ll be switching home parks, he’s still going to be playing in an orange juice box. On Monday, it was reported that he agreed to a one year contract with the Rays. Coming out of Houston, the knee-jerk reaction is that his fantasy potential, whatever there was left of it, is now kaput. But is that really true? Let’s bring on the park factors to find out what a move from playing half his games in Minute Maid Park (MM, Houston) to Tropicana Field (Tampa, errrr, St. Petersburg) may do to his performance.

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So just as I had hoped when I published my 2017 starting pitcher strikeout rate upsiders using my xK% equation, followed by my recap of my 2016 upsiders, it generated some excellent discussion. I made mention in my recap article, that was also requested in the comments, that I should also compare how xK% did versus the 2016 Steamer projections. It’s not enough to share a list of 12 guys with upside, show that as a group they did improve, with 66% doing so, and call xK% successful. If every forecasting system projected improvement as well without my xK% equation, then perhaps the equation isn’t providing any incremental value. So let’s bring my recap table back, but this time with the 2016 Steamer projections included.

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So on Thursday, I used my xK% equation (updated version coming soon! probably) to assemble a list of starting pitchers that possess strikeout rate upside this year, strictly based on their strike percentage, looking, swinging, and foul strike rates. In it, I hinted that maybe I’ll recap how my 2016 pitcher list performed and since the majority of the comments requested such a post, here it is! Remember that the list assumes no change in pitch mix, strike percentage, or strike type rates. Essentially it’s saying that if the pitcher keeps doing the same thing, his strikeout rate should improve simply based on better sequencing or fortune.

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Three years ago, I shared with you an updated version of my xK% equation. The formula uses a trio of strike type rates found at Baseball-Reference.com, including a pitcher’s looking, swinging, and foul strike percentages, along with his overall rate of strikes thrown. With an adjusted R-squared of 0.913, it explains a very high percentage of a pitcher’s strikeout rate. Its best use is early in the season when the plate appearance (the K% denominator) sample size is still small, as xK% uses total pitches as the denominator, so we can reach a reasonable sample size to analyze much more quickly.

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Yesterday, I discussed the fantasy relevant average fly ball and line drive exit velocity (EV) surgers, which overwhelming fueled a spike in HR/FB rate. Let’s now check in on the other side of the ledger — those hitters whose EV declined precipitously from 2015 to 2016.

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We officially have two seasons worth of Statcast data! Mind you, it’s not two full seasons, nor does it include every batted ball. But it’s still highly useful data. Although I continue to work on developing new equations with the data, we could all agree on one thing — harder hit balls are better. This is especially true when considering fly balls and line drives. We care far more about this bucket of batted balls than grounders because I have calculated a correlation of 0.769 between average fly ball and line drive exit velocity (EV) and HR/FB rate. So let’s find out which fantasy relevant hitters enjoyed EV surges from 2015 to 2016 and if those spikes resulted in HR/FB rate increases as well.

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So according to Brad Johnson’s end of season value compilation, Brandon Kintzler lost fantasy owners $4.20 in value. But that’s not really an accurate way of describing his contributions to fantasy owners this year. Glen Perkins opened the season as the Twins closer, but made it just a couple of weeks before going down with a shoulder injury. The Twins scrambled to find a replacement and eventually settled on Kintzler, who did a fine job. He earned his first save on June 8, and from that time, posted a 3.40 ERA and 1.34 WHIP with, while recording 17 saves. That stat package isn’t worth much in a 12-team mixed league, but likely a couple of bucks from the time he was actually rostered as a closer.

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Alas, we have come to both the final 2016 Pod Projection recap and the last review of my 2016 preseason articles! We arrive at Raisel Iglesias, whose projections were all likely to be wrong, because we all figured he’d remain in the starting rotation. Instead, he ended up making just five starts, missed a month and a half with a shoulder injury, and then return as a reliever. He even ended up recording six saves! But let’s see what I projected and what actually transpired anyway.

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Alas, we have reached the end of our Steamer and I reviews and I left the best for last…just kidding. Though I was surprisingly far more bullish on Sonny Gray than Steamer was, his season was an unquestioned disaster. So we certainly know whose forecast was better before even beginning our deep dive! But let’s get to the two projections sets anyway and compare what Steamer and I were expecting versus what actually transpired.

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