I thought it may never be done. But Eric Hosmer finally cleared that impenetrable 20 home run barrier after many seasons of hardcore flirting. You see, Hosmer hates worms. So much so, that over 50% of the balls he has put into play over his career have been of the grounder variety. Those worms have likely learned not to pop out of the ground when he’s at the plate. But all those grounders come at the expense of fly balls. And a low fly ball rate has capped Hosmer’s home run potential. Until this year.

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It was no secret that I was a big Wil Myers fan heading into 2016. He appeared on my 8 Hitters With Major HR/FB Upside list, which, in part, led to my bold prediction that he’d hit 25 homers and knock in 90 runs. He made me look good. Thank you Wil. But aside from staying healthy, there was another part of his fantasy performance that surprised even the most bullish of the optimists — a hefty 28 steals.

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The beauty of our updated auction calculator is that it turns us all into masters of hindsight. Personally, I like to abuse this power by offering grating “I told you so” proclamations with little or no written accountability for the things I got wrong. But I also use the calculator to identify players who might be tough to evaluate going forward. Usually these players have greatly under-performed or outperformed their average draft prices and the sustainability of those performances is not always clear. Just because a player provided a certain end-of-season value doesn’t necessarily mean he’ll provide that value the next season. Obviously. Or if he does, that he’ll provide it by the same means. With that in mind, I’d like to look at a couple first basemen whose 2016 performances leave us with a muddled picture of how to value them going into next season.

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Heading into the 2016 season, two of the biggest questions we asked related to expectations for the newest arrivals from the KBO League of South Korea — Byung-ho Park and Hyun Soo Kim. Though obtaining historical statistics was easy, translating them from KBO to MLB is a challenge. At the beginning of February, I laid out my process in creating a projection for each, by first obtaining their career statistics, turning them into ratios, and then translating them as best I could into a 2016 MLB projection. Since this is first base week here at RotoGraphs, this article will focus on Park, with Kim’s review coming when we move on to outfielders. So let’s review Park’s performance and how that compared to my forecast.

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Votto finished as the No. 2 first baseman in 5×5 leagues via Brad Johnson’s postseason rankings.

Only one first baseman held a higher 5×5 value ranking than Joey Votto this season, and you can probably guess which one. That’d be Paul Goldschmidt of the Arizona Diamondbacks, who pulled a rabbit out of his hat by leading all first basemen with 32 stolen bases.

That’s not to say it’s unusual for Goldschmidt to steal bases, but that 32 — a career-high for Goldy — is more than he stole the previous two years combined (nine and 21, respectively). As a result, the steals vaulted Goldy over Votto, who swiped only eight bags and hit 30-plus points higher than his Arizona counterpart, with the rest of their 5×5 stats being comparable across the board. Frankly, you wouldn’t be complaining with either player, and the differential was pretty close, as Goldy checked in at $28.70 while Votto was at $26.40.

Also at $26.40 was Miguel Cabrera, who pummeled 38 home runs to Votto’s 29, but hit 10 points power, and didn’t steal any bases. Cabrera scored nine fewer runs, but drove in 11 more as both played in 158 games. Votto would probably be a better value pick in this sense, as I suspect Cabrera went a fair amount higher in drafts than his Canadian counterpart. Fantasy Pros had Miggy as the No. 10 player overall, and Votto at No. 22, so there’s some room for additional value with a round or so between them depending on your league size.

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I’m not sure we think about first round picks properly in fantasy baseball. I think too often we worry too much about if the player selected will “return first round value” which means being a top 10, 12, 15 player (or however many teams are in the league, of course). The BaseballHQ Forecaster reviews first round picks every year and compares them to those who finished as first rounders by dollar value and it shows we are terrible at actually picking first rounders in the first round. Their look at the last 12 years showed a 34% success rate.

I look for more of a balance between upside and floor with my first round pick. Make no mistake, we’re talking very high floors here. I’m not going to take Kyle Seager in the first round just because he has established a strong floor of quality play, but I’m careful not to overvalue nebulous upside while eschewing a “boring” pick just because I have a reasonable idea of what to expect from him. It’s not so much “will this guy blossom into a first round stud”, but more “will he be a centerpiece asset (top 35 or so) with a reasonable shot at first round production” which brings us to Miguel Cabrera.

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In 2015, Wil Myers, Hanley Ramirez, Mike Napoli, Carlos Santana, and Chris Carter were pretty bad. HanRam and Santana were $6 players. Napoli, Myers, and Carter combined for about negative $14. This season, the quintet teamed up to provide $87 of production – a near $90 increase in value. And that’s ignoring Adam Duvall, Mark Trumbo, and Daniel Murphy – all of whom also experienced big gains. It was a good year for snagging a cheap first baseman.

With 2016 in the books, let’s look ahead at some 2017 breakout candidates.

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Freddie Freeman had the best season of his career in 2016. He set career highs in just about every stat you can name: home runs, extra base hits, slugging, on base percentage, walks, BABIP and strikeouts. All of that sounded pretty great up until those last two, right?  You wouldn’t be alone if you felt that way.  Freeman has always been a good player, I doubt many have felt otherwise. It seems that every year Freeman marches into the season, puts up solid numbers at first base, shows off his leadership skills on and off the field, and then quietly goes into the offseason. This year was different, though. In 2016 Freeman had a true break out season worthy of MVP consideration. He had a substantial increase in performance across the board, in every major statistical category, and yet, there is still question about his ability to repeat this performance in 2017.  All due, in large part, I think, to one little number: BABIP.  

Freeman posted a .370 BABIP in 2016. This is significantly higher than his career averages .344 respectively, but it certainly isn’t unprecedented for a slugger to maintain a BABIP this high in the major leagues. Paul Goldschmidt, for example, has posted a .369 BABIP since 2014.  J.D. Martinez has hovered around the .366 mark as well of that same time frame.  Neither of these guys are horrible comps for Freeman.  Neither are speedsters, we know that much.  Although both are probably faster than Freeman by a decent margin, and I feel comfortable saying both are better power hitters as well.  We know the key to BABIP is hitting the ball around 14-18 degrees vertically, and the harder, the better.  Those sorts of hits will turn into singles pretty frequently, and if you can knock the launch angle up north of 24 degrees every once in awhile, you’ll hit home runs as well.  It’s easier said than done, but, in general, that is how you’re going to achieve consistently high BABIP over multiple seasons. Otherwise you start introducing the concept of luck.  

I have a few tools to examine just how ‘lucky’ Freeman may have been in 2016, though.  xStats examines each batted ball measured by statcast, and determines the league average success rate by comparing it to similarly hit balls (those with similar exit velocity along with vertical and horizontal launch angle).  So, for example, if the ball is hit 105 mph on a 22 degree vertical angle and 22 degree horizontal angle, xStats will compare that batted ball to all those hit between 104-106 mph and 20-25 degrees vertically and 20-25 degrees horizontally; count how many singles, doubles, triples, and homeruns were hit in that group divided by the size of the group; and then adjust these numbers for the running speed of the batter.  So, these numbers should be, theoretically, neutral for both park and fielding effects. Read the rest of this entry »

Last night I had a nightmare. I couldn’t get into a draft room because it was on a new site and Battle.net wanted me to complete a quest first. I had the fifth pick and the first guy was already on the clock. It was the most stressful dream I’ve had in years.

I think it’s pretty clear what Freud would say about it – my subconscious believes I’m not prepared for my fantasy drafts. Fortunately, I have another five months to get ready, and I’ve already built my Way Too Early Rankings. I started last week with catcher. We’ll move on to first base today. Oh, here’s what happened in 2016 at first base.

As a reminder, these rankings represent my first reactions rather than a truly rigorous approach. I’ve used an absolutely objective technique called mental math to compile the lists. I’m assuming a standard 5×5 format.

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Yesterday, we published the final 2016 first base rankings and dollar values. So let’s review my preseason Pod’s Picks and Pans at the position, where I identified those hitters I was most bullish and bearish on compared to the rest of my fellow RotoGraphs rankers.

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