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While there is no shortage of quality baseball projections, in large measure they are single numbers representing some measure of central likelihood such as a weighted average or median expectation. This is only half the story, as the compliment to average is the variance and shape of the distribution. Accordingly, this is an attempt to build out projections that incorporate both dimensions. For more background, see here.
These distributions are based on projecting playing time (PA/IP) and productivity on a seven point scale on each dimension to create a 7x7 matrix of 49 outcomes. The seven points roughly correspond to the 5th/20th/35th/50th/65th/80th/95th percentile outcomes on each dimension. I’ve used the public projection systems to guide the inputs, but also incorporating my own expectations (biases).
Projecting the 2021 Blue Jays regulars: Catchers/DH | Infield | Outfield | Starting Pitchers
Vladimir Guerrero Jr.
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The distribution for Vladdy is relatively wide and flat, reflecting the untapped but prodigious potential that has been hinted at. The bulk of the probability lies between 1-3 WAR, with a few expected outcomes below that and almost none on the negative side. That reflects, for all the consternation, the fact that before his 22nd birthday Guerrero has already been a good hitter with strong plate discipline.
On the other side, there is a long tail to the upside, reflecting the prodigious promise as well as the ability to hit balls really hard. If everything clicks and he can push his production into the 130+ wRC+ range, then he moves into above average regular territory even as a 1B/DH. And then there’s some possibility of further defensive/positional value upside if the conditional gains are maintained.
Marcus Semien
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For a veteran player with a longer track record, this is a pretty wide distribution of outcomes. But then there’s a fair bit of uncertainty after Semien’s monster 2019 and regression in 2020. The distribution having a modest peak around 2 WAR may seem pessimistic, but reflects a high floor as a solid regular, as well as some risk of higher productivity mixed with missed time given his age and some injury history. Then there’s a long skew to the upside baking in the 2019 breakout.
Cavan Biggio
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Conversely, for a younger less established player, Biggio had a very flat and normal-ish distribution, reflecting both consistency in his MLB track record (driven by a stable attribute in plate discipline) as well as a durable history. Of course, some inherent injury risk has to be nonetheless built in, driving some of wobble at the lower end (left tail). But he’d really have to dip from what he’s done to end up at or below replacement territory, so that’s a low probability.
On the flip side, there’s much less of a long tail to the upside. The bulk of the distribution extends from basically the low end of solid regular to above average regular (3-4 WAR) reflecting his all-around solid skillset. If everything clicked in a big season, there is some potential for a star level season, but Biggio’s profile stands outs in this infield in particular for consistency rather than purely.
Bo Bichette
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At first glance, this distribution might look off, but there’s a number of things going on here. First, given the missed month in 2020 as well as previous minor league injured stints, I’m modelling a moderate degree of injury risk. Since WAR is a counting stat, lower totals can come from both lower productivity full seasons, as well as higher productivity shortened seasons.
The projection is also building in uncertainty about the sustainability of his offensive production, given that it’s very geared to batted outcomes and he’s only had half a full season in the majors. Accordingly, there’s a very long tail of upside if he can stay largely healthy and maintain the productivity.
Inputs
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