Last year, I made fantasy infographics for each position, describing where players contribute the most in the standard 5×5 categories in a streamlined and easy-to-read fashion. I’ve tweaked my work in the offseason and I am bringing them back in a slightly different form with a slightly different process.
I’m still only comparing like positions to each other; for each position I take the top 30 players as listed by Mike Gianella, break them down into tiers, and come up with statistical averages and standard deviations using our very own PECOTA system. I did this so that we can compare like things to like things and to serve as a prep for the other graphs that are coming down the line. I’m sorry to say that the values and averages aren’t public at this time, so I can’t quite give you my formula here. Also there will be a big OBP graph at the end of the series as well as a graph that compares players to each other regardless of position, which was something of a hot request last year.
How to use this graph plus notes
This is a radar graph that is split out to five tiers. The fuller the graph, the better the player as PECOTA sees it. These graphs are also color-coded and they mirror Mike Gianella’s tier system; yellow = four-star player and so forth. There are a few things I’d like to address here. Catchers don’t steal many bases so their contributions in that category should be seen as a bonus only. Matt Wieters has a tiny radar because PECOTA doesn’t like him to get very many at-bats, this may or may not be adjusted in the near future as we tweak playing time. These players are in no way ranked in this order. I don’t value Salvador Perez over Brian McCann; they simply exist in the same tier.
My intent in creating these was to make a quick visual reference guide to see where certain guys can help in certain categories. For example, Lucroy is more balanced but Posey provides a ton of value in home runs over Lucroy, which makes a huge difference in how I see those players.
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It canbe very valuable to know this when bidding. And PECOTA has (or had) upside/downside type scores (standard deviation of forecast perhaps). The fantasy coverage only occasionally addresses this. And I would think that visual representation would be one nice way to show it. This knowledge can be huge for fantasy bidding/drafting strategy.
Any thoughts on how we could see this going forward in the fantasy coverage? Thanks!