Archive for review

Bold predictions are inherently jovial, whimsical, outlandish, possibly even blasphemous. You know you probably weren’t bold enough if you got too many correct, and you probably were too bold if you got too many incorrect. Mine typically follow suit. I don’t expect to get every prediction correct by the numbers, but I do hope each prediction is correct in spirit. My “spiritual” success in this regard, I’ve noticed, typically reflects upon how well my teams performed in a given season. Accordingly, I take my predictions seriously, and I sincerely use them as a collective barometer for how I had gauged value plays in the preseason.

I don’t remember any of my predictions, really, and I’m revisiting them in real time with you. My teams are doing well this year — 1st, 2nd, and 3rd in my three home leagues (humblebrag) (no expert or high-stakes leagues this year) — but I have a feeling my predictions have not stood the test of time. Again, this is to be expected. But, again-again, I’m not sure they’ve held up spiritually, either.

Here goes:

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2015 Visualized: Catcher

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For the next few weeks, the RotoGraphs staff will devote an entire week to each defensive position, including spotlights on particular players as well as trends throughout the 2015 season. This week, we’re highlighting first basemen.

I don’t claim to be a Tableau (or data visualization) whiz by any means, but I thought it would be cool to visually represent the first base landscape in 2015 — with some analysis sprinkled in.

Steamer and ZiPS represent premier player projection systems; FanGraphs’ Depth Charts combines the two, and the writing staff allocate playing time accordingly. The playing time part is less important relative to the combined projections, as aggregated projections tend to perform better than standalones.

Previously, I compared actual WAR (wins above replacement) to projected WAR. This is not entirely helpful in a fantasy context, however, given WAR is a catch-all component metric for offense and defense. Defense doesn’t do us a whole lot of good for fantasy purposes.

Thus, I figured out a way to compare projected wOBA (weighted on-base average) from the preseason to actual wOBA (1) by team and (2) by player within team. Unlike WAR, wOBA is a rate metric, so it does not need to be scaled according to playing time.

First: the difference between a team’s wOBA generated by first basemen and their projected wOBA. Blue represents the highest expected wOBA; yellow represents lowest expected wOBA. The size of the bar above (below) the line represents actual wOBA above (below) expectations.

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