What do we have here? For an explanation of this series, please read this introductory post. As noted in that introduction, the data is a hybrid projection of the ZIPS and Steamer systems with playing time determined through depth charts created by our team of authors. The rankings are based on aggregate projected WAR for each team at a given position. The author writing this post did not move your team down ten spots in order to make you angry. We don’t hate your team. I promise.

Also, keep in mind that these lists are based on rosters as of last week, so weekend transactions are not reflected in the rosters below. In some cases, teams have allocated playing time to different reserves than these depth charts show, but because they’re almost always choosing between near-replacement level players, the differences won’t move the needle much if at all.

And now, for our final act:

Your best bullpens in the league, separated by millimeters and likely to look completely different by the end of the year. In reality, this is the hardest group to project, because bullpens are more fungible than any other position on a roster. Starters who fail to pitch well in the rotation will get moved to the bullpen unexpectedly. Guys who look like fringe prospects will start throwing sidearm, destroy the world, and come up in a few months to dominate. The guys who were great last year will be less great this year, and new great guys will come out of nowhere.

Don’t yell at the projections, they’re doing the best they can with 60-inning samples. And we did the best we could to get the forecasted roles correct, but then Neftali Feliz gets optioned to Triple-A and who knows how long he’ll be there? So, yeah, imperfect exercise. Interpret accordingly.

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Episode 435
Dave Cameron is both (a) the managing editor of FanGraphs and (b) the guest on this particular edition of FanGraphs Audio — during which edition he explores the captivating nuances of service time and team control.

Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.

You can subscribe to the podcast via iTunes or other feeder things.

Audio after the jump. (Approximately 49 min play time.)

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Over each of the past three Mondays, the present author — who has written the majority of what follows while seated alongside his shockingly loquacious grandfather — has published a largely irresponsible leaderboard of regressed pitching leaders from spring training so far. This particular Monday, the author has produced another of those same kind of leaderboards — in this case, such as are current through Sunday, March 24th.

As noted last week, the existence of these leaderboards is predicated on three conditions, as follow:

(a) Spring-training stats don’t appear to be very predictive of regular-season stats; but

(b) The return of baseball is exciting, and invites consideration of some sort; and

(c) Research suggests that, of all spring-training stats, pitcher strikeouts and (to a lesser degree) walks are probably the closest thing to predictive.

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Episode 434
The host’s 93-year-old grandfather, a guest on FanGraphs Audio when he was merely a 91-year-old and 92-year-old grandfather, is the guest on this edition of FanGraphs Audio, as well — recorded live on tape from his (i.e. that same grandfather’s) condominium in Jupiter, Florida.

Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.

You can subscribe to the podcast via iTunes or other feeder things.

Audio after the jump. (Approximately 46 min play time.)

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As has been the case each of the past two years, the present author has recently transported his dumb body to Jupiter, FL, America — spring home of the Miami Marlins, the St. Louis Cardinals, and the author’s (now) 93-year-old grandfather.

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What do we have here? For an explanation of this series, please read this introductory post. As noted in that introduction, the data is a hybrid projection of the ZIPS and Steamer systems with playing time determined through depth charts created by our team of authors. The rankings are based on aggregate projected WAR for each team at a given position. The author writing this post did not move your team down ten spots in order to make you angry. We don’t hate your team. I promise.

As we make our way around the infield, we now land on second base. To the graph.

At the keystone position, there’s a clear top three, a bunch of teams in the same general range, and then there’s the Blue Jays. Make a trade, Blue Jays.

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Last week in these electronic pages — for reasons that remain opaque even to the author himself — I plumbed the depths of the 2005 edition of Baseball America’s Prospect Handbook with a view towards identifying how players distinguished for possessing certain tools (hitting for average, hitting for power, etc.) have eventually fared after graduating to the majors (or, alternatively, not graduating to the majors, from lack of opportunity/talent).

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Episode 433
Dave Cameron is both (a) the managing editor of FanGraphs and (b) the guest on this particular edition of FanGraphs Audio — which edition was recorded live on tape from Phoenix, Arizona.

Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.

You can subscribe to the podcast via iTunes or other feeder things.

Audio after the jump. (Approximately 41 min play time.)

Read the rest of this entry »

Podcast: Play in new window | Download

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Over each of the last two Mondays, the present author — who has written the majority of what follows beside a weird fountain in Arizona — has published a largely irresponsible leaderboard of regressed pitching leaders from spring training so far. This particular Monday, the author has produced another of those same kind of leaderboards — in this case, such as are current through Sunday, March 16th.

As noted last week, the existence of these leaderboards is predicated on three conditions, as follow:

(a) Spring-training stats don’t appear to be very predictive of regular-season stats; but

(b) The return of baseball is exciting, and invites consideration of some sort; and

(c) Research suggests that, of all spring-training stats, pitcher strikeouts and (to a lesser degree) walks are probably the closest thing to predictive.

Read the rest of this entry »

Episode 432
David Temple is a contributor both to NotGraphs and to the FanGraphs main page, and is proprietor of the very well-produced internet podcast Stealing Home. He’s also the guest on this edition of FanGraphs Audio, recorded live on tape in Phoenix, Arizona.

Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.

You can subscribe to the podcast via iTunes or other feeder things.

Audio after the jump. (Approximately 51 min play time.)

Read the rest of this entry »

Podcast: Play in new window | Download

Subscribe: RSS