Top NL Outfield Prospects: A Different Take

This is meant to be less of an overly serious analysis as it is an exercise in projecting minor league players in a new and different way. Unfortunately, Chris Mitchell has largely done what I’m about to present, and with more sophistication at that, so I’ll have to strike out the new part. But different? Sure, to an extent.

While Chris’ KATOH predicts a hitter’s probability of major league success by projecting career wins above replacement (WAR) thresholds, my model predicts probability of future success in the context of various career accomplishments: Will he be a better-than-replacement level starter? An All-Star? A future MVP? Ultimately, the exercise is simpler and more qualitative, evaluating strictly AAA stats (rather than all minor league levels, as KATOH does) and making predictions according to various marginal changes in common statistics such as isolated power (ISO), stolen base rate (SB/PA) and age. Think of the model as a series of player comparisons. Also, please think of the model as not a replacement or substitute for KATOH but a complement to it, albeit a less intense one. I will use this tool for analysis, but only infrequently; I recommend you keep up with all of Chris’ KATOH posts (as well as Kiley McDaniels‘ prospect coverage) to fulfill your prospect consumption needs.

Alas, I’ve buried the lede: I aim to project the best MLB-ready National League outfield prospects and assess each hitter’s fantasy relevance. For the sake of this post, I consider AAA experience the factor that qualifies a player as “MLB-ready”, but I know it’s not absolutely true, as hitters occasionally make the jump straight from AA to the majors. This assumption means the names you’ll see aren’t all dynasty considerations; some may be suitable only for the deepest NL-only leagues. I encourage you to use discretion.

With that said, my model employs an ordered probit*, a type of regression that indexes several ordinal outcomes into one dependent variable. The regression spits out values that can be used to calculate the probabilities that each outcome will occur, with all the probabilities summing up to 1 (100%).

* For context, a (regular) probit regression uses a dependent variable consisting of only two outcomes, using 0’s to represent one outcome and 1’s to represent the other — like “yes” versus “no.” For example, 1 could indicate “player reaches MLB” and 0 otherwise.

I custom-created an index according to the following outcomes, ordered from worst to best:

Outcome Description of outcome
0 Bust: Did not reach majors
1 Liability: Reached MLB + accumulated negative career WAR
2 Bench piece: Reached MLB + positive WAR, but never qualified for batting title (502 PA)
3 Starter: Reached MLB + positive WAR + at least one qualified season
4 All-Star: Appeared on at least one All-Star team
5 Award-winner: Rookie of the Year, Silver Slugger or batting champ at least once
6 MVP: Most Valuable Player at least once

The data is comprised of roughly 850 individual AAA seasons in which a hitter recorded at least 140 at-bats. The sample starts in 2000 and cuts off after 2009 to allow the sampled hitters ample time to accumulate WAR, make an All-Star team, vy for a Most Valuable Player award, and so on. Using recent AAA stats may oversimplify a hitter’s true skill, but it’s a helpful simplification because it typically indicates that he a) was promoted, b) was demoted and never promoted again, and/or c) retired from the sport. I took care to eliminate older hitters mounting a comeback and injured players on rehab assignments.

The model accounts for age, batting average, isolated power, stolen base rate, strikeout rate (K%) and walk rate (BB%). All counting stats are league-adjusted.

Lastly, I limit the list to rookie-eligible hitters who recorded at least 100 plate appearances at AAA in 2014 (for sample size concerns) and are 26 years old or younger in 2015. Keep in mind, that renders all your favorite AA prospects, as well as budding stars such as Gregory Polanco, ineligible for this list. Without further ado:

1. Joc Pederson, LAD (KATOH’s Overall Top 200: #1)
At least a “Starter” / All-Star: 81% / 55%

It’s certainly a good sign that my model agrees with KATOH, but maybe it’s not entirely surprising, either, given Pederson’s prowess and the relatively thin crop of players who qualify for this list. It’s really not worth spending a lot of time on him: he’s the Dodgers’ Outfielder of the Future and already a popular sleeper among the fans.

2. Jorge Soler, CHC (KATOH: #3)
Starter / All-Star: 72% / 44%

Soler is Wrigley’s version of Pederson — an emerging star who may actually be underrated, or at least overlooked, thanks to an immense wealth of young talent, predominantly of the infield variety, inhabiting Chicago. He notched the highest ISO of any AAA hitter with at least 120 plate appearances last year. To attest: he smacked five home runs in 97 MLB plate appearances for the Cubs (for the mathematically disinclined, that paces out to 31 in 600 plate appearances). He’s guaranteed playing time, unlike the three names that follow, so he should already be on your radar.

3. Andrew Lambo, PIT (KATOH: Unranked)
Starter / All-Star: 38% / 15%

We’re only at No. 3 and the optimism has already taken a nosedive. I am as surprised to see Lambo on this list as I expect you (or KATOH, if it had feelings) are. His former top prospect glow has faded, and it would be exceedingly generous to call him the odd man out of a talented Pittsburgh outfield. Fortunately for Lambo, the names preceding him at first base on the depth chart are Pedro Alvarez (and his beleaguered bat) and Corey Hart (and his beleaguered knees), and Pittsburgh’s outfield depth isn’t overwhelmingly so. An injury, let alone someone else’s poor performance, ought to free up playing time for him.

Meanwhile, between AAA seasons, he lopped off a third of his strikeout rate, and his superficial decrease in power (as measured by home runs) masks an ISO and OBP that ranked 6th and 7th in the International League for hitters with at least 250 PAs. KATOH probably sees Lambo’s distant past and shakes its head; my model sees Lambo’s recent past and does a little head-bobble thing, like, “Hey, I could be into that.” He’s an intriguing NL-only investment.

4. Eury Perez, ATL (KATOH: #172)
Starter / All-Star: 36% / 14%

My model loves his speed and silently cheers for his move to Atlanta, where he will no longer be completely buried by the Nationals’ talented outfield. He joins a ragtag crew comprised of the likes of Nick Markakis, Eric Young, Jonny Gomes and the Artist Formerly Known as B.J. Upton; Upton is expected to be out until at least May, so Perez will get his fair share of spring training face time, and Gomes and Young each have notched more than 400 plate appearances only once in the last five years. The Braves will likely contend, albeit for last place, so Perez has as a good a shot as anyone to not only earn a starting role come April but also keep it even after Upton returns. His calling card is speed, but he should be able to hold his own in the batter’s box — a beneficial characteristic for someone whose value is found on the basepaths. He refuses to walk, however — a convenient alibi for someone who likes to run — so his on-base ability will likely be BABIP-fueled.

5. Randal Grichuk, STL (KATOH: #81)
Starter / All-Star: 33% / 12%

Grichuk, meanwhile, doesn’t really have a calling card, although you could maybe argue it’s power after he sent 25 balls into orbit in Memphis last year. But that’s about it: his roughly 4-to-1 K/BB ratio explains last year’s pretty miserable batting average, and his .234 ISO isn’t as exciting in the context of the Pacific Coast League. It’s worth mentioning that my model likes Grichuk for his age — he was only 22 last year — so he would probably benefit from more seasoning. Like paprika. Immediate outfield depth is thin in St. Louis, which privileges Grichuk as immediate heir to Matt Holliday‘s or Jason Heyward’s thrones in the event of an injury, but teammate Stephen Piscotty and his more-refined approach is lurking around the corner, too (he would have inhabited the No. 7 spot on this list).

Edit (2:43 PM EST): Due to semi-popular demand, here are the next five names on the list sans my insight. I hope this helps gives the list more context.

6. Edward Salcedo, PIT (KATOH: #131)
Starter / All-Star: 29% / 10%
7. Stephen Piscotty, STL (KATOH: #113)
Starter / All-Star: 28% / 10%
8. Alfredo Marte, ARI (KATOH: Unranked)
Starter / All-Star: 26% / 9%
9. Jaff Decker, PIT (KATOH: Unranked)
Starter / All-Star: 24% / 7%
10. Mel Rojas Jr., PIT (KATOH: Unranked)
Starter / All-Star: 21% / 6%





Currently investigating the relationship between pitcher effectiveness and beard density. Two-time FSWA award winner, including 2018 Baseball Writer of the Year, and 8-time award finalist. Previously featured in Lindy's Sports' Fantasy Baseball magazine (2018, 2019). Tout Wars competitor. Biased toward a nicely rolled baseball pant.

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jvetter
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jvetter

I like this a lot and would to see more of this kind of analysis done on RotoGraphs. I would have liked to see a little bit more of the list (maybe top 10).