Exploring Top Prospect Lists: Expectations by Ranking

Putting together a top prospect list is, I imagine, no small endeavor. Much like in any other ranking of athletes, there are innumerable factors to consider. How well does the player hit, run, and field? How is his strike zone discipline, or power, or contact ability? Is there a particular type of pitch or pitcher that he struggles with? If he’s a pitcher, is he durable enough to stick in the rotation? How are his secondary pitches? His control and command? How old is the player, and what level has he reached in the minors, and how has his production changed as he’s climbed?

Once you consider all of those factors and more for a thousand or so players and combine them into a single list, a healthy majority of fans will care about exactly one thing: Where did you rank my team’s guy(s)?

So, for today, we’re going to consider that factor only. Absent any other information about the player, what does the raw ranking mean?

Last time, we looked at the list of the 23 #1 overall prospects from 1990-2012, as chosen by Baseball America. They ran the gamut from superstar to bust, but the overall results had an average of 36.9 WAR. How does that compare to other ranks? Here are the 10 highest-WAR ranking positions over our sample:

Rank	Avg WAR
1	36.9
3	27.4
7	27.2
2	27.0
14	24.0
10	23.5
13	22.8
4	22.4
12	20.0
11	19.5

So #1 is ahead by a lot, and all of the highest-scoring ranking positions are in the top 15. But still, based on their performance in the sample, it sure looks like you’d rather be ranked 10-14 than 5-9, which is rather counterintuitive. The rankings get even stranger as you go further down. #42 prospects have an average of 17.7 WAR, coming in solidly ahead of both #5 and #8. (#42 prospects in the sample include Albert Pujols, Larry Walker, Nolan Arenado, and Adam Wainwright – not too shabby!)

Well, that’s the average, a measure prone to being inflated by outliers. How about the median?

Rank	Median WAR
1	35.7
3	20.2
14	19.9
7	19.3
2	18.9
12	18.3
11	17.3
10	17.1
5	15.2
13	14.5

Yes, #14 prospects actually moved UP two spots via the more stable measure. The 14s are comparatively light on major stars for this neighborhood (“only” Carlos Beltran, Zack Greinke, and Manny Machado), but include a remarkable number of steady players. And while the top-heavy #42 prospects now fall behind #8, #41 jumps ahead of both of them.

Ultimately, no matter what statistical tool you use, we’re still looking at a sample size of 23; some amount of noise is inevitable. Even attempting an amateurish smoothing function yielded only moderate success; it still looks like you’d rather have #14 than #5, and #30 over #20. So what are we to do? Well, if sample size is the concern… increase the sample size.

If you read through my recent series on ranking the top 100 players at each position, you’ll hopefully remember that as you move further down such a list, the gaps between players become increasingly narrow. The gap from #10 to #20 may be noteworthy; the gap from #80 to #90 is barely there. If we assume the same should be true of prospect rankings over a theoretical large sample, it allows us to group nearby prospects together, and increase the size of the groups as we move down the rankings. So let’s try that and see how things look:

Group	Avg WAR	Med WAR
1	36.9	35.7
2-5	23.4	16.7
6-10	20.6	12.9
11-15	20.7	16.5
16-25	11.8	5.7
26-50	11.3	4.9
51-75	8.2	1.6
76-100	7.0	0.8

That’s more like it! Numbers descending (fairly) steadily from group to group, with comparatively little unexpected bouncing around. The medians can be read pretty straightforwardly as follows: #1, likely star; #2-15, likely solid player, #16-50, likely mediocre player, #51-100, likely inconsequential.

We could, in theory, stop there – but the median isn’t the whole story. As noted above, #42 alone produced four major stars in 23 years; clearly not everyone ranked between 26 and 50 will post between 5 and 12 WAR before moving on with their lives. So let’s break it down further by percentiles to get a fuller sense of the odds.

Percentile	#1	#2-5	#6-10	#11-15	#16-25	#26-50	#51-75	#76-100
90	76.3	58.5	57.2	50.8	31.8	34.5	27.0	21.9
80	56.7	39.3	37.9	36.8	20.3	19.9	15.9	12.5
70	51.1	32.3	26.8	28.2	15.1	12.6	9.2	7.3
60	47.2	20.7	17.7	21.5	9.7	8.4	4.8	2.9
50	35.7	16.7	12.9	16.5	5.7	4.9	1.6	0.8
40	23.5	10.6	8.6	8.7	2.6	1.8	0.2	0.0
30	14.7	7.4	5.6	6.5	0.2	0.1	0.0	0.0
20	9.0	3.2	2.7	1.1	-0.1	-0.2	-0.3	-0.5
10	1.3	0.1	0.0	0.0	-1.2	-0.9	-1.1	-1.1

I like this table quite a lot, frankly. The groups break down remarkably cleanly: #1 (likely star), #2-15 (likely good player, reasonable hope of stardom), #16-50 (likely usable, reasonable hope of good player), #51-100 (likely barely a major leaguer, reasonable hope of usable). Even with all of the caveats dealing with the age of the sample, the use of only one source for the rankings, and the vagaries of bucketing as a technique (#16 should have a lot more in common with #15 than with #50), I think this is a usable guide for a fan trying to figure out how much confidence they should have in their team’s shiny new hope, whether BA says he's #8, #28, or #98.

But of course, we’re not going to stop there. Up next, we’ll plan to take a crack at the classic question: Is there such a thing as a pitching prospect?

Exploring Top Prospect Lists: Introduction

Baseball is a sport that rewards attention, among both journalists and fans. During the season there are games basically every day, and every team plays at least five games each week. That’s plenty to follow even without talking about injuries, trade rumors, and minor league performances. And then the offseason comes, and… crickets. What’s a baseball follower to do? Oh, there’s free agency, and trades, and award announcements, and eventually Spring Training. But it’s still a sharp downturn in activity, and journalism abhors a vacuum at least as much as nature does.

Enter the top prospect list. An offseason tradition dating back over 30 years, a good prospect list inspires hope in the fans of (almost) all teams, allowing them to dream of the futures of players they’ve likely never seen play, but who scouts compare favorably to present and past stars. Sure, your team might have lost 95 games this year, but there’s a 19-year-old in the low minors who reminds an expert of Francisco Lindor or CC Sabathia or Jeff Bagwell, so the future is bright!

Despite the often-glowing descriptions, most prospects do not turn into CC Lindor-Bagwell. But it’s worth finding out just how much signal there is amid the noise, and that’s what I’m hoping to do here.

So let’s talk method. There are several sources these days for top prospect lists; among others, MLB.com, Baseball Prospectus, ESPN, and Fangraphs have released multiple years' worth. But in order to maximize the sample while standardizing the approach as much as possible, I’ll be using the oldest source available for prospect lists: Baseball America, which first put out a top-100 in 1990. It’s also preferable to look at players whose careers are either finished or very nearly finished. The cutoff point here is somewhere in the early 2010s; looking at the BA top-100 lists from 2009-14, the number of players who appeared in MLB in 2024 goes 9, 18, 24, 33, 47, 53. I’m using 2012 (the 33) as the cutoff point. Yes, a number of those players are still active, but neither aging superstar Mike Trout nor aging reliever Shelby Miller is likely to do much in the future that will significantly change how we think of them for this purpose. Using the lists from 1990-2012 gives us a 23-year sample.

How do we evaluate the players? I’m going to keep it relatively simple and use career WAR, per Baseball Reference. Yes, it might be more accurate when evaluating from the team’s perspective to just use the first 6-7 seasons (that is, the amount of time before the player is eligible for free agency). But considering things from a fan's perspective, I find that approach to be both more work and less fun. If your team re-signs the player past that initial period, he doesn’t stop being a prospect who (hopefully) worked out; if you trade him away and he turns into a star, you don’t stop regretting the deal once he signs a big contract.

Both of these choices introduce obvious limitations. With regard to using only the BA lists, and only from over a decade ago, we move from examining the general category of top 100 lists to examining a particular subset of evaluators. The time difference also brings in the additional factor that even BA themselves have likely gotten better at prospect evaluation in the last 35 years; their two worst #1 overall prospects to date have been the 1991 and 1992 selections. Results taken from old BA lists may well not apply to BA's newer work, let alone present-day lists produced by other sources. bWAR has its share of issues as well, particularly on the pitching side, and they’re compounded by looking at players whose careers are ongoing.

With those caveats in mind, let’s get a preview of what’s to come by looking at how past-BA fared in choosing #1 prospects:

Year	Player	WAR
1990	Steve Avery	13.8
1991	Todd Van Poppel	-0.3
1992	Brien Taylor	0
1993	Chipper Jones	85.3
1994	Cliff Floyd	25.9
1995	Alex Rodriguez	117.5
1996	Andruw Jones	62.7
1997	Andruw Jones	62.7
1998	Ben Grieve	8.4
1999	JD Drew	44.9
2000	Rick Ankiel	9.1
2001	Josh Hamilton	28.2
2002	Josh Beckett	35.7
2003	Mark Teixeira	50.6
2004	Joe Mauer	55.2
2005	Joe Mauer	55.2
2006	Delmon Young	3.2
2007	Daisuke Matsuzaka	9.4
2008	Jay Bruce	19.9
2009	Matt Wieters	18.3
2010	Jason Heyward	41.8
2011	Bryce Harper	51.1
2012	Bryce Harper	51.1

There are plenty of stars on that list; I count eight MVP awards to date among many other accolades. But there are some less impressive performers as well – pitchers who got hurt or flamed out, hitters who never developed, all the risks you expect from prospects. Next time out, we’ll compare the performance of the top-ranked players to other subsets of the data, and hopefully form a more cohesive sense of what can be expected from current up-and-comers.