Editor’s Note: An updated version of the Top 100, which incorporates Eric’s spring looks through the end of March, is available to read here. As always, full scouting reports and tool grades for every ranked prospect can be found on The Board.

Below is my list of the top 100 prospects in baseball. The scouting summaries were compiled with information provided by available data and my own observations. The ETAs listed generally correspond to the year a player has to be added to the 40-man roster to avoid being made eligible for the Rule 5 draft. Manual adjustments are made where they seem appropriate, but I use that as a rule of thumb.

All of the prospects below also appear on The Board, a resource the site offers featuring sortable scouting information for every organization. It has more details than this article and integrates every team’s list so readers can compare prospects across farm systems. It can be found here.

And now, a few important things to keep in mind as you’re perusing the Top 100. You’ll note that prospects are ranked by number but also lie within tiers demarcated by their Future Value grades. The FV grade is more important than the ordinal ranking. For example, the gap between Sebastian Walcott (no. 4) and Quinn Mathews (no. 32) is 28 spots, and there’s a substantial difference in talent between them. The gap between Chase Petty (no. 42) and Cam Smith (no. 70), meanwhile, is also 28 numerical places, but the difference in talent is relatively small. Read the rest of this entry »

Below is a team-by-team analysis of last night’s draft activity. Remember that you can find more detailed scouting reports and tool grades for the players drafted yesterday over on The Board. The positions below are what the player was announced as, not necessarily what I have them projected as on The Board. For pitchers, I have a role designated below: starter (SP), or single-inning or multi-inning reliever (SIRP and MIRP). Read the rest of this entry »

Below is our list of the top 100 prospects in baseball. The scouting summaries were compiled with information provided by available data and industry sources, as well as our own observations. The ETAs listed generally correspond to the year a player has to be added to the 40-man roster to avoid being made eligible for the Rule 5 draft. Manual adjustments are made where they seem appropriate, but we use that as a rule of thumb.

All of the prospects below also appear on The Board, a resource the site offers featuring sortable scouting information for every organization. It has more details than this article and integrates every team’s list so readers can compare prospects across farm systems. It can be found here.

And now, a few important things to keep in mind as you’re perusing the Top 100. You’ll note that prospects are ranked by number but also lie within tiers demarcated by their Future Value grades. The FV grade is more important than the ordinal ranking. For example, the gap between Paul Skenes (no. 10) and Chase DeLauter (no. 29) is 19 spots, and there’s a substantial difference in talent between them. The gap between Kyle Teel (no. 80) and Will Warren (no. 99), meanwhile, is also 19 numerical places, but the difference in talent is relatively small. Read the rest of this entry »

Below is our list of the top 100 prospects in baseball. The scouting summaries were compiled with information provided by available data and industry sources, as well as from our own observations. This is the third year we’re delineating between two anticipated relief roles, the abbreviations for which you’ll see in the “position” column below: MIRP for multi-inning relief pitchers, and SIRP for single-inning relief pitchers. The ETAs listed generally correspond to the year a player has to be added to the 40-man roster to avoid being made eligible for the Rule 5 draft. Manual adjustments are made where they seem appropriate, but we use that as a rule of thumb.

All of the prospects below also appear on The Board, a resource the site offers featuring sortable scouting information for every organization. It has more details (and updated TrackMan data from various sources) than this article and integrates every team’s list so readers can compare prospects across farm systems. It can be found here.

And now, a few important things to keep in mind as you’re perusing the Top 100. You’ll note that prospects are ranked by number but also lie within tiers demarcated by their Future Value grades. The FV grade is more important than the ordinal ranking. For example, the gap between Padres shortstop Jackson Merrill (No. 10) and Yankees shortstop Oswald Peraza (No. 40) is 30 spots, and there’s a substantial difference in talent between them. The gap between Peraza and Guardians pitcher Tanner Bibee (No. 70), meanwhile, is also 30 numerical places, but the difference in talent is relatively small. You may have also noticed that there are more than 100 prospects in the table below, and more than 100 scouting summaries. That’s because we have also included the 50 FV prospects whose ranking fell outside the 100, an acknowledgement both that the choice to rank exactly 100 prospects (as opposed to 110 or 210 or some other number entirely) is an arbitrary one and that there isn’t a ton of daylight between the prospects who appear in that part of the list.

You’ll also notice that there is a Future Value outcome distribution graph for each prospect on the list. This is an attempt to graphically represent how likely each FV outcome is for each prospect. Before his departure for ESPN, Kiley McDaniel used the great work of our former colleague Craig Edwards to find the base rates for each FV tier of prospect (separately for hitters and pitchers), and the likelihood of each FV outcome. For example, based on Craig’s research, the average 60 FV hitter on a list becomes a perennial 5-plus WAR player over his six controlled years 26% of the time, and has a 27% chance of accumulating, at most, a couple of WAR during his six controlled years. We started with those base rates for every player on this year’s list and then manually tweaked them depending on our more specific opinions about the player. For instance, Dodgers 2B/LF Miguel Vargas and Marlins shortstop Yiddi Cappe are both 50 FV prospects, but other than them both being Cuban, they are nothing alike. Vargas is a bankable, big league-ready hitter with moderate upside, while Cappe is a risky low-level prospect with huge upside. Our hope is that the distribution graphs reflect these kinds of differences.

This year’s crop of prospects has a relatively shallow high-impact group at the very top of the list. There is no 70 FV prospect in this year’s class and only two 65 FV prospects. In a typical year, we’d have a couple more than that, and sometimes as many as five or six, but this year there are only two. And it doesn’t take long before you start talking about players with warts that reduce confidence in the overall profile. This year’s 60 FV tier has some players who still show some hit tool red flags (Chourio, De La Cruz, Jones) that kept them from ever really being considered for the tier above.

Only 37 of the 112 ranked players here are pitchers. Pitchers tend to be volatile and subject to heightened injury risk, plus their usage is being spread out among more pitchers in the majors, reducing the impact of individuals. The 55 FV pitchers and above tend to have some combination of monster stuff and good command, whereas the 50 FV pitchers often have one or the other. We gravitate toward up-the-middle defenders littered all throughout the minor leagues, and really only tend to push corner bats onto the list when they’re close to the big leagues, or if we have an abnormal degree of confidence that they will continue to hit all the way through the minors. High-risk hitters with huge tools are also welcome since FV is a subjective way to factor both ceiling and risk into the same grade.

For a further explanation of the merits and drawbacks of Future Value, please read this and this. If you would like to read a book-length treatment on the subject, one is available here. Read the rest of this entry »

Below is our list of the top 100 prospects in baseball. The scouting summaries were compiled with information provided by available data and industry sources, as well as from our own observations. This is the second year we’re delineating between two anticipated relief roles, the abbreviations for which you’ll see in the “position” column below: MIRP for multi-inning relief pitchers, and SIRP for single-inning relief pitchers.

And now, a few important things to keep in mind as you’re perusing the Top 100. You’ll note that prospects are ranked by number but also lie within tiers demarcated by their Future Value grades. The FV grade is more important than the ordinal ranking. For example, the gap between Julio Rodríguez (No. 4) and Triston Casas (No. 16) is 12 spots, and there’s a substantial difference in talent between them. The gap between Mark Vientos (No. 64) and Patrick Bailey (No. 76), meanwhile, is also 12 numerical places, but the difference in talent is relatively small. You may have noticed that there are more than 100 prospects in the table below, and more than 100 scouting summaries. That’s because we have also included 50 FV prospects whose ranking fell outside the 100. Their reports appear below, under the “Other 50 FV Prospects” header. The same comparative principle applies to them.

You’ll also notice that there is a Future Value outcome distribution graph for each prospect on the list. This is an attempt to graphically represent how likely each FV outcome is for each prospect. Before his departure for ESPN, Kiley McDaniel used the great work of our former colleague Craig Edwards to find the base rates for each FV tier of prospect (separately for hitters and pitchers), and the likelihood of each FV outcome. For example, based on Craig’s research, the average 60 FV hitter on a list becomes a perennial 5-plus WAR player over his six controlled years 26% of the time, and has a 27% chance of accumulating, at most, a couple of WAR during his six controlled years. We started with those base rates for every player on this year’s list and then manually tweaked them depending on our more specific opinions about the player. For instance, Elly De La Cruz and Steven Kwan are both 50 FV prospects, but they are nothing alike. De La Cruz could be a switch-hitting shortstop with plus-plus power or he might turn into Seuly Matias. Meanwhile, Kwan has performed through the upper minors and is almost certain to contribute to a big league team, but doesn’t have nearly the same power potential or high-end ceiling De La Cruz does. Our hope is that the distribution graphs reflect these kinds of differences.

This year’s crop of prospects is a little bit down in the 60 and 55 FV tiers. Typically, the 55 FV tier runs to about the 50th overall prospect on the Top 100 (which again isn’t really a Top 100, so much as a ranking of all the 50 FV and above prospects, but that title is an SEO nightmare), but this year’s group only extends through No. 32. This might be due to random variation in the prospect population, or have to do with the lost year of development in 2020 or the new rules surrounding rookie eligibility, which caused several players to graduate off our lists more quickly than in the past. Jose Barrero and Keibert Ruiz, for example, would have been eligible under the older roster rules. Those guys can be found on The Board’s Graduates section. Or perhaps our evaluations are just wrong.

For a further explanation of the merits and drawbacks of Future Value, please read this and this. If you would like to read a book-length treatment on the subject, one is available here. Read the rest of this entry »

Below is my list of the top 100 prospects in baseball. The scouting summaries were compiled with information provided by available data and industry sources, as well as from my own observations.

As I’ve noted while publishing my team lists, because there was no minor league season in 2020, there are some instances where no new information was learned about a player. Players whose write-ups have not been meaningfully altered begin by telling you so. Each blurb ends with an indication of where the player played in 2020, which in turn likely informed the changes to their report if there were any. As always, I’ve leaned more heavily on sources from outside of a given org than those within for reasons of objectivity. Because outside scouts were not allowed at the alternate sites, I’ve primarily focused on data from there, and the context of that data, in my opinion, reduces how meaningful it is. Lastly, in an effort to more clearly indicate relievers’ anticipated roles, you’ll see two reliever designations, both on my lists and on The Board: MIRP, or multi-inning relief pitcher, and SIRP, or single-inning relief pitcher.

And now, a few important things to keep in mind as you’re perusing the Top 100. You’ll note that prospects are ranked by number but also lie within tiers demarcated by their Future Value grades. The FV grade is more important than the ordinal ranking. For example, the gap between prospect No. 3 on this list, Adley Rutschman, and prospect No. 29, Josiah Gray, is 26 spots, and there’s a substantial difference in talent between them. The gap between Heliot Ramos (No. 61) and Luis Matos (No. 87), meanwhile, is also 26 numerical places, but the difference in talent is relatively small. You may have noticed that there are more than 100 prospects in the table below, and more than 100 scouting summaries. That’s because I have also included 50 FV prospects whose ranking fell outside the 100; their reports appear below, under the “Other 50 FV Prospects” header. The same comparative principle applies to them.

You’ll also notice that there is a Future Value outcome distribution graph for each prospect on the list. This is an attempt to graphically represent how likely each FV outcome is for each prospect. Before his departure for ESPN, Kiley McDaniel used the great work of our former colleague Craig Edwards to find the base rates for each FV tier of prospect (separately for hitters and pitchers), and the likelihood of each FV outcome. For example, based on Craig’s research, the average 60 FV hitter on a list becomes a perennial 5-plus WAR player over his six controlled years 26% of the time, and has a 27% chance of accumulating, at most, a couple of WAR during his six controlled years. I started with those base rates for every player on this year’s list and then, with the help of Kevin Goldstein (who assisted with other elements of this list as well), manually tweaked them depending on our more specific opinions about the player. For instance, Jose Garcia and Trevor Larnach are both 55 FV prospects, but Garcia’s approach makes him very volatile, while Larnach is a surer bet to hit. At the same time, if Garcia ever develops a better approach, his power and ability to play a premium position give him a ceiling that Larnach can’t reasonably attain. My hope is that the distribution graphs reflect these kinds of differences.

For a further explanation of the merits and drawbacks of Future Value, please read this. If you would like to read a book-length treatment on the subject, you can purchase the book I co-wrote with Kiley, Future Value.

Read the rest of this entry »

Below is my list of the top 100 prospects in baseball. The scouting summaries were compiled with information provided by available data, industry sources, as well as from my own observations.

Note that prospects are ranked by number but also lie within tiers demarcated by their Future Value grades. The FV grade is more important than the ordinal ranking. For example, the gap between prospect No. 3 on this list, MacKenzie Gore, and prospect No. 33, Jazz Chisholm, is 30 spots, and there’s a substantial difference in talent there. The gap between Evan White (No. 64) and Matthew Liberatore (No. 94), meanwhile, is also 30 numerical places, but the difference in talent is relatively small. You may have noticed that there are more than 100 prospects in the table below, and more than 100 scouting summaries. That’s because we have also included 50 FV prospects who didn’t make the 100; their reports appear below, under the “Other 50 FV Prospects” header. The same comparative principle applies to them.

As a quick explanation, variance means the range of possible outcomes in the big leagues, in terms of peak season. If we feel a prospect could reasonably have a best big league season of anywhere from 1 to 5 WAR, that would be “high” variance, whereas someone like Sean Murphy, whose range is something like 2 to 3 WAR, would be “low” variance. High variance can be read as a good thing, since it allows for lots of ceiling, or a bad thing, since it also allows for a lower floor. Your risk tolerance could lead you to sort by variance within a given FV tier if you feel strongly about it. Here is a primer explaining the connection between FV and WAR. For further explanation of the merits and drawbacks of Future Value, please read this. (If you would like to read a book-length treatment on the subject, you can pre-order my forthcoming book, Future Value, co-written with erstwhile FanGraphs analyst Kiley McDaniel.)

You’ll also notice that there is a FV outcome distribution graph for each prospect on the list. This is our attempt to graphically represent how likely each FV outcome is for each prospect. Using the work of Craig Edwards, I found the base rates for each FV tier of prospect (separately for hitters and pitchers), and the likelihood of each FV of outcome. For example, based on Craig’s research, the average 60 FV hitter on a list becomes a perennial 5+ WAR player over his six controlled years 26% of the time, and has a 27% chance of accumulating, at most, a couple WAR during his six controlled years. I started with these base rates for every player, then manually tweaked them for the first few FV tiers to reflect how I think the player differs from the average player in that FV tier, since a player in rookie ball and a player in Triple-A with the same FV grade obviously don’t have exactly the same odds of success. As such, these graphs are based on empirical findings, but come with the subjectivity of my opinions included to more specifically reflect what I think the odds are of various outcomes.

Read the rest of this entry »

In November, I published the results of my research attempting to put a value on minor league prospects. It seems only natural that a similar study on draft picks should follow.

As with prospect valuations, considerable work has preceded mine in the area of valuing draft picks. Sky Andrechuk, Victor Wang, Matthew Murphy, Jeff Zimmerman, and Anthony Rescan and Martin Alonso have all done similar studies.

The work below is less a replacement of the work already done and is more of a continuation of, and addition to, the study of the subject matter. As to why we might want to know this information, creating an expected value for a draft pick helps us to understand and manage our expectations of draftees’ performance. More practically, teams regularly give up draft picks to sign free agents, receive extra draft picks when they lose free agents or reside in a smaller media market, and drop slots when they exceed the highest competitive balance tax payroll threshold, not to mention that some picks can be traded. Determining a value for these picks helps us better understand the decisions teams make regarding those picks.

In some ways, determining draft pick value is a little more complicated than figuring out prospect value. When determining prospect value, players are placed within the constraints of the current CBA, which provides for a minimum salary for roughly three seasons and suppressed arbitration salaries for another three years after that before a player reaches free agency. Draft picks are confined to the same system, but there is also a signing bonus to consider, not to mention slotting rules that are often manipulated in order to move money around to different picks.

Due to signing bonuses and bonus slots, to arrive at an appropriate value for a draft pick, it isn’t enough to determine the present value of players’ WAR in the majors without getting to a dollar figure. We also have to account for the present value in dollars and then subtract the expected bonus.

Before explaining the methodology for draft picks, we can look at the very similar framework used to get to the present value of minor league prospects. From my “Update to Prospect Valuation”:

To determine surplus value for players, I used WAR produced over the first nine seasons of a career, including the season in which a prospect was ranked. Why nine years? In today’s game, most players don’t hit free agency until after their seventh major-league season. By examining nine seasons, it’s possible to account for prospects who were still a couple years away from the majors when they appeared on a top-100 list — as well as late-bloomers who might have bounced up and down between the majors and minors for a full season.

Of course, not all prospects continue to develop in the minor leagues after appearing on a top-100 list. Some debut in the majors right away. Due to the methodology outlined above, such players might be in a position to receive greater credit for their first nine seasons simply because they were closer to the majors when they were ranked. To accommodate this issue, I’ve spread out a player’s WAR over the final seven seasons of the period in question, distributing 10% of it to years three and four before slightly gradually increasing that figure up to 20% by year nine. To calculate surplus value, I’ve discounted WAR by 3% in years No. 3 through 5 (to approximate the impact of the league-minimum salary) and then 15% in year six, 32% in year seven, 48% in year eight, and 72% in year nine. Spreading out the WAR in this way not only mimics a sort of generic “development curve” but also ensures that arbitration discounts aren’t too heavy.

After that, I applied an 8% discount rate for present value. For players immediately ready to play, the extra value they get from the eighth and ninth year is minimized by removing value they actually provided from the first two years and spreading into later seasons. This similarly ensures that the controllable years of players who take longer to develop or reach the majors aren’t treated the same way as those produced by players who contribute right away. A two-win season in 2019 is more valuable than a two-win season in 2021; and this method helps to strike that balance.

Draft picks aren’t as close to the majors as most minor league prospects are. To combat this problem, I used 10 years for college draftees and 11 years for those drafted out of high school, but kept the rest the same as above.

The other difficult issue for draft picks is one of sample size. When I looked at 15 years of prospect lists, it meant we were looking at hundreds of prospects at nearly every single prospect grade. If we did the same for draft picks over 15 years, we only have 15 players at every pick, which isn’t much of a sample. To compensate for this issue, I took a large percentage of the pick in question, and then a smaller percentage on a sliding scale of the next 12 picks. After all, having the third pick in the draft isn’t just an opportunity to take the third-best player; it is the opportunity to choose between a whole host of players. The Astros taking Mark Appel ahead of Kris Bryant doesn’t make the second pick in the draft better than the first. The Astros could have had Kris Bryant, and factoring in the picks that follow helps represent that challenge.

Smoothing things out a bit helps make sure a small sample doesn’t create a bias around a pick. For example, in the years I studied (1993-2007), the third overall pick often performed poorly, but Eric Hosmer, Manny Machado, and Trevor Bauer were taken with the third pick in the three of the four drafts that followed. It wasn’t bad to have the third pick from 1993-2007. It just happened that those picks didn’t work out well.

First round picks were then adjusted upwards slightly so that the actual WAR of the picks and the adjusted value using the method above matched. The values were then smoothed out to ensure the value of the picks moved downward. The smoothing stopped mattering after the second round. After finding the present-value WAR for each pick (I used $9M/WAR), I then subtracted the slot amount for each pick to come up with a current value.

This is what the first 70 picks look like:

The values at the very top of the draft are going to be context heavy. Sometimes, the top pick is a solid 55, like Casey Mize was a season ago. Other years, it might be Bryce Harper. For context, here is how the first round played out last season in terms of bonuses and slots for the pick.

The draft reveals just how important it is for teams to receive a compensation pick the following season when they fail to sign a pick in the current year. While there is certainly lost developmental time and opportunity in losing a pick for one year, losing that pick permanently would be a major loss, and provide considerably more leverage to the players when negotiating contracts.

Moving down, this is what the picks in the third round and below are worth. For the 11th round and below, the median value is used instead of the average given the potential for a few really good picks out of thousands to distort the value beyond what would be a reasonable expectation for that pick.

In practical terms, that means that for the picks in round 20 or later, you might come up with one average player every three years. For picks in rounds 11-20, a team can expect an average player every two or three seasons. The same is true for rounds three and four combined. It’s hard to find good players in the draft after the first round. There’s as much value in the first 100 picks as in the entire rest of the draft. Teams might opt to pay a third round pick a $3,000 bonus to save money and use it elsewhere. That doesn’t mean that we should expect the same performance from that pick as we would a typical third rounder, but we should expect that the slot money the team uses elsewhere will have a value somewhere close to $4 million.

When considering how teams sometimes shift money around from the second or third round to the sixth and seventh round (and vice versa) or use money to sign players above $125,000 after the 10th round, it helps to know how to properly value every dollar spent. For the first 100 picks, where the bonuses are the highest, every dollar spent generally yields five dollars in value. In rounds 4-5, every dollar should yield about six dollars in value, and in rounds 6-10, every dollar spent should yield 10 dollars in value due to the talent available and the small signing bonuses. Given this information, it appears teams might be better off paying slightly less money in the first few rounds while still getting good talent, and shifting some of that money elsewhere in the first 10 rounds. If teams are shifting money from the first 10 rounds to the back of the draft, they need to feel pretty confident in that player’s ability.

In terms of comp picks in this year’s draft, the Arizona Diamondbacks will receive a pick at the end of the first round for losing Patrick Corbin to the Nationals. That pick is worth something close to $10 million. The six small-market teams will receive picks between rounds one and two that are worth $8 million to $9 million each. The other eight small-market picks after the second round are worth around $4 million each, and the same is true for the free agent compensation picks like the one the Dodgers will receive for losing Yasmani Grandal.

Teams signing free agents who have received a qualifying offer generally lose their second pick, and that pick is worth somewhere between $4 million and $10 million depending on where in the draft the team is picking. The Red Sox’s top pick drops down 10 spots this year because they were more than $40 million over the competitive balance tax. That penalty is only worth around $2 million.

There’s further analysis to be done based on whether a player is coming out of high school or college, as well as whether he is a position player or pitcher, but that work will be left to a later date. For now, I hope this is a useful starting point for further study, and for gaining a greater understanding of draftees’ expected production and teams’ decision making.

FanGraphs has obtained bonus figures for over 90% of all the international signings in baseball history. We have all of the most significant bonuses, every big leaguer, notable current prospects, and everything in the mid-six figure range and above, along with many years for which we have every single signing.

This provides us with a pretty complete picture of the distribution and trends of these bonuses, also allowing us to estimate how many players we’re missing. Those players are overwhelmingly names you wouldn’t recognize, guys who played for a couple of years before being released, signing as filler for a five-figure bonus.

We’ve taken out all of the major league deals (think older, high profile Japanese and Cuban players), and we have incomplete data for all of the Mexican players, as MLB notes all of them as receiving a $0 bonus (it’s an easy workaround for a convoluted system that’s mostly cleaned up now). We’ve filled in correct bonuses for players where we have it, mostly among the high profile Mexican signings, like Luis Urias and Julio Urias (no relation).

We could do a lot of things with this data — and we will, including listing it on the player pages and THE BOARD — but the thing that interests me today is combining this bonus data with our asset value research, and the dollars-per-WAR framework to get a better idea of what a dollar invested in an international amateur player returns. We’ll start with some of the meta data:

2017 was the first season of hard-capped bonus pools, which explains why bonuses declined and also why they spiked the year prior. These figures don’t include the pool overage payments made to MLB from 2013 to 2016. We estimate those figures to add up to about $250 million over those four years, with about $100 million paid to MLB in 2016 alone. (The CBA says that this money was to be spent on international operations and initiatives.)

Since the international market changes and matures so rapidly, it makes sense to start with the early 2000s signing classes as a baseline for a similar era to today. Most of the players who signed 15 years ago are now in their early 30s and have either played out their entire careers or are into their seventh year of major league service time. We can grab the dollar-per-WAR figures from the years that spanned their controlled years and turn that historical WAR into a dollar amount of value created. I used seven seasons since we don’t have comprehensive service time data, which, from some spot-checking, appears to do the trick. We have the FV of the most recent signings that are current prospect on THE BOARD, which maps to an asset value.

The most interesting players to analyze signed in the last 5-10 years, are in the big leagues, and are in the middle of their control years, so I had to do some work to peg their value. I quantified what they’ve already produced the same way I did with the older players, then estimated or figured out by hand their current service time situation. I then used our various projections to fill in what those players are expected to produce in the rest of their controlled years.

In short, it’s not perfect, but as with filling in the holes in the bonus data, it’s fairly accurate and any mistakes appear to cancel each other out in the aggregate. There’s some noise in the data year-to-year, but it appears that right around 2004, the market improved its output and has held mostly steady to today. Here’s the production (a combination of produced WAR, projected WAR, and minor league asset values) over this period:

I included up to the 2017 class, but it would appear that we need three full seasons in the system — with players having signed on July 2, 2015, and played in 2016, 2017, 2018 — before the class as a whole has developed enough to reveal how much value it could create. As such, a dozen years (2004-2015) appears to be our usable sample.

We could use the above figures to create a simple return on investment calculation, but a true ROI would compute what a team is making on the average dollar spent, so we also have to consider the expense to operate the department that signs the players. Building or renting an academy, feeding and housing the players, running a DSL team, paying coaches, trainers, scouts, and administration and travel expenses are all facets of an international operation that are essential to signing and developing these players, so they have to be considered alongside the bonus expenditures. After consulting with some international directors, I’ve estimated those costs for all 30 teams combined and added that to the bonuses, before arriving at an ROI figure that represents something close to what MLB clubs can expect a bonus pool dollar to return. I used a rolling figure to smooth out any noise in the yearly results.

This gives us an idea of what a club’s accounting department would say their ROI was running an international operation in these years. There are a couple of other ways to look at this data. Going forward, we know that overages won’t exist. We also know the maximum that can be spent with hard caps in place. If we were to take the historic spending of 2016 and keep those signing rules, while also imagining that the talent of 2018 demanded the same outlay in bonuses and overages as the group in 2016, we could compare the two realities owners were considering in the most recent completed CBA negotiations:

You can see that there’s still a solid positive return even with historic spending levels, but owners negotiated to add a hard bonus cap to the international market, essentially doubling their ROI. The 2016 class was unique in that clubs were motivated to spend wildly in anticipation of the caps and because of that, a great class of Cuban players that couldn’t be duplicated today (four of our top 132 prospects are Cuban players from this class) drove much of that spending. That roughly $315 million expenditure may be the closest figure we’ll get to what clubs think the true value of a historically-talented class is in an open market with multiple motivated bidders. The market is now capped at half that figure.

We can also answer the question of what an international pool dollar is worth going forward. If we assume that the overhead of running a department is fixed, how should clubs think about the value of each additional dollar added to their bonus pool? We could take the table just above this one and use the projected actual 2018 row to figure out the ROI from $150 million in bonuses and the estimated $1.125 billion in value that will be created by the signees. The result is a staggering 650%. It appears that it takes about three years for the an investment in the international market to mostly mature in terms of trade value, though there’s a way to read this data where there’s further value gained in a 5-7 year horizon for full maturity.

This sort of analysis can get too close to quantifying the worth of humans in purely dollar terms, although going through the exercise in this way also helps to define what a fair market price is for someone’s service. 650% is a pretty abstract number to consider, so let’s compare it to an standard investment for wealthy individuals such as baseball club owners: investing in the stock market. An owner can invest roughly $5 million into international market each year and expect a median return of 650% after three years, while a strong 10% yearly compounded return in the stock market over that period would return a 35% return. That sort of return makes clear both the appeal for ownership of signing international players, and capping their bonuses. It also points to how wide a gap exists between the value these players generate for their clubs and their compensation relative to that value.

In the next part of this series, I’ll take a look at some of the best and worst signing classes, if we were to grade out every club’s international signing class over the last 30 years using the framework rolled out today.

We got a hold of the bonus slot values and, it follows, each team’s total pool amount for the upcoming 2019 MLB Draft. The PDF we acquired from an industry source was missing Washington’s comp pick for Bryce Harper at 138 overall, so we added that and manually recalculated each team’s pool total (which were incorrect on the PDF because of this missing pick).

(Update: After receiving additional clarification, it appears that Washington will not receive a comp pick for Harper; the pick that would have received as Harper compensation became the pick they gave up to sign Patrick Corbin.)

What follows is, first, the total draft bonus pool amounts for all thirty teams, followed by the individual slot values for each pick in the first ten rounds of the draft. Picks labeled “COMP” are compensatory selections for players lost via free agency or from last year’s unsigned draft picks. Picks labeled “CBA” or “CBB” are competitive balance picks (rounds A and B) allocated to teams in the spirit of parity. These can be traded, and several have been. In both the compensatory and traded competitive balance picks, we note the players for which the picks were received. The tables here will be updated if competitive balance picks change hands or if teams receive comp for a yet-to-sign free agent who received a qualifying offer, like Dallas Keuchel or Craig Kimbrel.