Valuing the 2017 Top 100 Prospects by Dave Cameron March 13, 2017 Earlier this morning, Eric Longenhagen rolled out his list of the top-100 prospects in baseball, with Red Sox-turned-White Sox prospect Yoan Moncada at the top of his rankings. Helpfully, Eric’s rankings include the FV grade for each player, so that we can see that he really does see a difference between Moncada and the rest of the pack, as Moncada was the only prospect in the sport to garner a 70 grade. As Eric notes in his piece, the grade is really the more important number here, as the ordinal ranking can create some false sense of separation, where players might be 20 or 30 spots apart on the list but offer fairly similar expected future value. The FV tiers do a good job of conveying where the real differences lay, highlighting those instances when Eric actually does see a significant difference between players, versus simply having to put a similar group of prospects in some order regardless of the strength of his feelings about those rankings. But while the FV scale is helpful in binning players, it doesn’t do much to convey the differences between the tiers themselves. How much more valuable is a 60 than a 55? Or is a team better off with one elite 65 or 70 FV prospect or a multitude of 50-55 types? These are interesting questions, and ones that teams themselves have to answer on a regular basis. To attempt to answer those questions, we’re proud to announce that we’ve licensed the prospect valuation model on which Kevin Creagh and Steve DiMiceli have worked for the last few years. Kevin and Steve have advanced the framework of previously published research on draft pick and prospect valuation, and have created a system that attempts to quantify the expected future value of a prospect based on how similarly rated prospects have performed in the major leagues. The model looks at the level of expected performance and the expected cost of a player during the years before he reaches free agency, and then estimates a player’s value to his organization during that time. In the previous iterations of this model, the model based the similarity of current prospects to players with similar rankings from Baseball America’s annual top-100 list. Thanks to some tireless work from Kevin this winter, assigning assumed FV grades to every player ranked on BA’s top 100 from 1994 through 2007 based on that player’s ranking, performance, and the scouting reports available at the time, the model is now able to project value based on a player’s FV grade rather than simply his ordinal rank. This change most significantly alters the expected values of the guys at the very top of the list, as the previous bins lumped all top-10 prospects together into a single bin, while the FV grade allows for separation between the truly elite, once-every-10-years kind of prospect and guys who are good but not quite as special. For instance, Eric’s grades make it clear that he sees a tangible difference between Moncada and every other prospect in the top 10, and there’s a 10-point difference in FV grade between Moncada and Gleyber Torres or Victor Robles, but all three would have been assigned the same value under the prior “top-10 hitter” tier. By moving the valuations to the FV scale, we can more reasonably account for real differences between players who may be ranked similarly but still have very different expectations of future value. As the chart of expected value below shows, the historical performances of the very best prospects is quite a bit different than players even just one rung down, which is why teams are so intent on developing high-end prospects. Historically, elite prospects have returned significantly more value than just good prospects, and this model attempts to capture those differences. Estimated Prospect Value by FV Grade Grade Hitter Pitcher 75 $175M $83M 70 $107M $62M 65 $70M $62M 60 $60M $34M 55 $38M $22M 50 $20M $14M 45 $11M $13M As you can see, Kevin didn’t feel that any player in the 1994-2007 sample was considered an elite enough prospect to generate an 80 FV grade, so it’s not in the chart. Alex Rodriguez and Andruw Jones were the hitters who got the closest, both receiving 75 FV grades in Kevin’s estimation, but with a sample size of two, you can put a very large error bar around that $175 million valuation. Prospects that good are so rare that nailing down their actual value is something of an academic pursuit anyway, as it’s almost impossible to see a team possessing that kind of young talent actually trading them anyway. Once you get down to the lower-tier grades, though, the sample size grows large enough that we can start to see some real trends. As is generally thought to be true, elite hitting prospects are simply more valuable than highly graded arms, as hitters just don’t get hurt at the same rate, and thus, they are far safer investments. You can see the large differences in expected value between hitters and pitchers at the top of the chart, though this lessens as you go down towards the lower grades; the fact that “low upside” pitchers can seemingly develop into frontline starters more easily than “low upside” hitters can turn into superstars reduces the gap between them when it comes to good-not-great prospects. Interestingly, you’ll note that the expected value for pitchers with 65 and 70 FV grades are identical. Pitchers that graded out as an assumed 70 FV — based on their ranking, performance, and scouting reports at the time — actually performed worse than 65 FV pitchers, but like with the 75 hitters, the sample size was too limited to draw firm conclusions, so we’ve simply merged the 65/70 FV pitchers into one larger tier to mitigate the sample-size issue. Based on the historical data, it appears to be easier to identify real differences in elite hitters than elite pitchers, or perhaps the attrition rate of pitchers is so high that the marginal difference in aiming for a better pitching prospect isn’t as large as it is with a lower-risk hitter. Now, it’s important to note that models like this are built on a tremendous number of assumptions, many of which can be reasonably debated. Kevin had to put a lot of work into translating BA’s historical information into an assumed FV grade, but in the end, it was still a subjective evaluation. To translate the performance of players in those FV groups into a valuation model requires assumptions about the market price for a win, the discount rate used to account for the long-term nature of a prospect’s return, and the expected cost of a player during his arbitration years. The model includes all of these variables, but nailing down those numbers is far from an exact science, and the results from the model should absolutely be thought of as estimates with some significant variance. I would not advise anyone to look at these valuations as the definitive final number of a prospect’s worth. But we do think looking at the historical performances of similarly graded prospects (as best as we can infer, anyway) helps to provide some context for the differences in expected value between types of prospects, and this data emphasizes just how valuable the very best prospects in baseball really are. Below, we’ve taken Eric’s top 100 and merged the FV grades he gave each player on the list with the valuations from Kevin and Steve’s model, and are presenting them with their rankings, grades, and valuations in one table. When the team reports are done, we’ll also use this model to look at organizational valuations; because non-top-100 prospects are worth enough to change the calculus, I wouldn’t suggest doing an organizational ranking just based on the names below, especially since a large number of players omitted from the list will have received the same FV grade as players ranked Nos. 73-100. We’ll be integrating these values into the prospect data on the site, as well, and are thrilled to be able to feature Kevin and Steve’s work here on FanGraphs going forward. So, with all those words out of the way, here is how the prospect valuation model sees the expected future value of the players Eric ranked in his top 100. Top 100 Valuations Rank Name Team Position Age FV Value 1 Yoan Moncada CWS INF 21 70 $107M 2 Andrew Benintendi BOS OF 22 65 $70M 3 Amed Rosario NYM SS 21 65 $70M 4 Dansby Swanson ATL SS 23 65 $70M 5 Austin Meadows PIT OF 21 65 $70M 6 Alex Reyes StL RHP 22 65 $62M 7 Gleyber Torres NYY SS 20 60 $60M 8 Victor Robles WAS CF 19 60 $60M 9 J.P. Crawford PHI SS 22 60 $60M 10 Anderson Espinoza SD RHP 18 60 $34M 11 Ozzie Albies ATL 2B 20 60 $60M 12 Yadier Alvarez LA RHP 20 60 $34M 13 Cody Bellinger LA 1B 21 60 $60M 14 Brendan Rodgers COL SS 20 60 $60M 15 Eloy Jimenez CHC OF 20 60 $60M 16 Lewis Brinson MIL CF 22 60 $60M 17 Willy Adames TB SS 21 60 $60M 18 Francis Martes HOU RHP 21 60 $34M 19 Lucas Giolito CWS RHP 22 60 $34M 20 Corey Ray MIL OF 22 60 $60M 21 Michael Kopech CWS RHP 20 55 $22M 22 Rafael Devers BOS 3B 20 55 $38M 23 Manny Margot SD CF 22 55 $38M 24 Vladimir Guerrero TOR 3B 17 55 $38M 25 Cal Quantril SD RHP 21 55 $22M Rank Name Team Position Age FV Value 26 Tyler Glasnow PIT RHP 23 55 $22M 27 Mickey Moniak PHI OF 18 55 $38M 28 Reynaldo Lopez CWS RHP 22 55 $22M 29 Jason Groome BOS LHP 18 55 $22M 30 Nick Senzel CIN 3B 21 55 $38M 31 Riley Pint COL RHP 19 55 $22M 32 Jorge Alfaro PHI C 23 55 $38M 33 Delvin Perez StL SS 18 55 $38M 34 Clint Frazier NYY OF 22 55 $38M 35 Ronald Acuna ATL CF 19 55 $38M 36 Brent Honeywell TB RHP 21 55 $22M 37 Francisco Mejia CLE C 21 55 $38M 38 Kyle Lewis SEA OF 21 55 $38M 39 Robert Gsellman NYM RHP 23 55 $22M 40 Blake Rutherford NYY OF 19 55 $38M 41 Kolby Allard ATL LHP 19 55 $22M 42 Alex Verdugo LA CF 20 55 $38M 43 James Kaprielian NYY RHP 23 55 $22M 44 Jose DeLeon TB RHP 24 55 $22M 45 Brad Zimmer CLE CF 23 55 $38M 46 Mitch Keller PIT RHP 20 55 $22M 47 Jeff Hoffman COL RHP 23 55 $22M 48 Kevin Maitan ATL 3B 17 55 $38M 49 Leodys Taveras TEX CF 18 55 $38M 50 Josh Bell PIT 1B 24 55 $38M Rank Name Team Position Age FV Value 51 Ian Happ CHC 2B 22 55 $38M 52 German Marquez COL RHP 21 55 $22M 53 Sandy Alcantara StL RHP 21 55 $22M 54 Ian Anderson ATL RHP 18 55 $22M 55 Triston McKenzie CLE RHP 19 55 $22M 56 Matt Manning DET RHP 18 55 $22M 57 Luis Ortiz MIL RHP 21 55 $22M 58 Isan Diaz MIL 2B 20 55 $38M 59 Josh Hader MIL LHP 22 55 $22M 60 Braxton Garrett MIA LHP 19 55 $22M 61 Aaron Judge NYY RF 24 55 $38M 62 Max Fried ATL LHP 23 55 $22M 63 Kyle Tucker HOU OF 20 55 $38M 64 Yohander Mendez TEX LHP 22 55 $22M 65 Amir Garrett CIN LHP 24 55 $22M 66 Nick Gordon MIN SS 21 55 $38M 67 Franklin Barreto OAK SS 21 55 $38M 68 A.J. Puk OAK LHP 21 55 $22M 69 Christian Arroyo SF 3B 21 55 $38M 70 Luiz Gohara ATL LHP 20 55 $22M 71 Jharel Cotton OAK RHP 25 55 $22M 72 Matt Strahm KC LHP 25 55 $22M 73 Dom Smith NYM 1B 21 50 $20M 74 Walker Buehler LA RHP 22 50 $14M 75 Hunter Renfroe SD OF 24 50 $20M Rank Name Team Position Age FV Value 76 Adrian Morejon SD LHP 18 50 $14M 77 Justin Dunn NYM RHP 21 50 $14M 78 Fernando Tatis, Jr. SD 3B 17 50 $20M 79 Anthony Alford TOR OF 22 50 $20M 80 Brandon Woodruff MIL RHP 23 50 $14M 81 Carson Kelly StL C 22 50 $20M 82 Andres Gimenez NYM SS 18 50 $20M 83 Kevin Newman PIT SS 23 50 $20M 84 Lucas Erceg MIL 3B 21 50 $20M 85 Chance Sisco BAL C 22 50 $20M 86 Tyler Beede SF RHP 23 50 $14M 87 Dustin Fowler NYY CF 22 50 $20M 88 Anthony Banda ARI LHP 23 50 $14M 89 Willie Calhoun LA 2B 22 50 $20M 90 Raimel Tapia COL CF 22 50 $20M 91 Jorge Mateo NYY SS 21 50 $20M 92 Jahmai Jones LAA CF 19 50 $20M 93 Mike Soroka ATL RHP 19 50 $14M 94 Zack Collins CWS C 21 50 $20M 95 Juan Soto WAS OF 18 50 $20M 96 Sean Reid-Foley TOR RHP 21 50 $14M 97 Justus Sheffield NYY LHP 20 50 $14M 98 Carson Fulmer CWS RHP 22 50 $14M 99 Ke’Bryan Hayes PIT 3B 19 50 $20M 100 Jesse Winker CIN OF 23 50 $20M