An Update to Prospect Valuation

Over the years, a good deal of effort has been put into determining the value of prospects. Victor Wang, Scott McKinney (updated here), Kevin Creagh and Steve DiMiceli together, and Jeff Zimmerman have all published work on the subject, roughly in that order.

The reasoning behind such efforts is fairly obvious: teams trade prospects for proven players all the time. Finding an objective way to evaluate those trades is useful to better understanding how the sport operates. Indeed, FanGraphs has benefited from those prospect-valuation studies on multiple occasions.

With another year having passed, I’ve attempted to build on the work of others and produce updated valuations of my own. Previous efforts have been very helpful in the process, while the input of prospect analysts Eric Longenhagen and Kiley McDaniel has helped me find results that would be most useful.

In building this study, I set out with the following aims:

• To separate players into as many useful tiers as possible without creating unnecessary distinctions.
• To use as much data as possible so long as it was useful and likely still relevant today.
• To make the valuations as forward-looking as possible.
• To recognize that player development is not linear and that players appearing on prospect lists vary from major-league-ready to raw, Rookie-level talents.

To those various ends, here are some of the parameters of this study:

1. Baseball America’s top-100 lists from 1996 to 2010 serve as the foundation for prospect grades.
When I started the study, I looked at the lists dating back to 1990, separating out position players from pitchers and organizing by year. I found that the evaluations from the earlier part of the 90s — especially those for pitchers — had considerably worse outcomes than those that came after. I debated whether or not to throw out the data. Eventually, though, I decided that since 15 years of prospect numbers were showing decidedly different results, and that there was considerable turmoil occurring within the sport during that time — expansion, a strike, and a lockout — it seemed reasonable to toss the earlier years and go with the assumption that the 1996-2010 lists more accurately represented prospect evaluation today and going forward than the rankings of 25 years ago.

2. No prospect ranking was thrown out.
Some studies have taken only the final prospect valuation for an individual player and not the previous seasons’ rankings, as well. I thought it was important to use every data point possible, however. Just because a player is ranked 85th one season and then first the next year shouldn’t render the No. 85 ranking moot. Removing previous rankings throws out a lot of potentially valuable information. Many players move up the rankings from one season to the next season and capturing that effect is important to understanding the enterprise as a whole

3. Players were separated into tiers based on the 20-80 scouting scale.
Because Baseball America didn’t put grades on players for many of the years considered in this study, it was necessary to make estimates after the fact. Fortunately, in a piece he wrote for the 2016 Hardball Times Annual, Jeff Zimmerman approximated historical grades by looking at the publicly available grades BA had used in more recent seasons. To make this as forward-looking as possible, I consulted with Eric Longenhagen and Kiley McDaniel to get a sense, on average, of how many prospects in each tier are typically populating the minors. We came up with this:

Separating players into group by scouting grade as opposed to a more arbitrary tiering system (for example, simply dividing players into groups of 10 or 25) has one distinct advantage — namely, that it more accurately reflects how talent is distributed. The gap in promise (and observed future value) between the 1st- and 10th-ranked prospect is often larger than the 50th- and 80th-ranked ones. Using the scouting grades allows us to capture these differences. And by grouping all of the 50-grade players together, for example, we get a lot more data points for that group and hopefully achieve more accurate results in the process.

Method

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.

Because a lot of that might be confusing, here’s an example of the methodology applied to Jason Heyward’s career:

Results

What follows are the present-day values of prospects based on the study performed above. The results are presented in present-day WAR and translated to a rough dollar figure based on $9 million as the cost of a win on the free-agent market. Keep in mind that the dollar figure isn’t a direct value, but rather equivalent value of a prospect relative to the free-agent market. Part of the reason prospects have such tremendous value is due to the suppressed salaries permitted by the CBA until a player has reached six years of service time. By translating the WAR figure into a monetary value, we can compare the value of prospects with the values of major-league players and their contracts. These values likely roughly approximate what an individual player might get as a signing bonus if he were declared a free agent and teams could only provide a signing bonus instead of a long-term contract.

For those of you who have read the piece up to this point, thank you. Hopefully it helped answer some questions you might have. For those who just scrolled down to see the dollar values, here you go:

As you can see, there’s an observed relationship between scouting grades and observed future WAR. A 70-grade position player is best, followed by a 70-grade pitcher. Interestingly, pitchers in the 60-65 FV range come out pretty much the same as their position-player compatriots. Top-level pitchers tend not to bust entirely, generally producing some kind of value. Once you drop a bit lower to the 55s and 50s, however, position players come out ahead, though that’s due less to pitchers busting more often than position players and more because position players are more likely to become stars. Over the past seven seasons, for example, roughly twice as many position players have reached the 20-win threshold than pitchers. There just aren’t as many slots to go around.

This post will be followed by two others, including one dedicated to 40- and 45-grade players, plus a second designed to value team farm systems as a whole.

Longenhagen and McDaniel go to great lengths to rank prospects within tiers — and not just present players in tiers with no further commentary — so while the numbers come out as one value per valuation, the rankings would serve little purpose if we simply placed the same value on all players with a 50 grade, particularly giving a pitcher ranked 55th a $21 million value while giving a hitter ranked 99th a $28 million value.

Sliding the numbers down the scale produces the following for Longenhagen and McDaniel’s top-131 prospects: