With two months of the minor-league season now complete and the draft also finished, it’s an appropriate time to publish a revised version of our preseason top-100 list. The list is below. Notes about methodology and specific players appear below that.
Eric and I have been working hard the last few months to rank everything that we can, including produce at the grocery store and our friends and family. As far as the rankings that appear on FanGraphs, we’ve had Prospect Week, headlined by the annual top-100 prospects list and complemented by nine other associated pieces, including preseason draft rankings that were updated yesterday to account for what’s happened in the last 10 weeks.
In that spirit of ranking and constantly updating, along with the desire to show our work and give readers tools to make decisions, today we are introducing THE BOARD.
This represents just the first pass at a feature that is likely to be modified and improved upon. Feel free to submit any suggestions in the comments. (I, personally, have a list of about a dozen additions for the coming months.) While we could have continued to develop this before releasing it, we felt this was something from which readers could benefit ASAP. It also serves as a bit of an apology for the team prospect lists taking so long. We’ll still be releasing an article for each team as planned over the next couple weeks. In the meantime, though, every organization is included in THE BOARD, updated with full tool grades. Readers, for example, can check out some of those to-be-published audits, like the record-breaking Padres’ list featuring 43 prospects.
A big hat tip is in order to dark overlord David Appelman for making our crazy ideas a reality.
We continue Prospect Week 2018 by trying to address a question frequently asked by fans of teams that have just graduated multiple high-level prospects — namely, where would those graduated prospects rank if they were still eligible for the Top 100? We usually don’t have that answer ready off the top of our heads since, as prospect analysts, we aren’t thinking about those players very much. We decided that wasn’t okay, though. So now, whenever we do an updated top-100 or midseason list, we will also provide an update on the prospects who have lost their eligibility in the previous/current year.
Below is our list of the top-100 prospects in baseball. Scouting summaries were compiled with information provided by available data, industry sources, as well as from our 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 rankings. For example, the gap between prospect No. 5 on this list, Fernando Tatis Jr., and prospect No. 35, Corbin Burnes, is 30 spots, and there’s a substantial difference in talent there. The gap between Ke’Bryan Hayes (No. 56) and Leody Taveras (No. 86), meanwhile, is also 30 numerical places, but the difference in talent is relatively small. Below the list is a brief rundown of names of 50 FV prospects who didn’t make the 100. This 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 like a prospect could reasonably have a best big league season of anywhere from one to five wins/WAR, then that would be “high” whereas someone like Colin Moran where it’s something like two to three wins/WAR is “low.” High variance can be read as good since it allows for lots of ceiling, or bad since it 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 variance. Here is a primer about the connection between FV and WAR.
If you’ve read any of the dozens of articles over the years trying to create a framework for player asset values (putting a dollar amount on a player’s value), you’re aware of the biggest weakness of this genre of article. Take a star player, run him through a marginal-value analysis, and you’ll be disappointed in what it says about his trade value. Before we jump into the Gerrit Cole and Andrew McCutchen trades, follow me down a thought-experiment rabbit hole.
Clayton Kershaw is the best pitcher in baseball and Steamer projects him as a six-win player next year. Using the roughly $9-10 million at which a win is currently valued on the open market, Kershaw is likely to produce something between $50 and $60 million of value next year; let’s call it $55 million. Would multiple teams bid that amount for his services on a one year deal? Probably yes, because there’s some surplus value at that salary for which the formula fails to account. It doesn’t consider, for example, either extreme payrolls (i.e. the Dodgers’ on one hand, the A’s on the other) or more critical spots on the win curve (moving an 87-win team to a 93-win team is worth far more revenue-wise than 65 to 71).
So what would the A’s bid? They had an $86 million payroll last year, and they obviously wouldn’t give nearly two-thirds of it to one player. Oakland’s value for Kershaw would likely be whatever the maximum is that they would pay for any player, but that number is much lower than what the Dodgers would spend, maybe $20 million. Granted, these are extreme cases, but it illustrates the limitations of using a one-size-fits-all dollar-per-win calculator in specific instances, even if it works fine in aggregate.
I point all that out to illustrate the fact that players aren’t worth the same to every team. Kershaw’s value, on which we all basically agree, varies by $30-40 million from the A’s to the Dodgers on just a one-year deal. So wouldn’t it follow that the A’s and Dodgers would value other players differently, too?
“Scouts vs. stats” is an expression that boils a complex, gray issue into clear black-and-white sides,in a way that’s familiar to those who follow political media. In the reality of front-office decision-making, however, this “debate” has been settled for years and the obvious answer was always “both.”
In fact, the issue has moved past simply using both. Until recently, if one suggested that a club should move further toward one side at the expense of the other, anyone could shoot back with a counter example of recent success from the other end of the spectrum. That’s a bit harder do now: two years removed from the Royals’ latest World Series appearance and three years out from the 2010-2014 Giants run, there isn’t a current standard bearer for the traditional point of view, even if that’s just cyclical and I’m using a somewhat subjective label.
The final four clubs standing in each of 2016 and 2017 — the Astros, Blue Jays, Cubs, Dodgers, Indians, and Yankees — would all rank among the top 10 of any industry poll of the league’s most progressive clubs. If you want to argue that their success is the result of variance, a blip, or mere coincidence, this development isn’t just the product of randomness. There’s an actual explanation. In these last two seasons, we’ve seen a fundamental change in the style of play (a greater emphasis on the air ball, quick hooks on starters, more aggressive bullpen usage, etc.) — particularly in the postseason. A progressive club, by definition, will adapt more quickly to such changes.
Over the next several months, I’ll be releasing comprehensive reports on each major-league club’s farm system and the prospects therein. Implicit in this is that I will be ranking the prospects – both within each farm system and across baseball – based on my own evaluation of the players as well as that of industry sources. The players will be ordered by their “Future Value” grade. This Future Value methodology was brought to FanGraphs in 2014 by former Lead Prospect Analyst, Kiley McDaniel (reggaeton horn).
If you’d like to read what is essentially the Book of Genesis on Future Value, then I’ll direct you here for McDaniel’s (reggaeton horn) 2015 top-prospects list for an explanation of FV and its merits, as well as here for discussion about the 20-80 scouting scale.
In short, Future Value attempts to combine a prospect’s potential (reasonable ceiling and floor) as well as his chance of realizing it (including injury-related risks or proximity to the majors) into one tidy, value-based number.
There are some pretty obvious issues with this system, some of which are practical, others more personal, and I’ll touch on those briefly before explaining why I’m retaining the system.
I wrote yesterday about the how the shelf life of draft rankings affects the finished product, using my “guy” from this year’s draft, Vanderbilt righty Carson Fulmer, as an example of a guy typically under-appreciated by this process. My history of scouting Fulmer goes back four years to his high school days, but my history of zeroing in on this type of pitcher goes back eight years.
Taking a Page from Wall Street
Nassim Taleb’s The Black Swan came out in 2007 and I read it toward the end of that year. Taleb made a lot of money during the stock market crash in 1987 and again during the financial crisis that started in 2007, a crisis he predicted in The Black Swan. The way he made his money is the underpinning of the book: better understanding how very rare events happen.
The human brain simplifies complex situations, which can often help us and conserve energy, but also makes us vulnerable when a seemingly unimportant piece of information is smoothed over by many individuals. Taleb names the unlikely event that few see coming a Black Swan, referring to the collective surprise exhibited when a black version of the (presumed exclusively) white bird was found in another part of the world.
Scouting Explained: Introduction, Hitting Pt 1 Pt 2 Pt 3 Pt 4 Pt 5 Pt 6
When I started here just last month, I promised I would write a comprehensive series of articles explaining every part of the 20-80 scouting scale. This is the beginning of that series.
Background
The invention of the scale is credited to Branch Rickey and whether he intended it or not, it mirrors various scientific scales. 50 is major league average, then each 10 point increment represents a standard deviation better or worse than average. In a normal distribution, three standard deviations in either direction should include 99.7% of your sample, so that’s why the scale is 20 to 80 rather than 0 and 100. That said, the distribution of tools isn’t a normal curve for every tool, but is somewhere close to that for most.
The Basics
You’ve probably heard people call athletic hitters a “five-tool prospect.” While that is an overused and misunderstood term, they are referring to the 20-80 scouting scale. The five tools for position players are 1) Hitting 2) Power 3) Running 4) Fielding and 5) Throwing. The general use of the “five-tool” term is when all five are at least average (which is more rare than you’d think) and I generally only use it when all five are above average. It’s a shockingly small list of players over the history of baseball that have five plus tools, but if you ask around, scouts will tell you Bo Knows.
