The 20-80 Scale, SABR Style

When scouts evaluate the players on the field, they use a 20-80 scale as shorthand to describe a player’s tools and/or his overall ability. Receiving a 50 on the scale means that one is major-league average, and for every 10 points up or down the scale, the scout believes the player is one more standard deviation above or below major-league average. An 80 is incredibly rare because one would have to be 3 standard deviations above the mean (or in the top 0.1-0.2 percent of players), and it’s a representation of the truly, truly elite. But the question becomes what those grades represent. When someone says that a player is an [insert grade], what should we actually expect them to do statistically at the major-league level? Armed with some advanced statistics and z-scores, I went to find out.

(Note: I used statistics from 2010-2012 because the timeframe is large enough to get a sample and small enough to stay within the recent run environment, and I used Russell Carleton’s measurements for each statistic to get a sample at least indicative of skill.)

Hit Tool

Hit Tool z BA Player BABiP Player
80 3 .336 Miguel Cabrera .383
70 2 .313 Josh Hamilton .357 Dexter Fowler
60 1 .290 Martin Prado .332 David Wright
50 0 .267 Rafael Furcal .306 Asdrubal Cabrera
40 -1 .244 Vernon Wells .280 Shane Victorino
30 -2 .221 Brendan Ryan .254 Mark Teixeira
20 -3 .199 .228

You can certainly argue with the statistics I choose for each of these tools, but I preferred to use statistics with which you are already familiar to simply give you an idea of the spread. In regard to the hit tool, I could have used Contact%, but while the hit tool is defined as the ability to make contact, we usually imply some semblance of production with it -it doesn’t matter that the player makes a lot of contact if he doesn’t do anything with it. Looking at the chart specifically, Cabrera was the only 80 hitter, and he was the only hitter within 15 points of the .336 mark. All the way at the bottom, you see a lack of examples for a 20 grade, but it shouldn’t be too surprising that a 20 hitter wouldn’t get enough PA (1000 for BA, 1500 for BABiP) to be on the list. It certainly doesn’t mean 20 hitters don’t exist.

Power Tool

Power Tool z ISO Player HR/PA Player
80 3 .294 Jose Bautista 6.6% Jose Bautista
70 2 .242 Joey Votto 5.2% Edwin Encarnacion
60 1 .191 Buster Posey 3.8% Kevin Youkilis
50 .140 Nick Markakis 2.4% Shane Victorino
40 -1 .089 Ryan Hanigan 1.0% Jose Altuve
30 -2 .038 Ramiro Pena -0.4%
20 -3 -.013 -1.8%

ISO was the stat of choice here as it is the most commonly used power metric, and I used HR/PA to give a look with a stat that didn’t involve speed (SLG, and therefore ISO, give singles, doubles, and triples different weights when speed could be the deciding factor between getting one or the other). Again, these are here to give you an idea of what a certain grade would merit in the majors. Back to the list, Bautista is the only player in either list to get an 80, but Giancarlo Stanton is so close in both (.282 and 6.2%) that you could go ahead and throw an 80 on it. As for the negative numbers, it’s mainly just a glitch in the numbers (those negatives obviously aren’t possible). Emmanuel Burriss had the least amount of power with a .007 ISO and a 0.0% HR/PA. Again, 20 power guys don’t stick on MLB rosters very long (180 PA – I took out pitchers – was the restriction here).

Speed Tool

Speed Tool z SB/3 Player BsR/3 Player
80 3 38 Ichiro Suzuki 9 Michael Bourn
70 2 29 Elvis Andrus 6 Rajai Davis
60 1 19 Chris Young 3 Andrew McCutchen
50 9 Jon Jay Yunel Escobar
40 -1 -3 Jason Kubel
30 -2 -10 -5 Adrian Gonzalez
20 -3 -20 -8 Ryan Howard

Speed isn’t much easier to isolate outside of the traditional 60-yard dash and home-to-first times, but as I said earlier, we expect a certain production from the tool by the time a player reaches the majors. BsR/3 (I divided the cumulative BsR by 3 to give you an idea of what it would take per season) gives you a better spectrum of players in this instance as it can go into the negative range (0 SB players are slow, but they aren’t necessarily equally slow), and it incorporates other instances involving speed, such as going first-to-third.

Defense Tool

Defense z-Score UZR/150 Player Fld/3 Player
80 3 22.8 17.9 Brett Gardner
70 2 15.7 Adrian Beltre 12.4 Michael Bourn
60 1 8.7 Giancarlo Stanton 6.9 Carlos Gomez
50 1.6 Casey McGehee 1.5 Drew Stubbs
40 -1 -5.4 Dan Uggla -4.0 Rickie Weeks
30 -2 -12.5 Asdrubal Cabrera -9.5 Michael Morse
20 -3 -19.6 -14.9

Defense might be the hardest tool to look at in this situation, and while it might have been better to look at this position-by-position, the sample (needing 2500 innings) was already pretty small. According to UZR/150, there are no 80 defenders in the game, and although Fld/3 names Gardner, he was the only one on the list. Perhaps 80 defenders are usually bad enough at offense that they don’t get the playing time necessary for this query, or we may simply need a bigger sample.

Arm Tool

Arm Tool z rARM/3 Player ARM/3 Player
80 3 8.8 Alex Gordon 8.5 Jeff Francoeur
70 2 5.9 Jose Bautista 5.7 Alex Gordon
60 1 3.0 Jayson Werth 3.0 Jayson Werth
50 0.2 Austin Jackson 0.2 Matt Kemp
40 -1 -2.7 Ichiro Suzuki -2.5 Matt Holliday
30 -2 -5.6 -5.3 Ryan Braun
20 -3 -8.4 -8.1

I added this in just to show you I wasn’t ignoring it. I used these arm ratings, but they only exist for outfielders and include accuracy as well as arm strength. Radar gun measurements and/or FIELD f/x velocity measurements would probably be more helpful for objectively measuring this tool.

Fastball Velocity

FB Velo z SP Velo Player RP Velo Player
80 3 97 100
70 2 95 Stephen Strasburg 97 Daniel Bard
60 1 93 Mat Latos 95 Drew Storen
50 91 Adam Wainwright 92 Ramon Ramirez
40 -1 88 Mike Fiers 89 Michael Wuertz
30 -2 86 Mark Buerhle 86 Pat Neshek
20 -3 84 Jamie Moyer 84 Livan Hernandez

This one is the easiest to isolate. While none of the pitchers have 80 velocities on average, several of them are obviously able to touch or even sit in that range for a period of time. As for how I split up the data, I originally did it for both SP vs. RP and RHP vs. LHP. Using SP and RP demonstrated the differences between the velocities necessary for starting and relieving, and while I hoped the LHP and RHP would show the differences between the two, I got some weird results. The mean for the two were 91.2 (RHP) and 90.5 (LHP), which was expected, but when I applied standard deviations, the SD for LHP was larger (probably due to the much smaller sample). A 60-80 necessitated a higher velocity from a LHP than a RHP, which didn’t seem to make sense. Using the mean velocity difference of about 1 mph, you can dock the grades shown above by 1 mph and use that for lefties if you so choose.


Control z SP BB% Player RP BB% Player
80 -3 1.7% 2.0%
70 -2 3.7% Roy Halladay 4.4% Sergio Romo
60 -1 5.7% Rick Porcello 6.8% Jason Motte
50 7.8% Derek Holland 9.2% Guillermo Mota
40 1 9.8% C.J. Wilson 11.6% Manny Parra
30 2 11.8% Danny Duffy 13.9% Tim Collins
20 3 13.9% Jonathan Sanchez 16.3% Carlos Marmol

I considered using Strike% here, but there are strategic reasons to throw balls and BB% is more commonly used when talking about pitchers. Again, I split up relievers and starters, and as you might expect, starters walk fewer hitters than relievers, which is probably at least one reason why they’re starting as opposed to relieving. You’ll note that there are no 80 control guys, and no one was even within 1% of reaching that grade. Perhaps 80 control (in its literal definition) is too high of a standard here, but there’s also the possibility that there is such a thing as “throwing too many strikes”, where pitchers somewhat choose to walk a guy even when they theoretically could avoid doing so.


The point of all of this was simply to give us all an idea of what it would actually take to reach a certain scouting grade. How rare is a literal 80? How hard is it to sustain such elite performance? What does it mean to be “plus” (60) in something at the major-league level? And how bad does one actually have to be to receive a 20? As prospect lists continue to roll out, you’ll hear these grades used frequently, and I just thought it was interesting and necessary to look at what it actually means to receive these scouting grades in our current environment.

Newest Most Voted
Inline Feedbacks
View all comments
Mike Axisamember
11 years ago