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
| 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.
Love.
Defense = fielding + position. Stanton and Uggla are much closer defensively after accounting for position.
Really enjoyed everything else.
Is that necessarily true from a scouting perspective?
It seems to me that scouts tend to grade defense relative to “natural” position rather than adjusting for difficulty on the defensive spectrum. But I’m also not a scout.
I think you’re mostly right, but there may also be a position factor. BA rated Bogaertes as a 55 defender; I would think he would end up being below average at shortstop. But if Sky were right, some of those catcher defense grades would be pretty awful.
From a scouting perspective, a lot of scouts will look at them from each individual position. It would have been more interesting to look at from each position, but space and sample (though I could have stretched it out to 5 years or something) made things a bit more difficult.
Usually, the grades on fastballs aren’t for velocity but the overall pitch, which is more complicated than simple velocity.
Depends on how one looks at it. Usually, a scout will break it up into velocity, movement, and command with another grade for the pitch overall. Here, I was just looking at velocity.
Why not use Pitch Values?
Not so technically speaking and strictly within the context of this post…
Strasburg is to Starting Pitching what Bard is to Relief Pitching. Oh how I wish this could be true for Bard.
For the first five months of the 2011 season, it was the case!
How would you place Total WARP on a 20-80 Scale. I was thinking about this when reading Baseball America’s Prospect Guide
Here is what I came up with
80- 8 WARP- A Hall of Fame/Perennial MVP Type Talent- A Top 5 Player in the Game on a yearly basis. Mike Trout/Justin Verlander
75- 7 WARP-Perennial All-Star- A top 10 Player in the game.
70- 6 WARP- All-Star- A top 20 Player in the game
65- 5 WARP-A top 40 player in the game
60- 4 WARP- A top 75 player in the game
55- 3 WARP- A above average starter. A Top 125 player
50- 2 WARP- A league average starter- A Top 200 Player
45- 1 WARP- A below average starter/plus back-up or back-end starter.
40- O WARP- A fringe MVP Player (Back-Up Catcher/Long-Reliever/Pinch-Runner)
35- -0.5- WARP- A 4AAAA Type Talent (Might or Might not be worth having on a 40 Man Roster
30/25/20 Organizational Filler- Used primarily to fill out Minor League Rosters.
I’m not claiming this to be a definitive guide. I’m just wondering if these numbers seem to be in the right ball-park.
Looks about right to me, SC!
Fine article, Mark. I’m not sure about your “hit tool” comment, though. It was my understanding that hit tool translates not into “ability to make contact” (i.e. simply avoiding strikeouts), but rather the ability to hit for average — which incorporates but isn’t limited to contact-making.
I absolutely could be mistaken, though.
FWIW, I use this scale to introduce people to WAR:
10 All-time great season
8 MVP finalist
6 MVP candidate
4 All-Star caliber
2 league average
0 scrub
I’m considering doing another post similar to this rating other metrics (OBP, wOBA, WAR, etc.). Would people be interested?
Yes
Yes
Yes, very cool stuff, Mark. I love the beer and tacos analogy from Dayn Perry at BP. Seeing articles that combine the two, especially with familiar names as real life examples is pretty rad. More, please!
Yes. This is great work. Nice job.
Absolutely!
I will be very interested to see how Trout does this year, will last year be his best??
I’m guessing you didn’t mean fringe MVP player for 40 and probably just meant fringy player for any roster. That’s a fair assessment though. I’m not sure, however, that judging a player’s production as a whole (No 80 tools, but a bunch of 60s and 70s equals an 80) is a fair assessment, but it’s a solid guess.
Silly me- Fringe MLB Player. I realize it’s not perfect since the 20/80 model is used to evaluate tools. I just found the distinction interesting when reading Baseball America’s Prospect Guide. I figured I’d throw numbers around.
This is my favorite article I’ve read in a long long time. I think this really bridges the gap between the perceived SABR/Scout war that never really existed in the first place while also giving a statistical measure to a scale that, really, lets be honest, we all love to use and observe.
I remember back when Vlad Guerrero came up and scouts would joke that his arm required another category unto itself? Because of how strong it was? No because you never know where it was going to end up; either an on the fly dart from the right field foul pole, or somewhere in the bleachers in center.
Thanks for this Mark. Fantastic work.
Agreed. Well done, Mark.
Agreed. One of the best of the early season so far. Nice work. Interestingly, Baseball American slapped an “80” grade on G. Cole’s fastball today in their Top 100 reveal. Would that mean he’d likely average >95+ mph?
From what I’ve read, an 80 fastball consistenly sits in the upper 90’s. I would assume averaging 97+ is the criteria.
Thanks for the kind words, everyone. As for Cole, an 80 is put on his fastball because he can hit fairly regularly 97 and above. Whether or not it “averages” that is another story. Would be interesting to have minor-league PITCH f/x data. Pitchers also start to lose velocity after the age of 21-22, so by the time some guys get to the majors, the higher velocities have diminished a little due to age/use.
Does the fastball tool only grade velocity or does movement come into play?
Again, it depends on what you’re grading. Above, I was just looking at velocity. But scouts will often grade velo, movement, and command along with an overall grade.
A++ for effort. Love the idea.
Awesome article.
What do you make of Mike Trout’s 12 BsR score last year? Since a 9 BsR average = 80 Speed, does Trout’s score imply a rating-system-busting 90 speed, or 4 standard deviations above the mean? I mean, assuming he can maintain that level, of course.
btw, I don’t think a normal distribution applies to steals. It’s extremely skewed towards low steal numbers, and obviously there’s no such thing as negative steals. Actually, you could say something similar about a lot of these categories.
I think it’s possible to be better than an 80, but it’s so rare anyway that it’s almost not worth doing anything else than just admiring it. Trout did a lot of things to impress last season, and his success on the bases was one of those things.
As for the steals, it didn’t really work out for some of the reasons you mention, but I included it to give a different look. Guys who are really slow won’t steal at all, and if a two players rate as a 35 and a 20, they’ll have 0 stolen bases because there’s no way to be negative. BsR is better because it starts taking into account other baserunning events that even slow runners can’t avoid.
http://en.m.wikipedia.org/wiki/Chi-squared_distribution
Mark, this article is beautiful. My only suggestion is to do a bit of research on non-normal distributions (chi squared makes sense with steals). Many recommended this on the steals, but i would also say to take a look at the rest (map real results against normal distributions first, this will get you most of the way there).
Funny how the scouts eyes and the statistical distributions are almost perfectly in line.
Putting this kind of work together with analysis over time could provide significantly improved forecasting methods. Very cool stuff.
Why not LD% for contact?
LD% is very volatile and subject to scoring anomaly.
Yep. What Dan said. It was in consideration, but the needed sample for batted ball statistics to stabilize is something like 9 years.
I’m a little confused, on Teixeira’s fangraphs page it says his babip is .250, here it says .254, but if I did everything correctly, it’s actually .258.
I believe those are parameters Max, and not their actual individual numbers. Those are the specific marks that separate the standard deviations.
Max, what wilt said. His .254 BABiP is based on the last 3 seasons.
If you need a 20 runner, it’s Matt Wieters.
Or David Ortiz. Keith Law uses him as an example on his top 100.
It blows my mind that Jason Kubel is a 40 on this scale for speed. He is only one standard deviation below average?
This is the real divide between traditional and sabrmetrics – the skill vs tool divide. Kubel may be slow, but he could be smart about base running which improves his “speed” grade. His BA speed would be 20 or 25, but his fSpeed grade would be 40. Stanton is a 80 BA power, but not quite there for fPower. Bautista’s fPower is higher than his BA Power.
The hitting mappings work well, the pitching, not so much. If only the run values on types of pitches weren’t so unusable.
Then Jesus Montero must be a legit 10
For power, shouldn’t you use HR/AB not PA? Seems like taking a walk or getting hit by a pitch shouldn’t count against your power.
You’re probably right. I’ll look into it.
It should probably be HR per batted ball, as you would in theory want to evaluate HR power completely independent of strikeouts.
I’ve done similar to this with minor leaguers. If you add HBP% onto the BB% you push the results away from 0% and you start to see more pitchers who are 2 to almost 3 standard deviations better than the mean. In essence it lessens the “right skewness” of the BB% distribution a little making it a bit more “normal”.
I expect Andrelton Simmons will live up to his 80 defense after two more seasons worth of data.
That’s not how you regress stats that have a small sample size.
Mike Newman has stated multiple times that his scouting contacts all claim Andrus as the best defensive SS in MLB. And it is rumored that the Rangers tried to get Simmons just to flip him to Arizona. Atlanta fans need to temper their expectations.
Not trying to denigrate Atlanta fans specifically, but last off-season the consensus groupthink amongst Atlanta fans was that Jair Jurrjens was an Ace level pitcher and the fanbase in general couldn’t understand the rest of the baseball world’s lukewarm reception of his abilities. (This came about in discussing a possible Adam Jones to Atlanta trade scenario)I suppose it is why the term fan comes from fanatical.
If you’re talking about the people who post on the AJC blogs then sure. Anyone who was even mildly sabr inclined knew that Jurrjens was riding the luckiest comet in the galaxy. As for Simmons, only time will tell my friend 🙂
This article is interesting and certainly highlights some of the major disagreements between the scouting community and the SABR community with regard to individual players (e.g., I don’t think any scout would call Drew Stubbs a 50 grade CFer).
Also, I really don’t think BABIP is a good way of measuring the hit tool. Dexter Fowler’s 70 grade is a good example of why.
It is a good way of “proving” BABIP though!
The Stubbs grade stood out to me as well. His MO around the league is plus range in CF but terrible at the plate where he K’s too much and doesn’t walk nearly enough. If he were an average defensive CFer I don’t think he would get the ABs that he gets.
There’s not an 80 control pitcher because Rivera was hurt.
I was going to say Rivera has nothing on Cliff Lee, but as it turns out they’re essentially equals. But if 2010 Cliff Lee doesn’t have 80 control, then 80 control doesn’t exist.
Shouldn’t the true valuation on fastball incorporate movement? Velocity means jack if it doesn’t move.
usually scouts will give separate grades on FB velo and movement. can then piece together overall FB effectiveness. also need to consider command / control
Fantastic.
great article. my only qualm would be the use of stats that don’t fit the normal distribution
Jose Bautista tearing these lists UP!
would like to use the Fans fielding grades translated into 20-80 scores. Always wanted to see a wisdom of the crowd scouting report with actual scout grades(!)
All the Molinas add up to a 20 for speed.
No, 3×0=0.
What do the distributions look like?
This idea could make an already great article even better. Could you show a graph of the distribution of data points around the mean? And when you hover over a point, it tell you what player the data point refers. That would be cool. I don’t know if it’s practical to implement though.
Terrific piece, Mark. I really enjoyed this. Enjoyed the discussions in the comments it provoked as well.
So good.
Great article, and very good insight. I look forward to cross-referencing top 100 lists with this article. Nice work.
This is great. We used the scouting scale this year in out draft kit to scale risk / reward for fantasy players. I use it all the time, because once you become confident with it it holds all sorts of utility. Thanks for running those numbers for us.
Am I to believe that scouts actually calculate standard deviations of the five tools when assigning ratings?
Yes! and they think in logarithms, too!
Haha. Probably not. But when they give grades, they usually have an idea of what stats they’ll produce with those tools (or may produce, given development). This just gives us a more precise and current look.
Peter Bourjos is an 80 defender, imho. You didn’t see him on the field last year but in 2011 he was spectacular on defense.
This is a great article, insofar as it actually helps me understand and think about the game I love in a new way. Thanx!
I feel like part of the point Mark was making is that 80 grades are meant to be rare. Look at the hit tool. It is Miguel Cabrera. That is it. The power tool. Jose Bautista and probably Giancarlo Stanton. Really, for someone to get an 80 grade they are the best player with that tool of all the players in baseball. In general 80 grades are tossed around a little too liberally. 60 and 70 grades should be seen as very high praise as well.
This may have already been addressed, but I would strongly suggest you use sample quantiles rather than normal approximations so you don’t get ridiculous results like negative HR/PA.
Jerry Dipoto developed this years ago. He translated the 20-80 scale into performance, and even used OPS+ and ERA+ extensively in his metric, (as well as all the traditional).
It was a terrific tool for the scouts to really get a handle on what they were actually projecting.
It always amused me how many people on this very site criticized the heck out of Dipoto for some press conference comments he made about Joe Saunders and “winz” when he made the Haren for Suanders/Skaggs/Corbin trade.
Anyway, great article, and glad to see the concept advanced. But I couldn’t pass up the opportunity to point that things are not always as they seem to appear in this fabulous, mystical game we love.
Well done.
Great article.
You get a gold star!
Very useful. I was surprised, though, to not see Aroldis Chapman in the relief pitchers for fastball velocity. At least by the popular conception, if he isn’t three standard deviations above average, I don’t know who would be… Is it possible that he doesn’t really use that express-speed fastball very much? The two games I saw he certainly did, though.
Again, these are based on averages. There are many nights where Chapman has more than enough fastball to grade out as an 80.
I take it that Chapman (to name one) averages a lot less than 100+mph. On the other hand, it also surprises me not to see Kimbrel – I know his average is way up there, definitely not “only” 95mph. Is there a resource for finding the averages?
Well, these are multi year averages. I’d bet that Kimbrel averaged closer to 90 than 100 in 2011.
I love this kind of stuff.
Best…user name…ever…
Mark, Jason Parks at BP broke down the Power tool as follows, by HR:
Power (HR/Year):
80: 39+
70: 32-38
60: 25-32
50: 17-25
40: 11-17
30: 5-11
20″ Up to 5
Question: does the Power tool not take into account all extra bases (“doubles power”) or just HR? For example, do you evaluate guys like Billy Butler and Brian Roberts just on HR alone?
What Jason described was a shorthand way of describing the power tool. A lot of scouts don’t really think in terms of ISO, etc. HR will give you the basic idea of a guy’s power, but when scouts grade out power, they’ll take everything into consideration. It’s just a point of direction, essentially.
Home runs make it easier. Take a speedy hitter for example. If he is batting leadoff, he is probably going to be able to rack up some extra doubles and maybe triples that if he were batting say 7th, he wouldn’t be able to because runners would be on base in front of him that he couldn’t out run to gain those extra bases. That isn’t power at play, that is his speed at play. Home runs are home runs (assuming neutral field environments of course). While “doubles power” certainly can boost overall numbers, home run power exists all over the place, no matter the situation. Doubles power doesn’t.
Oh, please, not the clogged base paths theory. The speed difference between MLB players is nowhere near 150-200%.
I never said it was. But some guys can add doubles/triples that others can’t. But they aren’t showing more power, just more speed. Maybe it is only 5-7 a year, but it is showing up and it isn’t actually showing more power, but more speed.
This is terrific. Thanks for the great work, I’d love to see more like this.
Would 2009/10 Ubaldo Jimenez have gotten an 80 fastball grade?
Has anyone at fangraphs tried to do an ‘all-time tools player’ write-up? I’m thinking Mays has to be at or near 80 in every tool, both from a ‘tools’ perspective and SABR. Bonds (with an average arm) and Griffey probably aren’t far behind. Young A-Rod comes to mind as well. It would be fun to see an ‘all-time’ ranking, based on the ‘sum’ of one’s tools (with a max of 400 – 5 x 80).
Mays
Hit: AVG 60 (.302) BABIP 40 (.299)
Power: ISO 70 (.256) HR/PA 70 (5.28%)
Speed: SB 50 (17/Y) BsR 50 (1.7/Y) For speed I removed 3 years he had reduced playing time in.
Defense: UZR/150 N/A Fld 60 (9.68) Removed the same years as speed. The last five seasons used killed him here.
Arm: N/A
Hmm interesting. Maybe it would be better to take a 3-4 year peak for this kind of study? I think you’d want to measure a player when his ‘tools’ are in their prime, rather than having his final years drag down how good of a player he actually was.
surprised to see Ichiro still at the top in speed, even more that he is less than average on arm.