Five-Tool Players by the (Nerdiest Possible) Numbers
If there’s still such a thing as newstands anymore, the issue of Baseball America at your local one (i.e. your local newstand) is that publication’s annual “Tools” edition. No, it’s not (as you might suspect from the title) an issue dedicated entirely to relief pitchers with questionable taste in facial hair. Rather, it’s in this edition of the magazine that the editors of Baseball America attempt to isolate the players — major- and minor-leaguers — with the best baseballing tools (hitting for average, hitting for power, speed, etc.).
Beyond the results of a survey to which each of the league’s 30 managers responded, the issue also includes an attempt by author Matt Eddy to find five-tool players “by the numbers” (subscription required, I think).
After a brief discussion of what a “plus” tool might look like when quantified — and also some notes on the obvious limits of such an endeavor — Eddy suggsts this as a methodology:
For the sake of this exercise, let’s identify an above-average hitter as one who bats at least .285/.360/.460 with an isolated power of .175. That’s a 110 percent bump across the board (and then rounded down slightly to please the eye).
To this, Eddy also adds a speed component (more than 20 stolen bases) and runs his criteria through Baseball Reference’s Play Index for all player seasons 2000-10 — the results of which you can find here. (Note: it appears as though Eddy’s power criteria in that search is actually 20-plus homers and not a floor of a .175 ISO, but the results come out similarly.)
The big winner using this methodology is Bobby Abreu, who meets all of Eddy’s criteria in seven of 11 possible seasons. Hanley Ramirez qualifies in four seasons, while Alex Rodriguez finishes third with three “five-tool” seasons.
Eddy’s experiment is an interesting one, both in and of itself, and also for its potential to be nerd-ified — which, this being FanGraphs, that’s what I’ve endeavored to do in what follows.
For every player in the FanGraphs Era (2002-10), I’ve attempted to build on Eddy’s methodology using some numbers that might be more amenable to a FanGraphs reader’s tastes. Defense, as Eddy notes, is tougher to quantify, but I’ve submitted a way to deal with it that’s at least somewhat satisfying.
Here are the criteria for each of the five tools in this particular exercise:
Tool: Hit for Average
Stat: Contact Rate (Contact%)
Notes: I also considered strikeout rate (K%) for this, but felt that, if the goal is really to isolate a hitter’s contact ability, then contact rate is (n’doy) the best way to do that. While contact rate is a different thing than hitting for average, it also (i.e. contact rate) becomes reliable in a much smaller sample. In fact, batting average doesn’t even become a reliable marker of skill within 750 plate appearances, making a single season’s worth of data something less than entirely meaningful.
Tool: Hit for Power
Stat: Home Runs per Batted Ball (HR/(PA-K-BB-HBP))
Notes: For power, I considered at least two other metrics — namely, isolated power (ISO) and home runs per fly ball (HR/FB). The problem with ISO is that it gives credit to speed, because faster players are more likely to turn singles into doubles and doubles into triples. That’s fine, but if we’re trying to isolate speed separately, we don’t want to credit it here, as well. HR/FB, as I say, was another possibility, but the thing that it ignores is a player’s proclivity for hitting fly balls in the first place. Part of the mechanics of hitting a home run is the ability to create loft. Home runs per batted-ball rewards this ability.
Tool: Speed
Stat: Speed Score (Spd)
Notes: There’s no totally great way to do adjudge speed. I considered finding runs added via stolen bases (using linear weights) and general baserunning runs together, but there are plenty of players who are smart baserunners but who aren’t necessarily fast. If the goal is to isolate the speed tool, Speed score is the best (if not ideal-est) way to do that.
Tool: Fielding (and Arm)
Stat: UZR + Positional Adjustment
Notes: If I’ve had one intelligent thought in the past week (or, granted, maybe longer), it was to include not only UZR in the fielding criteria but also to add in each player’s respective positional adjustment. One of the draws of the five-tool player is that he’s theoretically able to play a position somewhere on the right side of the defensive spectrum. In other words, a player with a +5.0 true-talent UZR at shortstop is very different than one with a +5.0 true-talent UZR at first base — about 20 runs different, in fact. Adding in the positional adjustment is also akin to adding a sort of regression to the defensive numbers, thus giving less overall weight to UZR, which needs some three seasons to become reliable, alone. The addition of positional adjustment also goes some way to crediting both fielding ability and arm together. Like the above categories, it’s not necessarily ideal, but it works well for the purposes of the exercise, I think. (Note: so’s not to credit players who appeared in more games, I divided the sum of UZR and positional adjustment by games played).
To decide what constituted a “plus” tool, I calculated the above stats for each of the 1397 qualified players between 2002 and ’10. From there, I found the z-score (standard deviations from the mean) for each player in each respective category. The goal was to produce a number of player seasons roughly equivalent to the 40 or so Eddy found (or slightly fewer, because Eddy’s study included two more years.)
To do this, I went through each of the first three categories and chopped off all the player seasons with z-scores below 0.10 in the relevant category. This process revealed immediately how difficult it is find players who possess all the skills simultaneously.
To wit: eliminating just the players with a contact or power z-score below 0.10 leaves only 125 player seasons — or roughly 9% of the original sample. Cutting speed z-scores below 0.10 leaves only 36 players. All 36 of these players are included below.
I’ve sorted the qualifying players by the defensive component so that the reader can draw his own conclusions about the players who finished below the 0.10 threshold. The 20 players above the Xs qualify as five-tool players across the board, including defense; the other 16 players finished below the threshold.
| Year | Name | Team | Con | Pow | Spd | Fld+ |
|---|---|---|---|---|---|---|
| 2008 | Chase Utley | Phillies | 0.48 | 0.76 | 0.95 | 1.83 |
| 2007 | Chase Utley | Phillies | 0.55 | 0.17 | 0.95 | 1.49 |
| 2010 | Troy Tulowitzki | Rockies | 0.76 | 0.89 | 0.83 | 1.41 |
| 2008 | Carlos Beltran | Mets | 0.81 | 0.29 | 1.25 | 1.26 |
| 2006 | Carlos Beltran | Mets | 0.45 | 2.05 | 0.89 | 1.21 |
| 2009 | Chase Utley | Phillies | 0.46 | 0.85 | 1.37 | 1.20 |
| 2009 | Ian Kinsler | Rangers | 1.05 | 0.68 | 1.67 | 1.18 |
| 2006 | Eric Byrnes | Diamondbacks | 0.50 | 0.37 | 1.25 | 1.04 |
| 2008 | Grady Sizemore | Indians | 0.22 | 0.79 | 1.31 | 0.95 |
| 2007 | Jimmy Rollins | Phillies | 0.91 | 0.10 | 2.68 | 0.89 |
| 2006 | Chase Utley | Phillies | 0.32 | 0.61 | 0.95 | 0.87 |
| 2009 | Troy Tulowitzki | Rockies | 0.39 | 1.08 | 1.43 | 0.87 |
| 2006 | Vernon Wells | Blue Jays | 0.32 | 0.61 | 0.59 | 0.83 |
| 2005 | Felipe Lopez | Reds | 0.48 | 0.13 | 0.77 | 0.80 |
| 2007 | David Wright | Mets | 0.20 | 0.61 | 0.53 | 0.79 |
| 2008 | David Wright | Mets | 0.31 | 0.72 | 0.24 | 0.69 |
| 2009 | Nate McLouth | – – – | 0.43 | 0.14 | 0.65 | 0.37 |
| 2004 | Carlos Beltran | – – – | 0.12 | 1.16 | 2.38 | 0.33 |
| 2003 | Carlos Lee | White Sox | 0.60 | 0.50 | 0.42 | 0.31 |
| 2006 | Ray Durham | Giants | 1.12 | 0.55 | 0.71 | 0.26 |
| x | x | x | x | x | x | x |
| 2005 | Vladimir Guerrero | Angels | 0.29 | 0.86 | 0.47 | -0.05 |
| 2010 | Aubrey Huff | Giants | 0.26 | 0.35 | 0.59 | -0.11 |
| 2004 | Tony Batista | Expos | 0.48 | 0.55 | 0.36 | -0.15 |
| 2003 | Gary Sheffield | Braves | 0.34 | 1.12 | 0.59 | -0.17 |
| 2006 | David Wright | Mets | 0.45 | 0.38 | 0.95 | -0.22 |
| 2009 | Grady Sizemore | Indians | 0.26 | 0.28 | 1.07 | -0.46 |
| 2007 | Ian Kinsler | Rangers | 0.62 | 0.15 | 1.37 | -0.55 |
| 2005 | Albert Pujols | Cardinals | 0.64 | 1.26 | 0.53 | -0.67 |
| 2002 | Raul Ibanez | Royals | 0.24 | 0.45 | 0.18 | -0.68 |
| 2008 | Nate McLouth | Pirates | 1.17 | 0.23 | 1.43 | -0.74 |
| 2009 | Johnny Damon | Yankees | 0.48 | 0.31 | 0.95 | -0.83 |
| 2002 | Brian Giles | Pirates | 0.91 | 1.70 | 0.30 | -0.96 |
| 2007 | Gary Sheffield | Tigers | 0.13 | 0.52 | 0.89 | -1.03 |
| 2007 | Hanley Ramirez | Marlins | 0.50 | 0.30 | 1.84 | -1.04 |
| 2004 | Bobby Abreu | Phillies | 0.38 | 0.76 | 0.83 | -1.56 |
| 2006 | Carlos Lee | – – – | 0.83 | 0.78 | 0.30 | -1.60 |
The results pass the sniff test, I think. By this methodology, four players have recorded multiple “five-tool” seasons since 2002: Chase Utley (four), Carlos Beltran (three), Troy Tulowitzki (two), and David Wright (two, with a third below the Xs). It’s possible that Utley’s arm might preclude him from being a true “five-tool” player, but I’m leaving him here because (a) I know literally nothing about his arm strength, and (b) he’s awesome.
Some other notes on the results:
• The average WAR for the 20 qualifying five-tool players is 6.3.
• Bobby Abreu, who dominated Eddy’s list, appears here only once — and even then he doesn’t qualify defensively. He qualifies in the speed category in every season but one, but power (the way it’s defined here, at least) holds him back: he’s only posted two seasons with a power z-score greater than 0.10 since 2002.
• Carlos Lee was fast once. Maybe. Anyway, between 2003 and ’06 he averaged 15 stolen bases and just four caught stealings.
• Aubrey Huff probably wasn’t ever fast, but he’s managed five triples in two different seasons (2007, ’10).
• Tony Batista slashed just .241/.272/.455 (.225 BABIP) in his quasi-five-tool season, finishing with just a -0.4 WAR.
Carson Cistulli has published a book of aphorisms called Spirited Ejaculations of a New Enthusiast.
I am a bit surprised not to see A-rod on here, but I guess he really only had 3 good defensive seasons in this timeframe. And maybe the speed wasn’t there either?
Great article, though.
Maybe pre-Fangraphs A-Rod made it. His 1998 season was pretty awesome.
Carson, I enjoy these posts, but is there any reason for the white text in your charts? Or is it only white for me? Anyway, I have a terrible time reading them against the light tan background.
I see no white text.
Interesting.
I’m with you Richard. White text FTL.
Upon further analysis, it only happens when I view his tables in IE (I know, I know, but I have to use it for work), doesn’t happen in Firefox.
yeah, I suspected this might be the case; I have the same problem
I’m in IE 9. Black text.
Carson, great post, but are you going to show us who are the toolsiest players this season?
This is an interesting analysis. Think back to the 50’s, 60’s when Mays, Mantle, Aaron, Clemente, etc. etc all played at the same time. Puts the modern 5 tool list to shame.
…or maybe we just think of all these guys as having the most magnificient of tools, when more rigorous analysis (instead of our old, failing eyes and memories) would have led to more rigorous and better supported results. Whichever.
(Not saying those guys were chopped liver, by any means; just that it’s easy to think of someone as a resplendent 5-tool player but something different entirely to actually quantify it, or to test the assumption.)
Chase Utley needs a GG.
I think all the best hitters deserve a Gold Glove.
especially ones with a combined 91.9 uzr since 03.
It seems to me that besides David Wright and Carlos Lee, all the players that make the cut are up the middle players. The way you’ve calculated the defensive component seems to preclude players at the corners (and indeed, the except-defense list is full of corner players).
One might make the argument that corner infielders and outfielders can’t be 5 tool players, however I don’t think this is the way it has traditionally been conceived.
Felipe Lopez and Eric Byrnes are two players that I definitely did not expect to see.
To be fair, Eric Byrnes is absolutely TERRORIZING the beer league he’s playing in now. He’s presently triple-slashing .647/.782/1.128 for Beckman Tool & Die.
I find it curious that you don’t just use batting average in the “hits for average” component of a five tool player, since batting average is the definition of the tool. Maybe you think it’s a lousy way to judge a player, but the people who conceived of a five tool player clearly disagree with you (since, it is explicitly one of their “tools”).
Batting average is a result, not a skill. The tool is the talent that allows a player to post high averages … not the averages themselves.
I think this is misguided. There are lots of skills that go into a player hitting for a high average (making contact, speed from home to first, etc.) and they cannot all be incorporated into a single statistic easily. Any effective measure of these skills individually will correlate with the desired outcome (hitting for high average), however the correlations won’t be perfect and the difference in R-square from a perfect correlation is due to all the other factors that aren’t incorporated in the statistic plus stochasticity. Well, if you want to best incorporate all of the things that go into hitting for average, the best way to do it is to look at the result if you have it (and we do of course!).
Isn’t it the ‘hit’ tool, not the ‘batting average’ tool? While I agree that a player’s speed to first should play a factor I think BABIP fluctuations make for too much noise to use the BA statistic. An example is Milton Bradley in 2008: top 10 in BA but a marginal speed score that season (3.2) and a typically low contact% (83%). So what gave him that great ‘hit tool’ that season? A .388 BABIP. I would never say that Milton Bradley circa 2008 had a plus hit tool, he just ran into a crapload of luck that season.
I’m not sure what the ultimate solution would be if we were to include speed to first in the equation, but to me BA has far too much noise to be used for the hit tool.
Ray, the classic five tools are :
1) Hits for Power
2) Hits for Average
3) Speed
4) Defense
5) Arm
Batting average is explicitly one of the criteria.
Jason – you’re right in that…I always think of it as the ‘hit’ tool and ‘power’ tool but what’s generally used is ‘hit for average’.
I think, to a degree, the ‘hit for average’ tool is meant to show a players ability to repeatedly get on base. When BABIP noise is eliminated from the equation I think you get a better picture, as again I point to Bradley in 2008 as an example of someone who doesn’t have a plus hit tool but was easily ‘plus’ in that category in 2008 using BA.
As much as Eric Byrnes in 2006 shouldn’t be on this list, neither should Milton Bradley in 2008, so I think somethign other than contact% and BA needs to be considered for this to truly reflect what we see.
Ray,
Whether batting average is a useful measure is a separate issue. “Hits for average” is explicitly one of the scout’s five tools. Maybe they are idiots looking forward.
However as a retrospective (as this article is) batting average needs to be considered because it is what actually happened. The proof that Grady Sizemore didn’t actually have a five tool season is the fact that he hit .268. Maybe he should have had a 5 tool season but was just unlucky. Or maybe, just maybe, there is also a lot of noise in the correlate of batting average that the author used to calculate the batting average component.
Jason – First of all sorry if this gets misordered, the reply link isn’t showing everywhere that it should.
I think you’re getting hung up on semantics.
The point of a scouting scale is that results may be misleading. When a scout says that a player has a “Hit For Average” tool, it doesn’t mean he HAS it for average, rather it means he WILL hit for average. Thus, the skills that predict AVG are more important that the resultant AVG. Luck dragons can influence a player’s AVG to a great degree but have zippy to do with his “Hit For Average” tool.
Contact rate may not be the best proxy to use, but using results to make a priori claims is just wrong.
David,
It’s, of course, true that scouts are trying to project forward. They don’t have the results yet, so they need a predictor of batting average.
This article is a retrospective of 5-tool seasons. We have the results. There is no reason to use a predictor of what you think those results should have been.
….2006 is pretty “a posteriori”….
Jason,
I’m not a scout, so I could be wrong, but I don’t remember reading “hit for average” tool on any prospect site. My sense is the “hit” tool is trying to measure how often a hitter makes hard contact.
I also think there’s just way too much noise in a season’s worth of batting average data to use it.
Is there really any less noise in “Contact%”?
Hits for avg may be simply a way of saying “Puts the ball in play, but not necessarily puts it over the fences” — think, slap hitters, singles hitters, but, even those can be .270 defensive whizzes and yet possess a good eye, jus’ not enough muscles/steroids/frame/favorable park to clear the fences.
In my opinion, its jus’ a “not for power” hitting style being characterized. Not necessarily batting average. Rod Carew is a classic of this line. If you absolutely needed a ball in play, put him at the dish. Doesn’t have to be a liner to the gap, just any ole ball in play.
I would rename hit for average as make contact. Or leave it hit for average and use batting average or maybe batting average based on xBABIP.
I don’t like speed score as the tradition “tool” is steal bases, especially when fielding is factored seperately. So the speed tool should be replaced with stolen bases. Or maybe just the steals portion of wOBA.
Wow, what a useless bunch of garbage. If a guy hits well, it means he can get to first, read pitches, good bat speed, hand/eye coordination, strength…. Trying to encapsulate what a five tool player does in any sabermetric fashion is an effort in confirmation bias. To wit: “The results pass the sniff test,”
Watch a guy. If he can hit, hit for power, runs the bases well, can cover ground in the field and throws well, he’s a five tool player. Don’t need sabermetrics to separate the wheat from the chaff.
And yet the author of the BA article had Abreu as a five-tool player in seven seasons, yet using the saber breakdown he’s not on there once. Personally, I wouldn’t have called Abreu a 5-tooler in his prime (marginal real ‘power’ and crappy fielding) so yes, this article does work to ‘separate the wheat from the chaff’.
The funny thing is that the methodology tells us a player like Eric Byrnes who obviously never was a 5 tool player is in fact a 5 tool player. In Eric Byrnes 5 tool year he hit .286…. I guess it was just bad luck that year for the career .258 hitter.
I agree, contact% alone doesn’t encapsulate the hit tool. I’m not sure there’s one true measure that does. But I would also say–as I did above–that BA doesn’t do the job either, way too much BABIP noise over a 400-600 AB season for it to be relied upon.
Oh, and Eric Byrnes actually hit .267 in 2006 (the year he’s on this list), his remarkable .286 season came a year later 🙂
(So yea, as I said earlier I think using contact% produces outliers just like BA would)
regressing BABIP to the player’s career average, and then taking the resulting BA would probably be the best way to do it.
Honestly though, I think just using BA would be a lot better than contact %.
Utley has a noodle for an arm. It’s really terrible. He’s a great 2nd baseman because of his range and positioning.
Grady Sizemore is considered a 5 tool player in year in which he hit .268. He is a career .270 hitter.
Carson, Utley’s arm is the only real weakness in his game. It’s not strong and not very accurate, though he’s gotten to the point when he can pretty reliably turn the DP.
Ray Durham is a funny one. He almost really did have a 5 tool year in 2006. Then he fell of a cliff and was out of baseball.
Kinsler in 09 is the toolsiest in my opinion because his lowest number, .68 power, is the highest low.
That’s not quite true. Troy Tulowitzki 2010’s lowest was contact at 0.76. Plus I just feel Kinsler’s season was just too fluky, he hasn’t been able to produce as much power since. Great player, just a career year
“he hasn’t been able to produce as much power since.”
Seriously? He’s coming off a 32 HR season…
Domingo Ayala needs to be in there somewhere.
You should do this study from 1901, but for fielding TZ + UZR and for hitting for average BABIP instead of contact %. Maybe you could do a three year range instead of 1, showing which players are consistently the most toolsy in history
Doing it this way (4 real tools, hit, power, speed, and “defense”) will definitely result in Utley being high, given his one bad tool (arm) is hidden by how good he is at fielding and his position (2B).
It’s not that an unfair of a statement, given that of any position, second base requires the least amount of “arm”, besides maybe 1B or LF (which aren’t premium defensive positions anyway).
Contact % is a ridiculous proxy for Hits For Average.
HR/Batted Ball is a ridiculous proxy for Hits for Power.
Are we gonna now say that a guy who hits 15 HR and 50 doubles doesn’t hit for power?
You completely overthough the analysis, and ended up with something thats pretty much useless.
“Contact % is a ridiculous proxy for Hits For Average.
HR/Batted Ball is a ridiculous proxy for Hits for Power.”
…why?
Well, I’m not RC, but I can speculate on this anyway:
Contact % is a terrible proxy because it takes nothing about the contact into account. So if I make contact 90% of the time and always pop the ball up for an infield fly (basically an automatic out), then I’m as good as someone who always hits line drives, right? No so much.
HR/Batted Ball is a little more reasonable. With that said, the difference between a HR and a non-HR can be very marginal. Especially if we’re talking about scouting tools, it’s well known that a young player who hits a lot of doubles will often turn more of those into HR as they develop. So it’s not going to have very good year-to-year consistency. I wouldn’t throw it out entirely, but I think one would want to supplement that with something like the average distance of a player’s fly balls and line drives. The problem is that getting HR really depends on a couple of things: getting the ball up (FB and LD) and getting the ball out (speed off the bat/distance). HR/Batted Ball sort of captures those, but it leads to ridiculous things like a player being more toolsy because he moved from San Diego to Colorado.
Look guys, if you want to predict who will have a 5 tool season going forward, then by all means use the best predictors of batting average, slugging percentage, etc.
However, if you want to tell us who actually had 5 tool seasons in the past, then you should not look further than batting average, slugging percentage, stolen bases, etc.
Its like awarding the homerun crown at the end of a season. You might want to calculate homerun percentage on balls in play, or any other thing you can think of. But the easiest and most accurate way to do it is to just count who hit the most homeruns.
Once something has happened you can forget about what you think should have happened before the fact.
Carson is trying to retrospectively determine skill rather than results. They are not always the same thing.
Right, he is just clearly doing it in a bad way.
Don’t you wonder why the list is chock full of players who obviously aren’t 5-tool players? It’s because he isn’t measuring the skill in the best way available to him.
Seriously, he’s got Tony Batista just missing the cut in 2004. In 2004 Tony Batista hit .241/.272./.455! Granted that .241 was probably a bit of bad luck since he was a career .251 hitter, but still!
So why is he getting it so wrong so often? The answer, obviously, is that the correlation between contact % and being a good hitter is not perfect (and may not even be that good), so he’s got a list full of hitters who apparently made a lot of really shitty contact.
I found this funny article by Dave Cameron showing that both Eric Byrnes and Tony Batista are, in fact, the masters of shitty contact:
http://www.fangraphs.com/blogs/index.php/byrnes-babip/
I didn’t need to read the article to know that these players made a lot of shitty contact though. I knew because their contact rates are apparently high (according to the article we are commenting on) and yet they were always terrible at hitting for average. It turns out a sizable chunk of that contact was infield popups.
The mistake is thinking that contact % is 1) a skill (it’s a result, the same as batting average) and 2) that contact % equals hitting ability (it doesn’t, it’s just a corollary. It explains some of the variation in hitting ability but not all of it).
So, what we were left with was a list of players the author thought SHOULD have been 5-tool players based on his favored statistics, even though many of them weren’t (and I’m willing to bet he also missed some that really were).
It might be fun to calculate the list of who really were 5-tool players and then compare it to the list of players that the author thinks should have been. You will get three categories :
1) should have been but weren’t (e.g. Eric Byrnes)
2) should not have been but were (e.g. Arod I’m guessing by his conspicuous absence)
3) should have been and were (e.g. Carlos Beltran)
Categories 1) and 2) are interesting because they are outliers in their corollaries (like Eric Byrnes).
just to make sure i understand – how does this account for arm strength? if i understand uzr correctly, it’s the ability to get to the ball and has little to do with what happens once you get there. isn’t that why it can make weak armed fast outfielders look great and guys like sheffield look beyond incompetent in the outfield?
Not that its a big number, but in the HR/power dept, did you exclude the inside the park HR from the number, where applicable? Not that I have a problem with those in the bigger picture of Tools, but, that particular HR is a speed one, if anything. Not only the minus for power, but making sure its included somehow in the speed numbers.
Not sure if it makes sense to even bother. Inside the park HR are so rare, I doubt they’d impact things much. I can’t even think of anyone who’s gotten more than 2 in a season.
Is it possible that we can consider Hanley Ramirez is a 6-tool player?
One of the tools is himself.