While all of the focus over the last month or so has been on the Phillies quest to repeat as World Series champions, I’ve been spending an inordinate amount of time refining and working on a system that I’ve been building for 2 years now to analyze the performance of minor league players. The system has gone through a bunch of changes, there are aspects of it that I’m still not 100% happy with, but right now, its at a place that I like, and the last changes made to it will come over time, as I figure out better ways to improve it. And like all cool systems, it needed a name, so I give you the SONAR Score system, a system that tries to dig beneath the surface (Sonar, get it) to analyze minor leaguers. So, check below the fold for more.
Statistically Objective Neutralized Analytical Report score. Cheesy? Sure. But I’m not very creative, and this is actually better than some of the other crap I came up with.
This post is going to serve as the outline of the system, what purpose it serves, and how I came up with what I did. I’m hoping that this helps to explain everything about the system, and I’ll make sure to put the content below along with the spreadsheets and statistics related to the system for reference.
Every year, MLB teams draft 50+ guys in June, which if you do the math, comes up to about 1,500 players. These players join the thousands of guys already in the minors, playing across 10 full season leagues and another 6 short season leagues. These leagues are filled with elite prospects, career minor leaguers, washed up veterans who were good 5 years ago, and just about everything else in between. As I’m sure you know, not every league is the same, not every level of baseball is the same, and within leagues, not every park is the same. The minor leagues serve as a learning ground for young players, a place to work on your flaws, develop new pitches, hone your skills, and generally prepare yourself for the major leagues. For some guys, its a way to earn a paycheck, and a delay, for however long, entrance into the regular world and holding down a regular job. Minor league statistics, as you may have heard, are not really always the best indicator of the type of player a prospect is going to become. Some guys put up seemingly pedestrian numbers for 2 or 3 seasons, then bam, they explode and become elite prospects. Some guys enter pro ball with a boatload of tools and hype and then 3 or 4 years later people say “he was a 1st round pick? Really?” Some guys spend years in the minors, logging 4,000 AB’s or more before they get a shot in the big leagues. Some guys spend only a few months in the minors. My goal when I started out was to be able to look at a minor league player’s numbers and immediately understand how he stacks up based on what league he is in, how old he is, and what home park he plays in, but do so by focusing mainly on his core abilities, not his batting average, home runs, RBI’s, or stolen bases.
What’s under the hood
For different reasons, I’m not going to spell out my formulas right now, but I’m going to give some bullet points on what the system looks at and why I chose the factors that I did.
* The final product, whether it be a pitcher or a hitter, is the SONAR score number. The higher the score, the better the prospect. I’ll give the scale at the end of entry. The number is not a counting stat like HR or RBI, and its not a true average stat like OB%. Its kind of a composite stat.
* All players have their numbers adjusted based on a few key factors. Those are; age, level, home park, and number of plate appearances or innings pitched. Age and level should be self-explanatory. Older prospects in lower leagues need to have their numbers adjusted downward, just like really young prospects in more advanced leagues need to have their numbers adjusted upward. Adjusting for park is slightly tougher, because park factors in general, especially minor league park factors, are very sketchy. A three year weighted average was used here, which is more reliable than a 1 year number, but its still not perfect. If you asked a scout which minor league parks were hitters parks and pitchers parks, I’m sure he could tell you, but measuring it is difficult. Even MLB level park factors sometimes seem kind of curious, but I knew that I needed to have some kind of adjustment here, or you’d end up with tons of guys from Lancaster and High Desert at the top of the list every year. The other adjustment, for PA’s and IP, might seem less obvious, but its one that I think is somewhat important. Baseball is a game of sample sizes, and if you look at a set of statistics, you need to evaluate how reliable the sample is. A sample size of 20 AB’s is worth a whole lot less to me than a sample of 500 AB’s. So players with low PA/IP totals see their score adjusted downward, simply because their sample is less reliable/subject to more uncertainty. Its a subtle thing, but something I wanted to add in.
So why is this new statistic important?
Thats a good question, and its one that I’m not sure I know the answer to, but that’s part of the reason in me wanting to do something like this. When you look across Major League Baseball, most every superstar in the sport was a big tools guy in the minors. Most of these guys were big scouts guys. For elite guys, there isn’t much to it. You could watch a guy like Cole Hamels dominate minor league hitters and know that he was going to make it as a big league pitcher. Lots of guys are like this. You didn’t need a fancy stat to tell you Albert Pujols was going to hit. Or that Joe Mauer could hit, or that Yadier Molina had a strong arm and would throw out his share of baserunners. But at the same time, there are lots of guys who come into pro ball with glowing scouting reports, they are ranked near the top of prospect lists because of these reports, and they never make it. Why don’t they make it? Why do some guys seemingly come out of nowhere and turn into great big league players? Is there a secret formula? Well, that was kind of my hope, that I’d run all of these numbers through a system, and it would identify guys that maybe the big publications weren’t focused on, and when those guys excelled, I could say “hey, I saw that coming” or something like that. When I started putting this idea together a few years ago, my preliminary system loved Brett Anderson, the young lefty for the A’s. Scouting reports on him weren’t great, most of the publications said he might be a #4, maybe a #3 if things bounced right. He scored really well in one of my early test runs, and was a guy I kind of stowed away in the memory bank. He had a big season last year in the minors, and was amazing at times this year, flashing plus stuff in the majors while basically learning on the job. Could he still only be a #4? Sure, but those same publications that were lukewarm on him a few years ago are now raving about him and talking him up like a future #1. Those are the types of situations I was hoping to unearth, guys who maybe are flying under the radar now, but who are displaying the skills needed to succeed at the next level.
Which brings me to something that I also need to address. This is a system without bias. Its strictly numbers based, with the adjustments I mentioned above. This system will not favor Phillies prospects, or prospects of any team. This system also does not replace a scouting report. A guy could be dominating Low A hitters while only throwing 88-89 mph because he has a ridiculous curveball that inexperienced hitters have no shot at hitting. That’s where its nice to know that Player X only throws 88, because generally righties that only throw 88 tend to struggle. But rather than casting this player aside because of his velocity, you take note that he has dominated at a lower level, and that he’ll need to prove it at a higher level. Should this player find a way to add 2 or 3 mph to his fastball, his core peripherals indicate he already has the ability to get hitters out, and his prospect status could rise. My system is limited, obviously, because the system does not know whether Pitcher X throws hard, or whether Batter Y has any physical projection left. It also doesn’t know whether a guy was a 1st round pick or a 50th round pick, but that’s kind of the point. My system is 100% objective, its up to the reader to determine whether a player’s score is too high or too low based on his scouting report.
There will be guys who post really high scores and then do nothing next year. There will be guys with negative scores (more on the scale later, I promise) this year who have big seasons next year. Its going to happen. Every publication that ranks prospects hits and misses on tons of guys every year. I’m not going to tell you that my info is more important than the info you can get from Baseball America, Baseball Prospectus, or anything other site. I’m simply telling you that what I have is a snapshot of how a player has performed, and it considers a lot of different factors. Will it turn out to be useful? I suppose only time will tell.
The SONAR Score Scale
When looking at the list of players, I wanted to try and think of a good way to present the scores and give it some context. Most people who follow the minors know what the 20-80 scale is. When looking at the 5 tools for a player (hit for power, for average, running, throwing arm, fielding), scouts will give a player a rating on each tool from 20 to 80 in increments of 5. 80 is considered elite, absolutely top shelf, very very rare. Think Ryan Howard’s power, Carl Crawford’s speed, and Joe Mauer’s ability to hit for average. A 20, on the other hand, is the absolute bottom of the scale. Think Eric Bruntlett’s ability to hit for average, Pedro Feliz’s speed, and Johnny Damon’s throwing arm. Then what you have is everything in between. A 50 is basically considered major league average. Here is a general breakdown of the 20-80 for practical purposes
80 – Elite, very rare skill
75 – Well above average, borderline elite
70 – Well above average
65 – Above average, borderline well above average
60 – Above average
55 – Average to above average
50 – Average
45 – Average to below average
40 – Below Average
35 – Below average to well below average
30 – Well below average
25 – Well below average to very poor
20 – Very poor
This gives you 13 different classifications. I think its important to create a bell curve type distribution here, simply because it seems logical. For 2009, I considered well over 2,000 position players. Of this sample, only 9 came in with a score of 70 or higher. This makes some sense to me. Sure, there are tons of elite guys in the majors, but not all of them were elite prospects in the minors. You can look at the Phillies current major league team as a prime example. Only Cole Hamels was touted as an elite uber prospect in the minors. There were lots of question marks on Howard, Utley, Rollins and others. If you extend out further, there are a total of 194 players who scored in the 50-80 range. That seems pretty accurate, doesn’t it? That’s 194 players in the minors who put up average to elite numbers. This is the sample of guys who I think should be closely examined. The single biggest chunk scored in the 40 range, below average, and intuitively, that seems right. Most prospects don’t make it, and if they do make it, its usually as a backup/roster filler type. There will always be the guys like Jayson Werth who fall completely off the map, only to re-emerge and turn into stars. But those guys are exceptions to the overall picture.
Using the 13 different categories and the 20-80 template, here is the scale I used when grouping prospects, based on their score. The number in the brackets at the end coincides with the 20-80 scale breakdown above. The hitting scale and the pitching scale are the same. A pitcher with a score of 85 could be compared to a shortstop with a score of 85. Its up to you to determine whether you want to compare hitters to pitchers. I generally prefer to look at them separately, but its a judgment call.
SONAR Score Chart
Score of 110+ = Elite 
Score of 95-110 = Well Above Average to Elite 
Score of 80-95 = Well Above Average 
Score of 65-80 = Above Average to Well Above Average 
Score of 50-65 = Above Average 
Score of 35-50 = Average to Above Average 
Score of 20-35 = Average 
Score of 5-20 = Average to Below Average 
Score of 5 to -10 = Below Average 
Score of -10 to -25 = Below Average to Well Below Average 
Score of -25 to -40 = Well Below Average 
Score of -40 to -55 = Well Below Average to Terrible 
Score lower than -55 = Terrible 
I know it should seem obvious, but a score of, say, 65.50 would count in the “65-80″ range, while a score of 64.50 would count in the “50-65″ range. At that point, you’re splitting hairs, and you could put the guy in either group. But I just wanted to make it easy to read. So a player with a score of, say, 70.34 would be considered Above Average to Well Above Average, obviously a very good prospect. Make sense?
It may look confusing now. But I think after you read this entire entry a few times (if you choose to), then it will make sense.
This whole concept, this whole stat, seems simple to me because I’ve spent hundreds of hours working on the project and its second nature. If you just skimmed the whole thing (which I don’t recommend) and you’re just looking for a takeaway, here it is. The score number that you’re going to find is a composite score that is neither a simple counting stat nor a simple percentage stat that attempts to evaluate what a player has done in the current season, based on his core skills. The stat is age, league, park and playing time adjusted. The scale is the same for hitters and pitchers.
As with anything, I’m open to questions/feedback if you take the time to read through this and make sense of it. If you just tell me how dumb it is, or how pointless it is, there isn’t a whole lot for me to say, so I probably won’t. If you have a question and I have an answer to it, I’ll definitely post it. Eventually, all of the scores will be available for all 30 teams, and I’m going to attempt to do a Top 15 prospects list for every team this year, heavily influenced by the scores, just to see how that list fairs with regard to the lists put out by BP and BA.
The score is meant as a frame of reference. It represents what the player did in the current season. Its important, when looking at the player’s score, to also look at other factors which might confirm the high or low score. For this, I think its important to focus specifically on a hitter’s walk rate, his Secondary Average, and his strikeout rate. For pitchers, its important to see how much contact he allows, and how many home runs he’s allowed, especially when considering his park. A hitter who posted a high score could have arrived at that score because he showed exceptional power, but if he’s sporting a 35% K rate and a very low walk rate, that should raise obvious red flags. Conversely, if a pitcher posts a high score but allowed a lot of hits and a moderately high HR rate, that should raise a red flag. I think the pitching scores are going to be slightly more reliable, because it is easier to isolate a pitcher’s true core skills, whereas hitters require a lot more aspects to be examined, and some of those skills are tougher to evaluate.
With all of that said, its time to get to the Phillies prospects. All of the scores and information is collected via Excel, and in the next few weeks I’m going to be adding all 30 teams spreadsheets into Google Documents and then adding a page at the top of the site to access all of this information, for those who find it interesting. I’ve stripped the nuts and bolts used to calculate the player’s score out of the spreadsheet and just included a few basic statistics, as well as the player’s score, the heart of this whole process. Players are sorted by score. I’m going to address the players in groups, starting with the hitters. If the pictures aren’t properly visible for you on your monitor, I recommend right clicking and then opening the image in a separate tab or window. A smaller image would have been too grainy, and this is simply an easier way. It won’t like right in the main page, but opening the image separately will make it much clearer and easier to read. I’m not going to touch on every prospect individually, but when I do my Top 30 prospects list, I will be referencing this material, so I’ll touch on lots of guys.
Here you have a list of the Phillies hitters who posted a positive score. Domingo Santana, who I raved about a few months ago, had a very impressive season. Its easy to get carried away over rookie ball numbers (D’Arby Myers, just a few years ago, burned me here), but unlike Myers, Santana’s season looks much more legit. His 10.8% BB rate was very good and helps to ease some concerns over the 31.7% K rate. His .364 Secondary Average is very good, as is the .220 Isolated Power. Its important to remember that he was just 16 for the first 6 weeks or so of his season. He’s obviously going to have to cut down on the strikeouts as he climbs the later, but at 6’5/200 lbs already, he could grow into an absolute monster in the Michael Taylor mold. He’s so young, but has shown massive skills already. He’s a long way out, but I’m really excited here. In a similar light, Sebastian Valle posted a solid score of 53.92, the second highest score among Phillies hitters. He got off to a slow start at Lakewood, but even considering those numbers, he basically destroyed the New York Penn League, a very tough hitters league. Most high school guys in the NYPL are 19 or 20, while most college guys are 21, 22 or 23, so Valle was still one of the younger guys in the league. His overall rates (BB, K, and SecAvg) are brought down by his performance at Lakewood, but he put up an .866 OPS in the NYPL. Domonic Brown and Michael Taylor were compared all season, and not surprisingly, they scored right in the same neighborhood here, with Brown slightly ahead of Taylor. They posted very similar rate statistics, Brown drawing slightly more walks and Taylor striking out slightly less. Both posted excellent SecA’s, with Taylor having close to a 20 point advantage. Taylor has shown a bit more power, but is also 2 years older than Brown. Both guys are very good prospects at this point, with Brown having a bit more projection.
Of the guys who we maybe focused on a bit less, Leandro Castro and Jonathon Singleton stood out here. Castro’s numbers were solid considering his lack of a real track record in the US. His walk rate doesn’t inspire a lot of confidence, and his .255 SecA kind of backs that up. Singleton, on the other hand, shows a lot more positive signs. He posted a stellar 15% BB rate and backed that up with an 11% K rate, a very good indicator. His .340 SecA ranks him just below the big 3 of Santana, Brown and Taylor, and though he didn’t hit for a TON of power in the GCL, he has a good projectable frame, and the power should come. Maybe somewhat surprisingly, Tim Kennelly ranked above highly touted Travis D’Arnaud. Kennelly posted an .802 OPS across 2 levels, while showing good discipline and contact skills. His .268 SecA also ranks above D’Arnaud’s .257 mark. D’Arnaud, as we know, got off to a really slow start and started to come on strong in the 2nd half, but splits in the minors are tough to really gauge. Matt Rizzotti was 2 years too old for Clearwater, but nevertheless had a nice season. He showed decent plate discipline, but a sub .200 ISO probably isn’t going to cut it for a corner infielder. Then again, I could envision him being something like a Greg Dobbs type of player, which I suppose wouldn’t be too awful as a reserve type player. But that’s a ways away.
Here is the next group of hitters
The beginning of the negative scores. Again, a score of zero means the player was basically average for his league, but this takes into account the entire player universe, not just the prospect universe, so an average minor league hitter (a score of zero) is probably below the threshold of average hitting prospect. D’Arby Myers score actually comes in right under the zero line, but his peripherals are not good, especially the .200 SecA. You’d expect him to be higher here, especially with the speed that was advertised when he signed. His plate discipline still has not improved. Cody Overbeck, who I wasn’t high on at this time last year, had a very disappointing season in Clearwater. A .169 ISO from a corner infielder doesn’t inspire confidence, but he could end up maybe being a half decent utility infielder if he could show competence at 2B. Troy Hanzawa put up one of the most empty .267 batting averages you’ll see, but he’s know for his glove anyway. Quintin Berry shows up here, and the story hasn’t really changed. He shows good plate discipline, but he has very little power, and even his speed wasn’t able to give him anything more than a .258 SecA. Alan Schoenberger, who I don’t think I’ve ever even mentioned on this site, put up mildly interesting numbers as a 20 year old 2B/3B, including a 12% BB rate and a .270 SecA. Another Australian product, there probably isn’t anything to see here, as he’s struggled to even hit .200 as a pro, but a walk rate above 10% always stands out.
The final group of hitters
Hey, there’s Anthony Hewitt! Not surprisingly, it was a rough season for Hewitt, who sported a 31.2% K rate, the same as Domingo Santana. Unlike Santana, Hewitt showed little to be excited about, with only a 3.6% BB rate and a .227 SecA. The .172 ISO is about the only thing to hang your hat on, but simply put, he’s been brutal at the plate. With the latest news of Hewitt’s move to the OF (which I alluded to a few weeks ago), the offensive bar is going to be raised unless he can stick in CF. A corner outfielder will absolutely be expected to outhit a 3B in most cases. Anthony Gose, arguably the fastest player in the minors, ends up well down the list here, and its not that surprising. His walk rate is pedestrian, and he’s shown almost no power. Scouts think the power is coming, and if it does, he’ll certainly jump up the rankings. His .273 SecA is driven by his massive stolen base totals at a relatively high success rate. 2009 draft picks Aaron Altherr and Kyrell Hudson are long on tools and short on polish/performance at this point, but again thats no surprise, especially in such a small sample. Travis Mattair, a consistent source of frustration for me, also fairs poorly in the system. His 10.4% BB rate was driven by his first half, as he drew 39 BB in his first 3 months, but only 15 over his last 2+ months. The power is still non-existent, despite a strong physical frame. He has no speed to speak of, so his bat is going to have to carry him. He plays solid defense, so he’ll keep getting chances, but the bat really has to emerge at some point, hopefully some time soon. Freddy Galvis, like Mattair, is a solid defender, moreso even, as his defense has been labeled elite already at a very young age. With the bat, however, he appears hopeless. This could be because he tried to learn how to switch hit, or it could be that he just can’t pick up breaking balls, or any other reason. Right now, he may be Ozzie Smith with the glove, but he has no power and he doesn’t draw any walks, so its tough to project him as anything other than a reserve infielder. When John McDonald is your current best case projection, its tough to get too excited. Maybe the most surprising guy in the entire system is Zach Collier, who ends up posting the lowest score of any Phillie. 2009 was essentially a disaster for Collier, who flopped at Lakewood and then performed poorly at Williamsport. He was only 18, very young for Lakewood, and was obviously in over his head. His peripherals were poor across the board at both levels, and its time to throw on the brakes in a big way. I can’t see him going anywhere other than Williamsport in 2010 and hopefully he gets back on track.
This concludes the introduction and the hitter portion of my system for the Phillies. Soak it all in, ask questions if there is something you are curious about. I’ll roll out the pitching scores on Monday. Please forgive any typos/terrible grammar, its a long post and I don’t have time to triple check it.