Hello, and welcome to the first part of my 2010 SONAR review. As you know, last winter (and really it was 2 years in the making) I unveiled a new metric I had created to try and evaluate minor league performance across all levels, taking into account a player’s age, his league he was playing in, his home park, and measure the performance based on his true performance, not just the standard 3 slash stats. I re-worked the stat a few times, trying to get the kinks out, and then rolled out my final scores for the 2010 season. All of the data is found here, as well as a primer on the basics of what the score measures and my rationale for creating the metric. Now that we have a full year of data, I want to re-visit my lists heading into 2010 and see how good SONAR was as a predictor, based on 2009 performances used to create each player’s SONAR score. I’m going to do 6 parts, one for each division, and keep them in separate posts. So check below and we’ll get started.
If you head on over to the SONAR Scores archives, you can check out the top 30 lists churned out by SONAR, as well as notable players in each org who didn’t make the top 30 and how they scored. Again, these lists are simply a readout of a formula, they do not take raw tools/projectability/signing bonus/how much scouts love the prospects into the mix. The lists should prove interesting when comparing them to the lists from the other big prospect outlets. This essentially concludes my work on the 2009 data. 1 year won’t be enough to tell us how valuable the system is, but it will be very interesting to go back and look at these lists/results in a year’s time and see how players played, which guys SONAR was high on that succeeded, which guys fell flat, and which guys SONAR pegged as overrated who struggled.
Note number 2. I recently started a new job, and my job will keep me off the grid for most of the day during the week. Gregg is in charge when I can’t get to the computer to post a newsworthy item, and though I shouldn’t have to say it, please be respectful. I’m planning on writing a daily wrap up piece every night that can function as the next day’s general discussion, gregg will have his affiliate report for Lehigh Valley once a week, and I’ll also be working on some other projects for the site, but I won’t have access during the day, so behave yourselves.
I’m back with the promised pitching numbers spit out by good ole SONAR. Unlike the position players, where it was appropriate to cover each position individually, I’m going to break down all of the pitchers together. But instead of 25, I did a chart of the top 100, with brief thoughts on a few, and more detailed thoughts on some of the interesting rankings. I recommend you checking out my revised SONAR post from a little while back, which talks about the way the system was tweaked. Most of it had to do with the position player aspect of SONAR, but I updated the weightings for the pitching formula, as well as fixing a few bugs with park factors and age factors. I’m going to first present the chart for all Phillies pitchers, then present the Top 100, split into 3 separate charts to make it easier to read. Check below for more..
I hope all of you have read my revised and updated piece on the SONAR score published a few days, but if you haven’t, check it out before proceeding here. After my initial release, I went through each position and did an examination of the top 20 at each position. I’m not going to do the same in depth analysis here, I’m just going to give you the Top 25 at each position, and then brief general thoughts underneath each chart. I’ve chosen here to also break down the OF spots into the more traditional LF, CF, and RF. As always, SONAR is an attempt to look at a player’s secondary skills (plate discipline, raw power, speed) and ignore the more superficial stats like batting average, which are more luck influenced. SONAR represents a data point, a means for further exploration, its not a replacement for scouting reports or other statistics. So check below and we’ll get started.
This is something I’ve been spending a lot of time working on with the completion of my Reader Top 30, and I feel like I have things where I want them, so I wanted to make another detailed post talking about my new creation, the SONAR score. If you’ve been around for a while, you read my introduction pieces here and here back in November. Like any good social scientist, I set out with a goal; to try and figure out a way to evaluate minor league prospects across all leagues, factoring in all of the aspects of the game that can be accurately measured, to try and evaluate what prospects have done, and which players might succeed/struggle going forward based on their peripherals. Along the way, I encountered many difficulties, including the simple amount of work it entails to code over 5,000 players into a system, and then trying to figure out if the formulas I used were accurate, helpful, or off the mark. My test run was published in November, and then I started to do position by position breakdowns. It was during this process, when I was looking at the numbers in depth (and based on reader feedback) that I discovered some of the flaws in the system, and I set about fixing the errors, making adjustments, and trying to make the system the best it can be. As any person who tries to create something new, the first run (or first 10 in this case) rarely is ever perfect. But a good scholar always tries to improve, to figure out what is missing, and to try and make it the best it can be. So that is where we are now. Check below for the details.
The next installment of the SONAR series is going to focus on corner outfielders. I’ve decided to group the two positions (LF and RF) together, because its common for prospects in the minors to switch between the outfield spots, and in many cases, you’ll see a player with 70 games in RF and 55 in LF, his team obviously sees him in a corner, and his arm is probably borderline in right field, but they are giving him a chance there. The difference in LF and RF is small, but it is an important difference. Rightfielders are required to make the longest throw, from the right field corner to 3B, while the LF’s longest throw is to home plate. A corner outfielder is less valuable than a CF in terms of defense, and a right fielder is a tick or two more valuable than a leftfielder. Both positions are more valuable defensively than 1B, though the offensive expectation in LF is slightly higher than RF. If you’re new to the concept of SONAR, how it works, what it means, etc etc, then I suggest you read this, then check here for more scores and information. Check below the fold for more
Welcome to the latest installment of the SONAR takes on series. If you’re new to the concept, I recommend you check out my intro piece on SONAR here, then check out the reports for first base, second base, shortstop, and third base so you have an idea of how I’m approaching the project. After catcher, I’m going to do the corner outfielders together, then centerfield, and that will wrap up the position player side of the ledger. I’ll then break down the pitchers, before finally releasing a top 100 prospects based on SONAR scores. After that, I’m going to reveal my top 15 prospects for each team, which will be a synthesis of my own personal opinions of the prospects, plus my work here with SONAR. We really won’t know how accurate my readings on these prospects are until we have multiple years of data, but it should be fun to look back at these lists next year and see which guys proved to be real and which faded into obscurity. So lets get started with the catchers…
Sorry for the delay after the 3B writeup, I took some time to get all of the pitcher reports in order, but now we’re moving on to the shortstop position, one of the toughest to evaluate, along with catchers. If you’re new to the concept of the SONAR score, I recommend you read the intro here, and then check out the reports for 1B, 2B, and 3B. SONAR is a look at what a player has accomplished statistically, looking at the metrics that are most indicative of future success, and putting it into the proper context with regard to league, level and age. Its a one year score, based on pure 2009 data, and is not meant as a replacement for scouting reports, just as a supplemental piece of data, one which should be used in conjunction with other evaluation methods. After 2010, a new statistic will be introduced which combines 2 years of SONAR data to form a weighted score. For now, we just have one score for 2009. Lets get right into it.
The third installment of the SONAR position by position breakdown focuses on the hot corner, looking at the best 3B prospects in the game and how they fared with my newly created metric. if you’re new to the whole SONAR concept, I recommend you start here, then check out the report for first base and second base. Third base has its difficulties, just like the up the middle positions, because the defensive value dropoff from 3B to the positions further down the defensive spectrum is steep, especially the drop from 3B to 1B, which is a common transition for some slow footed sluggers. Check below the fold and we’ll dig right in
The position by position breakdown of prospects according to SONAR scores continues today with 2B. If you missed the first installment, check here. Before getting into the position, again just a few quick reminders. This statistic is based on 1 year of data. It does not factor in a player’s draft slot, his signing bonus, his raw tools, or any kind of projection for his future ability. It tells a story of what he did in 2009 based on his age, what level of the minors he was at, what league he played in, and how he was affected by his home park. There are other aspects that need to be considered when trying to evaluate prospect status, but those aspects are subjective, this score is not. This is meant to be taken as a data point for further confirmation/investigation, and to give a snapshot of the player’s true performance in 2009. After the 2010 season, a two year combination score will be used, as well as a 1 year score, but for now, the statistic only considers 2009. Check below for more…