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Previous editions: Baltimore / Boston / Chicago AL / Chicago NL / Cincinnati  / Cleveland / Colorado / Detroit.

Earlier this week, lead prospect analyst Dan Farnsworth published his excellently in-depth prospect list for the Houston Astros. In this companion piece, I look at that same Houston farm system through the lens of my recently refined KATOH projection system. The Astros have the second-best farm system according to KATOH, trailing only the Brewers. Their system lacks star power, but is easily the deepest. That’s why this post has way more words than you probably care to read.

There’s way more to prospect evaluation than just the stats, so if you haven’t already, I highly recommend you read Dan’s piece in addition to this one. KATOH has no idea how hard a pitcher throws, how good a hitter’s bat speed is, or what a player’s makeup is like. So it’s liable to miss big on players whose tools don’t line up with their performances. However, when paired with more scouting-based analyses, KATOH’s objectivity can be useful in identifying talented players who might be overlooked by the industry consensus or highly-touted prospects who might be over-hyped.

Below, I’ve grouped prospects into three groups: those who are forecast for two or more wins through their first six major-league seasons, those who receive a projection between 1.0 and 2.0 WAR though their first six seasons, and then any residual players who received Future Value (FV) grades of 45 or higher from Dan. Note that I generated forecasts only for players who accrued at least 200 plate appearances or batters faced last season. Also note that the projections for players over a relatively small sample are less reliable, especially when those samples came in the low minors.

1. AJ Reed, 1B (Profile)

KATOH Projection: 7.1 WAR
Dan’s Grade: 60 FV

Reed might have had the biggest breakout of any minor leaguer in 2015. Minor league pitching was no match for his mammoth power and copious walks, as the 22-year-old hit .340/.432/.612 between High-A and Double-A last year. If you’re looking for something to be concerned about, it’s Reed’s 20% strikeout rate. While that’s not alarmingly high, it’s a tick above average, and hints that he might have a tough time making contact against big league pitching. But otherwise, all systems are a go. It isn’t often that KATOH gets excited about a first base prospect, but it’s all in on Reed and his gaudy power numbers.

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Today we’re on a quest of sorts. It’s not a holy grail-type of quest, but then again, in a way we are looking for a grail: it’s just the grail of never walking. That’s not the actual intention of these hitters, because walks are a good thing if you’re a batter, and at some point you simply have to walk — no matter how hard you try not to — because a pitcher is going to come along and throw you nothing but junk. The lack of walks for these guys are just a product of their approach, and hitters with this kind of approach either quickly lose their job or are really good at other aspects of the game.

Take, for instance, the hitters we’re going to discuss today: Jean Segura and Salvador Perez. You might not have visited their player pages recently, but take a look at a few select categories in their stat lines from this past season:

A few things jump out. Holy moly those walk rates. Below average (in one case, very below average) offensive numbers. And finally: solid defensive ratings. That last point is the main reason these two players garnered a combined 1137 plate appearances this past season despite their woeful offensive production: Segura is an above-average defensive shortstop (also providing speed on the base paths), and Perez is one of the best defensive catchers in baseball. Even though Segura’s playing time will be in question following his trade to the Diamondbacks, this goes to show you the kind of bat that can stick at these thin positions for most or all of a season.

The walk rates are the thing on which we really want to focus today, however, because they’ve rarely been paralleled in the past century. If we look at individual season walk rates going back to the start of the live-ball era (1920), we find Segura and Perez at the extreme end of the leaderboard among qualified hitters: in 2015, Segura tied for the 23rd-lowest walk rate since 1920 at just 2.2%, and Perez (with a walk rate of 2.4%) tied for the 40th-lowest mark. We could go into the hundredth decimal place to break some of those ties, but we won’t. We could even go further and factor in intentional walks, noting that Segura had two and Perez had four, but that seems unnecessary. We get the point: in relation to average full-time major league hitters, these two basically never walk.

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You come here to read baseball analysis, not baseball blog analysis, but just this once real quick, I’m going to turn the metaphorical camera around. Let’s spend a few minutes talking about FanGraphs!

If you’re reading this post in your browser, you might see off to the right a list of authors. Just to the right of that, there’s an additional list, of tags. You’ve probably never paid attention to these tags, or categories, and they do appear poorly organized, but we try to tag all of our posts. Now, we certainly don’t do a perfect job. And we did a worse job in the past. But it’s always been something that’s supposed to be done, and among the various categories are all 30 individual baseball teams. Focusing on those, then: look closely. Under “Angels,” for example, you see “Post Count: 299.” That means there have been 299 FanGraphs blog posts with an Angels tag. Is that a lot, or is that a little, or is that just right?

We can easily look at the numbers for all 30 teams. We can see who we’ve written about the most, and who we’ve written about the least.

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Ben and Sam preview the Rockies’ season with Deadspin editor Tom Ley, and Jeff talks to Purple Row prospect writer Jen Mac Ramos (at 19:45).

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“Tanking” has become a word people are applying to baseball, with various agendas being pushed in advance of the CBA negotiations. No matter where you stand on the merits of the argument, it’s at least a curiosity that now, perhaps more than ever, almost everybody seems to have a chance. It’s easier than it’s ever been to build a roster capable of making the playoffs, and the landscape feels like it’s mostly in balance. You probably already knew these things. If you’re a big fan of looking at stuff you already know, wait’ll you see what I have in store for you here!

Ben Lindbergh wrote an excellent article at Grantland last March about the broad trend toward greater parity within the game. There’s not very much for me to add, because in classic Lindbergh fashion, he went into incredible detail, following every thread. You should read that article from start to finish, and all I’m really here to do now is add a little more data. As I noted earlier today, this is projection season, so it’s of interest to see what the projections are saying. They’re saying what you might’ve already been able to guess about the American and the National Leagues.

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Spring training is getting underway, which means while we aren’t yet into the regular season, we are into projection season. Depending on what you’ve been looking at, there’s been a lot of talk about the White Sox, and there’s been a lot of talk about the Royals. Those teams have received some somewhat controversial projections, but not everything is so up for debate. For example: it’s universally agreed the Cubs look really good, and it’s universally agreed the Phillies look really bad. These statements are practically givens.

The White Sox became a topic of conversation because of USA Today. The Royals are back in the spotlight because of Baseball Prospectus and PECOTA. This is FanGraphs, so let’s take a look at what’s being published on FanGraphs. Here’s our projected standings page, based on Steamer projections and the depth charts, and you see the Cubs projected for an MLB-best 94 wins, and the Phillies projected for an MLB-worst 66 wins. These projections won’t cause any arguments — the numbers agree with consensus opinion.

Projections, though, are midpoints, at least when you see them published. Ranges exist around them. Sometimes pretty big ranges. And both the Phillies and Cubs will employ major-league baseball players, who are elite talents when it comes to their craft. The Cubs will win a bunch of games, and the Phillies will win a bunch of games. What are the chances the Phillies win more games than the Cubs?

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Ben and Sam banter about a picture of Michael Pineda, then answer emails about deferred contracts, players they wish would write books, Michael Jordan the minor leaguer, and more.

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There is an inherent risk/reward dynamic for both team and player when it comes to locking up young players to guaranteed contracts past their arbitration years. Without a guaranteed contract, teams can go year to year with players through the arbitration process and, in the event of player injury or decline in performance, the team can drop the player without consequence. However, once that same player reaches six years of service time, he is free to choose any team he prefers, often at an expensive price.

For the player, going year to year naturally exposes him to a possible loss in future compensation due to the risk of injury or a decline in performance. That said, by going year to year, the player essentially bets on himself during the arbitration process and reaches free agency at the earliest possible time — and with the benefit of a potentially large payday.

Where these two interests meet, teams and players reach agreements early in careers to buy out the player’s remaining arbitration years and some years of free agency. A team’s ability to absorb risk in handing out contracts is much greater than the player’s risk in turning the contract down, and the savings are generally much greater for the team.

From the winter of 2008 through the summer of 2011, teams and players agreed to 53 contracts both (a) at a point before the player in question had recorded four years of service time and (b) in which the contract featured no guaranteed money beyond 2016. Among those players, there are some bargains and some duds. By examining only the free-agent years for which clubs paid ahead of time, we can calculate rough approximation of how much money teams saved or lost by locking up players early in their careers.

While there are some players who might have been non-tendered during the arbitration process — therefore costing teams a bit more money than they would have going year to year — there are also players who would have earned considerably more during the arbitration process than their contracts provided. When teams sign players to these type of contracts, the major win for the team comes in free agent seasons, and the major concession by the players are those same years. As a result, the analysis below will focus on those years.

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Full-season team projections cause some heated arguments. If a team finishes the year with fewer wins than expected, fans want to know why their club underperformed projections. If a team overperforms its projections, meanwhile, those same fans will insist that forecasts in subsequent years lack the ability to detect their club’s particular strengths and are thus useless.

Here at FanGraphs, we have only been doing full-season projections for a couple years, but just about every week I see a mention of the 2015 World Champion Kansas City Royals’ projected record of 79-83. If I search Google for “79-83 Royals FanGraphs,” I get over 11,000 article links. Unsurprisingly, it’s a popular topic. Rarely does a club, following a pair of World Series appearances, then proceed to fail to break even. But that’s what the numbers suggest for 2016.

While FanGraphs has produced team win projections for only a couple seasons, Replacement Level Yankee Weblog (RLYW) has been publishing win projections for years. Since 2007, to be precise. Given this larger sample, I thought that it might be worthwhile to compare the projected win values produced by RLYW to the actual final win values produced by teams. So, with the permission of RLYW editor SG, that’s what I’ve done here.

I hate to disappoint anyone, but there are actually aren’t any great findings in the plethora of graphs to follow. I did find a couple interesting artifacts of the data, but no game changers. Instead, I see the following mainly as an additional data point in many past, present, and future discussions.

To start with, here is how projected and actual values have correlated.

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