As we count down the days until spring-training games begin, let’s continue to take a position-by-position look back at the ball-in-play (BIP) profiles of 2015 semi-regulars and regulars to see if we can find any clues as to their projected performance moving forward. We’ve already looked at first and second baseman; today, let’s go all the way to the “good” end of the defensive spectrum and examine the shortstops.

First, some ground rules. To come up with an overall player population roughly equal to one player per team per position, the minimum number of batted balls with Statcast readings was set at 164. Players were listed at the position at which they played the most games. There is more than one player per team at some positions and less at others, like catcher and DH. Players are listed in descending OPS+ order. Without further ado, let’s kick it off with AL shortstops.

BIP Overview – AL Shortstops

Name	Avg MPH	FB/LD MPH	GB MPH	POP%	FLY%	LD%	GB%	CON	K%	BB%	OPS+	Pull%	Cent%	Opp%
Correa	90.58	94.66	87.39	2.6%	26.5%	22.4%	48.6%	130	18.1%	9.3%	132	35.5%	34.2%	30.4%
Lindor	89.08	92.05	88.13	3.1%	25.6%	20.6%	50.8%	118	15.8%	6.2%	122	34.6%	36.1%	29.3%
Bogaerts	88.13	90.84	87.53	2.7%	23.1%	21.5%	52.7%	114	15.4%	4.9%	108	33.8%	34.2%	32.1%
Miller	90.71	94.00	89.64	2.6%	28.8%	20.2%	48.4%	99	20.3%	9.5%	106	32.9%	35.5%	31.7%
Cabrera	87.76	91.61	85.25	5.3%	38.3%	20.7%	35.8%	106	19.4%	6.5%	105	47.9%	27.7%	24.4%
E.Escobar	86.06	89.55	82.32	3.1%	35.6%	19.3%	42.0%	107	19.3%	6.3%	102	41.5%	34.2%	24.2%
Iglesias	83.33	87.17	82.95	3.5%	19.7%	21.0%	55.9%	82	9.7%	5.5%	100	34.6%	36.4%	29.0%
Semien	87.56	91.54	82.12	3.3%	35.5%	23.1%	38.1%	106	22.0%	7.0%	95	42.0%	33.3%	24.7%
Gregorius	86.05	88.67	84.75	3.2%	30.9%	21.2%	44.7%	81	14.7%	5.7%	90	38.5%	35.0%	26.5%
Reyes	85.06	85.92	85.83	7.7%	28.2%	20.0%	44.1%	80	11.9%	5.0%	84	42.5%	35.7%	21.8%
Aybar	85.25	87.87	84.72	1.4%	25.0%	21.0%	52.6%	69	11.4%	3.9%	81	40.1%	37.5%	22.4%
Andrus	87.28	89.71	87.36	3.1%	28.7%	21.1%	47.1%	69	11.8%	7.0%	80	43.7%	31.0%	25.2%
A.Ramirez	84.66	87.57	83.34	3.3%	25.8%	21.4%	49.5%	66	10.9%	5.0%	79	38.1%	42.3%	19.5%
J.Ramirez	86.15	87.73	86.63	4.8%	31.4%	16.2%	47.6%	55	11.0%	9.0%	70	44.2%	30.4%	25.4%
A.Escobar	84.11	86.51	83.31	3.0%	26.9%	22.3%	47.8%	61	11.3%	3.9%	68	31.5%	38.3%	30.2%
Hardy	87.94	90.69	86.51	3.4%	29.7%	17.5%	49.4%	64	20.1%	4.6%	53	40.1%	40.4%	19.5%
AVERAGE	86.86	89.76	85.49	3.5%	28.7%	20.6%	47.2%	88	15.2%	6.2%	92	38.8%	35.1%	26.0%

Most of the column headers are self explanatory, including average BIP speed (overall and by BIP type), BIP type frequency, K and BB rates, and BIP by field sector (pull, central, opposite). Each player’s OPS and Unadjusted Contact Score (CON) is also listed. For those of you who have not read my articles on the topic, Contact Score is derived by removing Ks and BBs from hitters’ batting lines, assigning run values to all other events, and comparing them to a league average of 100.

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Let’s be honest. I’ll start. I’m not a very good baseball player. I used to be much better than I am now, but even back when I was better, I was not good. I fit in with my high school competition and, later, adult league, but in the grander scheme I was, sadly, not good. You are also probably bad at baseball. I know because you are reading this and not playing baseball. That’s okay. It’s what joins us together, you and me.

But what if you had to play? What if you were sitting in the bleachers at Camden Yards and all the Orioles came down with 168-hour food poisoning. What if the team bus blew out a tire between the airport and the ballpark and there were no other buses available because the Pope was in town for a week and he loves buses. So, you need to play!

The team needs you, but it also knows you are terrible. You have to play, but you have to play as little as possible while playing. Where could you play with out hurting the team? Well, nowhere. You’re going to hurt the team. Badly. You’re going to really hurt the team because you are awful. Terrible. The worst. You’re just barely better than me, although that’s like saying rotten food is better than poo. It is, but it’s also what Olympic announcers refer to as a “low bar.”

The worst part is that you have to play for a week’s worth of games. And you’re starting. All six games (there’s an off-day but it’s in Baltimore [sad face emoticon]). That’s one long monster truck rally! You have to hit and play the field. No DH for you. Maybe you’re stuck playing for the Red Sox and David Ortiz is like, “No way, bro. Get out there.” Maybe the other people who are forced into duty are older, fatter, and worse than you. Maybe I have to play DH!

So. Now we have to figure out where to put you. First things first: let’s figure out the batting order. Course, it’s actually not hard to figure out the batting order. You’re batting last. The less you bat the better. Because you’re horrible. Sorry to dwell on the fact; I just don’t want you to forget. It’s sort of the point of this article. But it’s probably for the best, batting ninth. I mean, really, do you want to stand in against 95 mph heat? I sure as hell don’t. I don’t want to tell you what I’d do in my pants in that situation, pun sadly intended. I’d bat 10th if I could. I imagine, whether you admit it or not, you would too. But you can’t. You’re hitting ninth. Congratulations. Hope you can foul one off, maybe. Also try not to mess your pants too noticeably.

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On Tuesday, our friends over at NEIFI published a piece about one of the more interesting parts of MLB’s international spending market, building off reports that 16-year-old Lazaro Armenteros — Lazarito, as he is commonly referred to — is looking for a signing bonus in the range of $15-$20 million.

As mentioned, he’s expected to get a bonus in the $15-20 million range. Jim Bowden claims it could reach $25-30m. He’s 16 years old, has no performance record whatsoever. For all practical purposes, he’s in the same boat as any other international free agent his age. The record for largest signing bonus for an international free agent of this age is Nomar Mazara’s $4.95 million.

Sure, perhaps there’s inflation to consider. But are we really supposed to believe that Lazarito’s expected talent is roughly triple, or perhaps as much as six times higher, than the expected value of any other 16-year-old international player? Any 16-year-old international player ever?

That would be really hard to buy under any circumstances. But perhaps especially because no one even actually seems to be making that claim about Lazarito’s talent. People are certainly glowing about Lazarito, saying he has exceptional tools and blue-chip potential. Similar things were said about Miguel Sano, Wily Mo Pena, Michael Ynoa, and others. Similar things are said about one or two amateur free agents each season, or at least every couple of seasons. And yet no player in that age bracket has ever signed for more than $5m.

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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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“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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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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Deception seems impossible to quantify. How are you going to put a number on something like the Invisiball thrown by Yusmeiro Petit? The ball is there, and then it isn’t, and then it’s back! Put that in your number machine, nerd boy.

Except, hidden in that description of the Invisiball is a possible guide. The release point. The release point is a huge moment for the hitter — it can tell him about the type of pitch and type of movement he’s about to see even before the ball is released.

Think of Brad Ziegler. You see that arm dragging along the ground, and you know the ball is going to move down and away from you. You adjust. Think of Darren O’Day. You see that arm slot, and you think the ball will drop, and when it doesn’t, you miss his Submarine Riseball. Tyler Clippard! You see that over the top and you think the ball will rise — and his fastball does, but not his changeup.

So maybe deception is deviation from the expected movement given a pitcher’s arm slot. Or at least that’s maybe one sort of deception. It probably won’t help us understand Petit’s Invisiball any better, but it may give us something with which to work on this hard-to-define aspect of pitching.

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