It seems like it should matter how hard you hit the baseball. That statement probably seems self-evident, but until this year we haven’t really had a whole lot of evidence to demonstrate whether that’s true. We have an old month of HITf/x data from 2009 and there’s non-public data about exit velocity, but until StatCast data arrived this year, we didn’t really have the tools to determine how much quality of contact matters.

Last week, FanGraphs launched quality of contact statistics courtesy of Baseball Info Solutions to add to this effort. The methodology isn’t based solely on a raw exit velocity, but the data stretches back to 2002 and it’s publicly available now and easy to manage. As soon as people realized the data was available, the sabermetric masses went to work to run preliminary tests on the data. One of the interesting things that showed up right away was that the data didn’t do a great job predicting itself in the future and things like Hard% didn’t correlate with stats like BABIP or LD% as well as we might have otherwise thought.

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When MLB added a second Wild Card in each league for the 2012 season, making a version of the postseason got easier. More teams were invited into the season’s final month, even if you want to make conditioned arguments about how adding the extra teams changed the nature of in-season roster decisions. Over three seasons, we’ve had six second Wild Cards who averaged just under 90 wins per team per season. It’s a small sample as far as trends go, but the values have been lower in the National League and have generally decreased each year.

As a result, we can essentially say that the average second Wild Card will win about 90 games this year. It might be more or less, but it’s a fairly safe starting assumption. It’s an assumption you take into account when thinking about your team’s chances of making the playoffs. We’ve seen teams make the postseason with fewer wins, and in an age of increasing parity, 88 might do the trick as well. In general, a 90 win team has performed well enough that they will very likely make the playoffs under the current regime.

Which brings us to the 14-7 Houston Astros who currently lead the AL West by four games on April 30. The Astros, if you haven’t noticed, have been bad for quite a few years, and there was an expectation entering the 2015 season that they would remain relatively unimportant to the AL playoff picture. They averaged 58 wins over the previous four seasons, and while they built a team that our Playoff Odds machine projected for 78 wins in 2015, that’s a far cry from the amount needed to make the postseason, as we just learned.

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At some point this year, the samples will be large enough that every post doesn’t have to come with a massive disclaimer. Of course we’re dealing with minuscule samples, but interesting things can happen in minuscule samples even if they don’t provide a lot of externally useful information. In particular, the first month of a baseball season can bring some extremely unusual and compelling stat lines, especially when dealing with metrics that are designed to be useful over larger samples. Enter Nick Martinez.

Martinez was the 564th pick in the 2011 draft and likely only has a safe spot in an MLB rotation this year because he is a member of a Rangers organization that has been decimated by injuries. While we saw Martinez toss 140 innings in his age 23 season in 2014, they were bad innings. He posted a 113 ERA- and 128 FIP-, both of which are still using park factors that treat Globe Life Park as if it’s more hitter friendly than it’s played since the renovations. If we’re being generous, he pitched like a replacement level starter and you might argue he was worse.

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On Wednesday, Collin McHugh pitched well against the Ben Zobrist-less Oakland A’s. Zobrist’s absence made the A’s a weaker version of themselves, but they were still a tougher opponent than the hapless Rangers he saw five days earlier. While McHugh only tossed 5.2 innings and faced just 23 batters, he tied Trevor Bauer for the single-game strikeout lead for 2015 with 11. Although unlike Bauer, McHugh walked zero A’s instead of five Astros.

This is largely noteworthy because Collin McHugh was one of the most prominent breakout players from a year ago, and we’re dying to know how much of that breakout we should take to heart. In 2014, McHugh was a 3-4 win player, who could have been a solid number two starter on almost any team in the league and he posted those numbers in under 160 innings. If McHugh is actually that able, the Astros have five more seasons of a very good pitcher who can help anchor their next playoff rotation.

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If someone asked you to guess which right fielder provided the most value on the defensive side of the ball last year, the only logical answer is Jason Heyward. Heyward was so far above his compatriots that you almost wonder if he was simply not supposed to be a right fielder and that Fredi Gonzalez’s lineup card handwriting was somehow confusing the players and sending them to the wrong positions.

Heyward posted 32 defensive runs saved and a 24.1 ultimate zone rating in 1317 innings in right field. No one else was even in the ballgame, but if you had to guess who was second, it might be a little more difficult. Enter Kevin Kiermaier. Kiermaier’s 14 DRS and 16 UZR in right field landed him at second on a list of right fielders sorted by DEF, which is UZR and the positional adjustment.

DEF is a cumulative statistic, meaning more opportunities can lead to higher numbers. Heyward’s DEF was 17.3 and Kiermaier’s was 13.3, but Kiermaier played just 526.1 innings in right field last year. If you convert those marks to a rate statistic, say UZR/150, then Kiermaier rockets up to an insane 56.6 UZR/150 while Heyward settles just above 20. By the numbers, Kiermaier was the most dazzling defender we saw in right field last year.

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Last week, we rolled out some minor tweaks to WAR, one of which was the addition of wGDP. If you haven’t read the primer, wGDP is a measure of double play runs above average and captures how many runs you save your team by staying out of double plays.

In general, it’s a minor piece of the overall puzzle with the best and worst players separated by less than a win of value over the course of a full season. Staying out of double plays helps your team, but even the best players don’t stay out of a large enough number to swing their value in a big way. Introducing wGDP makes WAR a better reflection of reality and that’s a good thing, but it also allows us to better measure the GIDP column we’ve all seen for years because it puts double plays in the context of double play opportunities.

Dave and August have already looked at some surprising and obvious players who are great at staying out of double plays, but I wanted to consider this new statistic from another angle. For the most part, it seems like staying out of double plays should be a base running issue, as you have to be fast enough to get to first before the infield twists it.

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What do we have here? For an explanation of this series, please read this introductory post. As noted in that introduction, the data below is a hybrid projection of the ZIPS and Steamer systems, with playing time determined through depth charts created by our team of authors. The rankings are based on aggregate projected WAR for each team at a given position.

Yes, we know WAR is imperfect and there is more to player value than is wrapped up in that single projection, but for the purposes of talking about a team’s strengths and weaknesses, it is a useful tool. Also, the author writing this post did not move your team down ten spots in order to make you angry. We don’t hate your team. I promise.

As usual, we’ll kick this off with a graph of each team’s projected right fielders by WAR, while also acknowledging that 0.4 wins here or 0.3 wins there isn’t really a tangible difference.

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In the grand scheme of things, evaluating a baseball player’s current ability isn’t that difficult. If you have a sampling of their statistics and have a chance to watch a handful of their games, a reasonably informed observer will come up with a pretty good estimate of the player’s current talent level. Figuring out how good a player is right now requires some skill, but it’s nothing compared to having that same information about a player and attempting to forecast six years into the future.

That’s the job of a scout. You get a handful of looks at a 19 year old, you talk to a few people, you glance at some numbers, and then you’re asked to predict what that player is going to look like at 25. It’s a big ask and as a result, there’s a pretty big margin of error. A good scout should be more accurate than a decently competent observer, but no one would expect a scout to be right on every player. There’s just too much uncertainty involved.

One would hope that a scout doesn’t miss any Mike Trouts or bet high on many Jeff Larishs, but they’re going to miss good players and speak highly of bad one’s during the course of their careers. That’s especially true with respect to very young players.

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Ian Desmond is a success story. There isn’t another way to spin it. He spent his first two seasons as a big league regular playing below big league regular levels. He was fortunate to be young enough and on a team that wasn’t quite ready to compete, otherwise he might not have gotten another real opportunity. After two plus years at the major league level, he was sitting on 1,302 plate appearances and 2.5 WAR.

That’s a fine number for most of the world’s population, but with Nationals gearing up to become real contenders in 2012 Desmond was entering a sink or swim kind of season. He was 26, a good base runner, an average defensive player, and he only looked average at the plate if you compared him to other shortstops. Something had to change or the Nationals would have had to look elsewhere.

Obviously, something changed. Desmond’s defense got better and he started to hit for power. While he wasn’t known for Vottoian command of the strike zone, he held his own while also connecting for extra bases. His glove started to come along and over the last three years he’s at 14 WAR in 1,850 PA. A terrific success story and reason enough to pump the breaks after any down season early in a player’s career.

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The way in which people evaluate defense fascinates me. Not because I find defense fascinating, per se, but because it strikes me as a very different evaluation process than the one most people use when evaluating offensive performance. I think this applies to both casual and die-hard fans, just to varying degrees.

Offensive evaluation is largely based on basic accounting. As a fan, analyst, or someone directly connected to the game, you weigh a player’s offensive actions against one another to develop an idea of their performance. Some people might choose to use a linear weights structure, or some might think only in RBI or RISP, but the methodology is largely consistent for each person. Each plate appearance is weighed based on its importance and not on the outcome.

Some will choose to treat each PA pretty equally, some will choose to place a lot of weight on certain moments, but it’s a predictable process. When evaluating defense, I believe things get much less clear.

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