Entering play on Thursday night, Kyle Seager owned a .274 batting average. Chris Johnson’s average was a nearly identical .273. The two third basemen have played in a similar number of games and have come to the plate close to the same number of times. If you use batting average to evaluate these players’ seasons, you’d come to the conclusion that Seager and Johnson are essentially equivalent players this year.

They’re not. In fact, it’s very clear Seager is substantially better than Johnson. Let me rephrase that: It’s very clear Seager is better than Johnson — but only if you’re well-versed in the language of baseball statistics. If you know how to properly value walks, extra base power, baserunning and defense, the difference between Seager and Johnson is impossible to miss.

At FanGraphs, our writers use statistics and metrics like wOBA, wRC+, FIP and WAR to evaluate baseball players and teams. We provide those tools, and more, so others might conduct evaluations on their own. Want to know Miguel Cabrera’s wOBA against lefties? You can find that on FanGraphs. But what if you don’t know what wOBA means, how it’s calculated or why you should care about it more than batting average?

You can find some of that information on FanGraphs. A well-motivated, self-starter could show up at the site, notice something called wOBA on the leaderboards, go to the glossary and figure out what it means and why it’s important. But it can be intimidating and challenging for people who are just starting out to make sense of everything we offer.

In an effort to make advanced statistics easier, and to understand and to better use the data and features available at FanGraphs, we’re relaunching and promoting the FanGraphs Library. There’s a lot of great information there already, but this revamped library is even better. There’s a steep learning curve, though, so I’ve been tasked with making things a bit simpler.

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With the addition of the new heatmaps, we have a new tool that lets you whip up league average heatmaps.

The tool can be conveniently accessed under the “leaders” section in the site’s main navigation.

I’m pleased to announce that we’ve rolled out new heatmaps to the site!

There are a number of ways to customize each heatmap:

– Options to choose either a traditional 5×5 grid or a more granular 10×10 grid.

– Choose a heatmap from the viewpoint of either the pitcher or the batter.

– For the 10×10 grid, you can choose your own level of smoothing, which will change the weighting of adjacent buckets.

– Filtering on single or multiple years, handedness, and count.

– A variety of different stats to choose from.

The color grading on the heatmaps is always compared to an MLB average player for the selected time period and handedness.

By popular demand, we’ve added K% – BB% (K-BB% on all pages) to all pitchers stats sections, including leaderboards, player pages, splits, etc….

Enjoy!

We’ve updated our WAR Graphs tool to include pitcher comparisons:

Source: FanGraphs — Pedro Martinez, Clayton Kershaw, Sandy Koufax

It’s also now possible to compare batters and pitchers on the same graph:

Source: FanGraphs — Clayton Kershaw, Felix Hernandez, Justin Verlander

The game log section on the player pages will now give you an extra line of data that displays the totals for the dates you selected.

For instance, if you wanted to see all of Mike Trout’s games since September 1st, 2013, you’d see he’s had a wRC+ of 172 over that same time period.

This feature is available for the minor league game logs too.

There are now splits options on the FanGraphs leaderboards that allow you to see exactly how a player performed at an individual position. These positional splits also include a Value tab, so you can see a player’s WAR totals and components at a specific position.

Please note that these are different from the existing positional filters, which filter on qualified players (25% of games played) at a particular position. The new splits will only show the stats for a player while he was playing a specific position.

This is particularly useful at the team and league level where you don’t want full season stats from players who play multiple positions in your leaderboard.

For every game this year we’ll be projecting the odds of each team winning on our live scoreboard. We’ve also added an extra experimental line on live Win Probability graphs that adjusts for the newly calculated game odds.

To calculate these game odds we’re doing the following:

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We have a new section on both the leaderboards and player pages that now displays Inside Edge fielding data.

Inside Edge scouts watch every play and grade how easy or difficult it is to successfully field on the following scale:

• Impossible (0%)
• Remote (1-10%)
• Unlikely (10-40%)
• About Even (40-60%)
• Likely (60-90%)
• Almost Certain / Certain (90-100%)

We’ve aggregated all the data and made it available for you to peruse on a player-by-player basis:

In addition, this data will be updated nightly during the 2014 season!

The 2014 ZiPS projections are now available in the player pages and on the sortable projection pages. Much thanks to Dan Szymborski for once again providing his projections!

With the arrival of the ZiPS projections, we’ve updated our depth charts and projected standings to be a combination of both ZiPS and Steamer projections. Additionally, our playoff odds are now computed using a combination of both ZiPS and Steamer.