Last night's Ortiz Grand Slam was the first in the postseason and 8th time in the RetroSheet canon (but probably overall) that four pitchers received earned runs on one play.

| game_id      | result_batter | batting_team_id | pitching_team_id | event_text           | home      | first     | second    | third     |
+--------------+---------------+-----------------+------------------+----------------------+-----------+-----------+-----------+-----------+
| BOS201310130 | ortizda01     | BOS             | DET              | HR/9/L9D.3-H;2-H;1-H | benoijo01 | albural01 | smylydr01 | verasjo01 |
+--------------+---------------+-----------------+------------------+----------------------+-----------+-----------+-----------+-----------+
+--------------+---------------+-----------------+------------------+-------------------------+-----------+-----------+-----------+-----------+
| game_id      | result_batter | batting_team_id | pitching_team_id | event_text              | home      | first     | second    | third     |
+--------------+---------------+-----------------+------------------+-------------------------+-----------+-----------+-----------+-----------+
| MIN196107041 | becquju01     | MIN             | CHW              | HR/9D.3-H;2-H;1-H       | hackewa02 | baumafr01 | kemmeru01 | piercbi02 |
| SEA198208060 | jacksre01     | CAL             | SEA              | HR/9.3-H;2-H;1-H        | vandeed01 | stantmi01 | anderla02 | bannifl01 |
| DET198307100 | parrila02     | DET             | OAK              | HR/7.3-H(UR);2-H;1-H    | jonesje01 | beardda01 | burgmto01 | codirch01 |
| SFN198709200 | esaskni01     | CIN             | SFG              | HR/7D.3-H;2-H;1-H       | perlmjo01 | leffecr01 | downske01 | robindo01 |
| SEA198805060 | sheripa01     | DET             | SEA              | HR/9.3-H;2-H;1-H        | jacksmi02 | solanju01 | powelde01 | mooremi01 |
| SDN200109010 | lankfra01     | SDP             | ARI              | HR/89.3-H;2-H;1-H       | kimby01   | sabeler01 | knotter01 | batismi01 |
| LAN200410020 | finlest01     | LAD             | SFG              | HR/89/F.3-H;2-H(UR);1-H | frankwa01 | hergema01 | chrisja01 | hermadu01 |

With the League Championship Series starting tonight, it's time to check out the Baseball-Reference Play Index if you haven't already signed up. What's the Play Index? It's a set of research tools that allow you to create customizable queries on our database, save the results, and share them with others. Using the PI, you can:

• Search full-season or multi-year totals to find your own custom leaderboards - Look at the entire history of baseball from 1871-2012 with every year, team, and position available, or filter the results in a vast number of ways: by specific years, by age, by first six seasons or last ten seasons, by American League only, by Cubs only, by switch-hitters, by catchers, by outfielder or infielder, by year of debut, but active or retired, by Hall of Famer, by height and weight, by living or deceased, or by a range of common statistical categories. Then sort the results by any common statistic, by the teams with the most players matching that category, by players with the most seasons matching that category, or by most recent, youngest, oldest, final year, or year of debut, and others.
• Search player game totals - Filtering on any of a dozen or more choices, search for games on a single player level, or on any batter from 1916-2012, or on any pitcher. The same can be done for Team Batting or Team Pitching Totals.
• Search player games looking for the most consecutive games matching a particular set of criteria - This can be done either on a single player level or on any batter in the last 97 years or on any pitcher. The same can be done for Team Batting or Team Pitching Streaks.
• Search the records of a specific player - Output a detailed summary and play-by-play list of all events of a specific type from a single year or an entire career. For example, you can see all of Harmon Killebrew's triples or even his outs to the second baseman.
• Search Batter vs. Pitcher Matchups - This tool presents a complete sortable list of batter or pitcher with totals for every opponent they faced by career or by year. Clicking on the player's name will lead you to a detailed output of their head-to-head plate appearances.
• ...And more!

Personal Subscriptions to the Play Index still cost just $36 for a year, $6 for a month, or $2 for 24 hours. Subscriptions may only be used by a single user, and there are discounts for users sponsoring at least $35 in pages.

Organizational Subscriptions can be set up for either an unlimited number of users ($600/year), or for up to five users ($125/year).

There are Two Steps to Subscribe to the Play Index:

1. Login to or create a Sports-Reference.com account (the same account used to sponsor pages).
2. Already logged in (or just created an account)? Go to our subscription page to sign up.

Our Always-Available Free Trial: Non-subscribers can use the PI's features as much as you like. However, your outputs will be restricted to a limited number of results.

The Play Index comes with a money back guarantee. We will gladly return the unused portion of any Play Index Subscription should you be dissatisfied with the Play Index.

So go ahead, give the Play Index a try -- we're confident that once you start using it, you'll wonder how you ever got along without it.

In case you missed it yesterday, we rolled out a couple of new goaltending stats for the 2014 season -- Save Percentage+ and Goals Saved Above Average. Overnight we got some feedback about SV%+ in particular, and the structure of having 1 minus the goalie's own SV% in the denominator of the formula. Right now, we are measuring the rate at which the league allowed more goals than the player, where 100 = average. So in the case of a 133 SV%+, the league's rate of goals allowed per shot would be 33% higher than the player's rate.

There are other alternatives. If we re-arrange the formula so that 1 minus the league SV% is in the denominator, we would be measuring the rate at which the player allowed fewer goals than the league. (Because of the nature of division, this is an important distinction from the definition in the previous paragraph.) If we tweak the formula in this direction, there are 2 options: we can compute a "minus" type of stat in which lower numbers are better, or we can stick with the "plus" style familiar to all from baseball's OPS+ and ERA+. The former would represent a goalie who allows 33% fewer goals than the league as a 67 (remember, lower is better); the latter would represent that as a 133.

(If any of this sounds familiar, it's because this battle was fought at Baseball-Reference 3 years ago and continues to rage in some corners of the internet to this day.)

As is the case sometimes in this business, there is no "right answer" here, but rather a matter of preference. For instance, we've long assumed users would find it counterintuitive to have a rate stat where lower numbers = better performance, but maybe that's not true. I'm interested in opinions on this, so let your voice be heard in the following poll -- which format do you prefer? Or do you care at all? I can't promise the poll-winning format will be what we eventually stick with, but I'd like to know what people think.

Today on Hockey Reference we're rolling out two new stats for goalie pages: Adjusted Save Percentage (SV%+) and Goals Saved Above Average (GSAA). First, you can check Broad Street Hockey for a great explanation of adjusted save percentage and goals saved, but for a simple look, consider the 2012-13 NHL season. League-wide, there were 41,827 shots overall and 3,684 goals scored, for a goals against average of 8.81%. Vezina Trophy winner Sergei Bobrovsky had a goals against average of 6.87% -- 29% better than league average, giving him a SV%+ of 129. Taking that 29% better performance into account combined with the number of shots he faced, we say he saved 21.48 goals more than an average goalie would have, given equal playing time.

These stats are especially helpful for comparing goalies across eras: Patrick Roy led the league in save percentage in the 1991-92 season with a .914 SV%; in the 2012-2013 season that would have placed him as the 26th best goalie between Ben Scrivens and Jonas Hiller. However, we can look at his SV%+ of 130 for that year and see that he was actually 30% better than the league average at stopping goals -- better than Bobrovsky, even.

Note that SV%+ has a minimum requirement of 4 shots faced per team game, so that we don't have goalies who stopped 7 of 7 shots faced in their single period played skewing the results. These stats are now up for goalies as far back as the 1983-84 season (the first year we have shots against data for the NHL), and for the entirety of the WHA (1972-1979), and will be updated throughout the year.

You may have seen our in-game Tweets and the win probability graphs on our box score pages -- we now have a detailed explanation of the win probability methodology from Neil Paine if you're curious how it works.

Using the play-by-play data that powers our play finder, I've built detailed season split pages for each team on offense and defense, as well as league total splits and league average splits for the year. Now you can compare your team's performance by field position to the league's, or see which team is best in the fourth quarter. If you can think of a situation you want to see that's not covered here, leave a comment & we'll see what we can do.

We often get emails about some of the more... let's say "esoteric" positional abbreviations in the P-F-R database (the most confusing of which date back to the earliest days of professional football). Here's a handy guide in case you ever get stuck wondering what in the world some of these positions are:

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