Archive for March, 2008

Welcome to the Majors: 3/30/08

Gregor Blanco made his major league debut last night as a pinch runner. He replaced Brayan Pena as the runner at first in the top of the 8th and did not return to field in the bottom of the inning. Blanco had a good spring by batting .326/.464/.442 which impressed enough to win him a roster spot as a potential outfielder. Last year in the International League (AAA) he had the 10th best OBP among qualified players.

Not exactly a player, but Nationals Park needs to be welcomed to the majors as well. I was in attendance during last night’s game and have to say the stadium is really nice. It reminds me a bit of Citizen’s Bank Park, which happens to be one of my favorite ball parks. Security was extremely tight including mandatory metal detectors due to President Bush’s attendance.

Much to my surprise, getting to the game was a cinch by Metro. I expected to have considerable wait times between transfers, but there was zero wait time and relatively short lines. Without a parking spot, I guess I’ll get to see if Metro can continue this level of competence all season long.


Get to Know: Win and Loss Advancement

+WPA (win advancement): The amount of positive wins a player contributed to his team, including only the plays where he increased his team’s win expectancy.

-WPA (loss advancement): The amount of negative wins a player contributed to his team, including only the plays where he decreased his team’s win expectancy.

How it’s calculated: It’s calculated exactly the same as WPA, but it only includes the positive (+WPA) or negative (-WPA) results.

Why you should care: It further breaks down WPA letting you understand how big a positive or negative contribution a player made to his team. A player who has a WPA of 1.25 could have made both huge positive and huge negative contributions to his team.

Links and Resources:

Win Shares and Loss Shares


Get to Know: Win Expectancy

WE (win expectancy): The percent chance a particular team will win based on the score, inning, outs, runners on base, and the run environment.

Assumptions: Win expectancy as it’s currently calculated assumes that each team has an equal chance of winning at the start of a game.

Specifics: FanGraphs uses Tangotiger’s most current win expectancy tables which are available for 3.0 to 6.5 run environments in increments of .5 runs. The league average run environment is used to calculate win expectancy. When the run environment falls in between a .5 increment, the tables are then weighted accordingly to achieve the correct win expectancy.

Links and Resources:

Hardball Times: The One About Win Probability
Walk Off Balk: Win Expectancy Finder
The Book Wiki: Win Expectancy


Get to Know: Clutch

Clutch: A measurement of how much better or worse a player does in high leverage situations than he would have done in a context neutral environment.

How it’s calculated: WPA / pLIWPA/LI

Why you should care: Unlike tradition clutch statistics (close & late), Clutch is a much more comprehensive statistic taking into account all situations that may or may not have been high leverage. Additionally, instead of comparing a player to the rest of the field, it compares a player to himself. A player who hits .300 in high leverage situations when he’s an overall .300 hitter is not considered Clutch.

Links and Resources:

All About Clutch
Baseball Fever Forum: SABR Matt


Notes From the Opener

The Japan series is over and no longer do I have to wake up at 6am to catch my daily dose of baseball. I like the idea of having a few games in Japan, but I don’t like having the season opener completely disjointed from the “other” season opener that will take place this Sunday night. It’s kind of a tease. Which leads me to Rich Harden.

Oh Rich Harden, I took a chance on you in all my fantasy drafts last year, but completely forgot about you this year! Needless to say, it looks like this could have been a huge mistake on my part. You struck out 9 in 6 innings of work while only allowing 3 hits and 1 run. The last time you struck out 9 was all the way back in 2005. I pleaded with you last year to stay healthy and it didn’t work so I’ll try again: Please stay healthy this year so you can dazzle us with your pitching ability.

Keith Foulke who retired in 2007 due to health reasons, pitched an inning in both games and struck out 2 while allowing not a single run. He entered both games as the setup man and was used in a fairly high leverage situation (LI of 2.17) in the first game. So far so good for the 35 year old.

Emil Brown made a big base-running error in the first game costing the A’s .25 wins (only -.064 wins overall). He tried to remedy his error in the second game by leading all batters with a WPA of .12 wins, courtesy of his 3 run homer in the 3rd inning.

And finally, Manny Ramirez now leads everyone in WPA and has already eclipsed his 2007 WPA total of .31. Looks like he’s already started to rebound from his worst season ever.

And don’t forget to check out Studes’ latest “Ten Things” column over at The Hardball Times where he delves into the merits of WPA/LI among other things.


2008 Stats: Now Updated

The site is now up to date with 2008 stats and will of course be updated nightly. The new pitch data usually runs a day or two behind and that’s why all the pitchers in yesterday’s game have undefined pitch type and velocity data.

Couple quick reminders:

– We’ll have live win probability data all season long including the all-star game and playoffs.

– The live play-by-play data is different from the data that becomes “official” in the nightly loads, which often causes WPA values to change slightly from those found in the live data.


The Great Clutch Project

Tangotiger is running his Clutch Project to see if you know which players on your favorite team are clutch. All you need to do is vote for which player you’d want to have at-bat when the game is on the line.

Once the votes are in, we’ll be compiling the results on a daily basis during the season. In the mean time, go vote!


Live Play Logs & Box Scores

Just as the title says, there are now play logs and box scores for live data. Unlike the graphs they do not update automatically, so you’ll have to refresh the page if you want the latest data. I might change that if enough people would prefer to have it update automatically every 30 seconds to a minute.


Get to Know: WPA/LI

WPA/LI (context neutral wins / game state linear weights): How many wins a player contributes to his team with the Leverage Index aspect removed, invented by Tom Tango.

Calculating WPA/LI: WPA is divided by LI for each individual play attributed to a specific player and then the WPA/LI for the individual plays is then added up to create WPA/LI for an entire season. This is considerably different then taking a player’s WPA and dividing it by pLI.

Why you should care: Unlike standard linear weights, WPA/LI does take into account the situation. So at times when a walk would be just as valuable as a home run, WPA/LI accurately weights the walk and the home run, where linear weights would still give .13 wins to the home run and the walk .03 wins.

Links and Resources:

Unleveraging Win Probability
The Book Wiki: Linear Weights


Live Win Probability: Spring Games

The following spring training games should be available with live Win Probability and of course we’ll have all regular season, all-star, and playoff games with live Win Probability as well.

3/18/2008 4:05PM OAK TEX
3/18/2008 4:05PM KC CHC

3/19/2008 12:05PM TOR BOS
3/19/2008 4:05PM COL CWS

3/20/2008 1:05PM TB CLE
3/20/2008 1:05PM FLA STL

3/21/2008 1:05PM TOR DET
3/21/2008 1:10PM WAS NYM

3/24/2008 1:05PM STL MIN
3/24/2008 4:05PM SD LAA


Get to Know: Leverage Index

LI (leverage index): A measure of how important a particular situation is in a baseball game depending on the inning, score, outs, and number of players on base, created by Tom Tango.

Baselines: The average LI is 1 and is considered a neutral situation. 10% of all real game situations have a LI greater than 2, while 60% have a LI less than 1.

Why you should care: Because LI puts a single number on the importance of a situation, it creates a much simpler and specific way of determining which situations in games are important. It can also be applied to players. See below for various LI player stats:

pLI: A player’s average LI for all game events.
phLI: A batter’s average LI in only pinch hit events.
gmLI: A pitcher’s average LI when he enters the game.
inLI: A pitcher’s average LI at the start of each inning.
exLI: A pitcher’s average LI when exiting the game.

See Critical Situations: Part 3 for more details

Additional Links and Resources:

Critical Situations Part 1, Part 2, Part 3
Leverage Index Tables


Pitch Type & Velocity: Leaderboards

The leaderboards are up for Pitch Type & Velocity! There are a couple standard leaderboard functions that do not work with the Pitch Type tab.

-Starters and Relievers cannot be broken down yet.
-You cannot filter by league.
-You can select the minimum IPs.
-You can select only qualified players.

If there’s a % sign in the column, it’s the percentage of pitches thrown and if there’s a “v” after the pitch type, it’s the average velocity of the pitch.

Quick refresher on what means what: FB – Fastball, SL – Slider, CT – Cutter, CB -Curveball, CH- Changeup, SF – Split-fingered Fastball, KN – Knuckleball, XX – Unidentified, PO – Pickoff Attempt


Get to Know: Runs Created

RC (runs created): An estimator of how many runs a batter produces for his team, created by Bill James.

“Basic”: ((H + BB) * (1B + (2*2B) + (3*3B) + (4*HR))) / (AB + BB)

“Technical”: ((H + BB – CS + HBP – GDP) * ((1B + (2*2B) + (3*3B) + (4*HR) + (.26 * (BB – IBB + HBP)) + (.52 * (SH + SF + SB)))))/ (AB + BB + HBP + SF + SH)

Which formula and when: FanGraphs employs both formulas depending on what stats are available for individual seasons. Seasons prior to 1955 use the “Basic” formula and any season after and including 1955 uses the “Technical” formula.

Why you should care: Runs Created is a good estimator of how many runs a team should have scored in a given season. When applied to players, it is somewhat less accurate though still a useful estimator of a player’s actual production.

Variations: There are other run estimators that do a better job then Runs Created, yet one of the main advantage of Runs Created is that it’s extremely easy to calculate. Other run estimators include: Batting Runs, Base Runs, Extrapolated Runs, Estimated Runs Produced, Equivalent Runs.

Links and Resources:

Wikipedia: Runs Created
A Brief History of Run Estimation: Runs Created
How Runs are Really Created Part 1, Part 2, Part 3
The Book Wiki: Runs Created
The Book Wiki: Run Estimators


Get to Know: RE24

RE24 (runs above average by the 24 base/out states): RE24 is the difference in run expectancy (RE) between the start of the play and the end of the play. That difference is then credited/debited to the batter and the pitcher. Over the course of the season, each players’ RE24 for individual plays is added up to get his season total RE24.

Calculation Example
: In game 4 of the 2007 World Series, the RE for the Red Sox to start the inning was .52. When Jacoby Ellsbury doubled off Aaron Cook in the very first at-bat in the game, the Red Sox were then expected to score 1.15 runs for the rest of the inning. The difference or RE24 was .63 runs. Ellsbury was credited +.63 runs and Aaron Cook credited with -.63 runs.

Why you should care: RE24 tells you how many runs a player contributed to his team. It’s similar to WPA (except in runs), but unlike WPA it does not take into account the inning or score of the game. Therefore, it is a more context neutral statistic. It does however take into account how many runners are on base and how many outs are left in the inning.

Variations: REW (run expectancy wins) is RE24 converted to wins.

Links and Resources:

Run Expectancy by Run Environment
The Book Wiki: Run Expectancy


Pitch Type & Velocity

I put up something new today which I think is very cool. Under each pitcher page, in the very bottom table, you can now see the percentage of each type of pitch a player threw and its average velocity. These stats are available from 2005-2007 and will be updated daily when the season starts.

Some quick things to note:

-The average velocity is in parenthesis next to the % of the pitch thrown.

-The percent of any known pitch type is a percentage of only known pitch types thrown. XX is an unidentified pitch type and is taken as a percentage of all pitches thrown.

-PO are pickoff attempts and are calculated as a percentage of all pitches thrown.

A huge thanks goes out to Baseball Info Solutions for allowing me to do this. This is a work in progress and there’s more that can be done with stats like these so feel free to chime in with suggestions.

Update: I’ve removed SW (Screwball), FO (Forkball), and SI (Sinker) and moved them into SF (Split-fingered Fastball). There were just so few pitches categorized as those three, it didn’t make sense for them to have their own bucket.

FB: Fastball, CT: Cutter, CB: Curveball, SL: Slider, CH: Changeup, SF: Split-fingered Fastball, KN: Knuckleball, XX: Unidentified, PO: Pickoff Attempt


Get to Know: WPA

WPA (win probability added): WPA is the difference in win expectancy (WE) between the start of the play and the end of the play. That difference is then credited/debited to the batter and the pitcher. Over the course of the season, each players’ WPA for individual plays is added up to get his season total WPA.

Calculation Example: In game 4 of the 2007 World Series, the WE for the Rockies started out at 50%. When Jacoby Ellsbury doubled off Aaron Cook in the very first at-bat in the game, the Rockies WE declined to 44.2%. The difference or WPA was .058 wins (5.8%). Ellsbury was credited +.058 wins and Aaron Cook credited with -.058 wins.

Why you should care: WPA takes into account the importance of each situation in the game. A walk off home run is going to be weighted more then a home run in a game that has already gotten out of hand. This makes it a great tool for determining how valuable a player was to his team’s win total.

When not to use it: WPA is more of a descriptive statistic and not that great of a predictive statistic. There are better statistics to use in raw player evaluations than WPA.

Links and Resources:

The Hardball Times: The One About Win Probability
The Book Wiki: Win Probability Added
Wikipedia: Win Probability Added
WPA is… WPA is not…


Get to Know: K/9

K/9 (strikeouts per 9 innings): The average of how many batters a pitcher strikes out per 9 innings pitched.

Calculated as: (SO * 9) / IP

Why you should care: K/9 is a perfectly suitable way to evaluate a player’s ability to strike batters out.

Current Baselines
(2002-2007): The average K/9 for starting pitchers is 6.17 and 7.21 for relievers. For starting pitchers the top and bottom 20th percentile are a K/9 above 7.56 and below 4.89. Relievers top and bottom 20th percentiles are a K/9 above 8.94 and below 5.54.

Variations: Some people prefer to use strikeouts per batter faced (K% or K/G) to express a player’s ability to strike batters out. The difference is minimal and the argument for using K% is that K/9 excludes walked batters and K% does not, suggesting that K/9 may either overstate or understate a pitcher’s overall effectiveness (not pure strikeout ability).

Links and Resources:

Wikipedia: Strikeouts per 9 innings pitched
U.S.S. Mariner: Evaluating Pitcher Talent


Get to Know: The Stats

Because the FanGraphs glossary sucks so much, I’ve decided to update the glossary by posting one article each day on a particular statistic.

They’ll be easily accessible through the blog and eventually the glossary tab once all the stats are completed. Until then the old glossary will remain intact. Overall, I’m trying to make them fairly thorough, but feel free to comment and add new links and information if you feel what I post is incomplete or inadequate.


Bill James Projections: Updated

Just as the title says, they’ve been updated to the latest and greatest. There are a few players not in the database yet and here are their projections:

Alexei Ramirez: .282/.347/.455 (220 AB)
Kosuke Fukudome .289/.368/.476 (557 AB)

Hiroki Kuroda: 10-10, 0 SV, 175 IP, 115/52 K/BB, 4.01 ERA
Kazuo Fukumori: 3-4, 2 SV, 60 IP, 41/35 K/BB, 5.25 ERA
Masa Kobayashi: 4-4, 0 SV, 68 IP, 50/19 K/BB, 4.24 ERA
Yasuhiko Yabuta: 4-4, 0 SV, 75 IP, 61/28 K/BB, 4.08 ERA


MINER Projections

Jeff Sackmann of MinorLeagueSplits.com fame created his own set of projections for use in John Burnson’s Graphical Player 2008. He was kind enough to offer them for use on FanGraphs and now they’re available in the player pages and in their own sortable stats page.

His MINER projections are based off of the Marcel projections, but take into account batted ball data and minor league stats, including minor league batted ball data.

Still working on getting a link for a downloadable spreadsheet of the projections, but that should soon be available for those of you who want to play with them.