CSS Button No Image Css3Menu.com

Baseball Prospectus home
  
  
Click here to log in Click here for forgotten password Click here to subscribe

Premium and Super Premium Subscribers Get a 20% Discount at MLB.tv!

Articles Tagged Sample Size 

Search BP Articles

All Blogs (including podcasts)

Active Columns

Authors

Article Types

Archives

05-09

comment icon

5

Baseball Therapy: Should I Worry About My Favorite Pitcher?
by
Russell A. Carleton

07-24

comment icon

6

Baseball Therapy: It Happens Every May
by
Russell A. Carleton

07-16

comment icon

16

Baseball Therapy: It's a Small Sample Size After All
by
Russell A. Carleton

12-02

comment icon

19

Prospectus Hit and Run: Resetting the Standard
by
Jay Jaffe

11-08

comment icon

14

Baseball ProGUESTus: Getting Explicit with Sample Sizes
by
Matt Lentzner

10-26

comment icon

16

Spinning Yarn: Can We Predict Hot and Cold Zones for Hitters?
by
Mike Fast

09-24

comment icon

71

Spinning Yarn: Removing the Mask Encore Presentation
by
Mike Fast

06-01

comment icon

6

Spinning Yarn: The Real Strike Zone, Part 2
by
Mike Fast

04-21

comment icon

5

Collateral Damage: The Concussion Discussion, Part II
by
Corey Dawkins and Marc Normandin

02-16

comment icon

59

Spinning Yarn: The Real Strike Zone
by
Mike Fast

08-29

comment icon

2

Between The Numbers: The PITCHf/x Summit Quasi-Liveblog
by
Ben Lindbergh

05-28

comment icon

1

Ahead in the Count: Hometown Discounts
by
Matt Swartz

04-26

comment icon

4

Baseball Therapy: The Difference Between Night and Day
by
Russell A. Carleton

04-21

comment icon

6

Fantasy Beat: When Sample Size Matters
by
Marc Normandin

04-08

comment icon

2

Manufactured Runs: April is the Cruelest Month
by
Colin Wyers

01-22

comment icon

43

Under The Knife: Frickin' Laser Beams, Part 1
by
Will Carroll

08-05

comment icon

17

Changing Speeds: PECOTAs Wild Pitches
by
Ken Funck

07-23

comment icon

55

Changing Speeds: PECOTA's Strikeouts
by
Ken Funck

07-05

comment icon

14

Prospectus Idol Entry: Cartwright Interview Transcript
by
Brian Cartwright

02-12

comment icon

24

Future Shock: Royals Top 11 Prospects
by
Kevin Goldstein

03-18

comment icon

0

Prospectus Today: It Doesn't Count
by
Joe Sheehan

03-13

comment icon

0

Prospectus Hit and Run: Running Afoul
by
Jay Jaffe

04-09

comment icon

0

Prospectus Today: Playing Games
by
Joe Sheehan

10-06

comment icon

0

Prospectus Matchups: October Musings
by
Jim Baker

04-18

comment icon

0

Prospectus Today: Confirmation Bias
by
Joe Sheehan

03-03

comment icon

0

Lies, Damned Lies: PECOTA Takes on Prospects, Part Four
by
Nate Silver

12-01

comment icon

0

Crooked Numbers: Plop Plop Fizz Fizz
by
James Click

09-13

comment icon

0

Doctoring The Numbers: The Draft, Part Seven
by
Rany Jazayerli

08-04

comment icon

0

Crooked Numbers: Objects at Rest
by
James Click

06-24

comment icon

0

Prospectus Notebook: Friday Edition
by
Baseball Prospectus

05-10

comment icon

0

Prospectus Triple Play: Florida Marlins, New York Yankees, Pittsburgh Pirates
by
Derek Jacques

04-27

comment icon

0

Lies, Damned Lies: Does Size Matter?
by
Nate Silver

04-21

comment icon

0

Crooked Numbers: April Fools
by
James Click

04-13

comment icon

0

Prospectus Triple Play: Florida Marlins, New York Yankees, Pittsburgh Pirates
by
Derek Jacques

03-07

comment icon

0

Fantasy Focus: Fantasy Feng-Shui
by
Erik Siegrist

03-03

comment icon

0

Crooked Numbers: The Morning After
by
James Click

02-24

comment icon

0

Crooked Numbers: More on the Lineup
by
James Click

02-21

comment icon

0

Prospectus Roundtable: Top 50 Prospects, Part I
by
Baseball Prospectus

02-20

comment icon

0

Baseball Prospectus Basics: Statistical Consistency
by
James Click

02-19

comment icon

0

Baseball Prospectus Basics: Measuring Offense
by
Dayn Perry

05-29

comment icon

0

Aim For The Head: Simulating Catcher's ERA
by
Keith Woolner

05-22

comment icon

0

Prospectus Feature: Analyzing PAP (Part Two)
by
Keith Woolner

05-22

comment icon

0

Analyzing PAP (Part Two)
by
Keith Woolner

05-21

comment icon

0

Prospectus Feature: Analyzing PAP (Part One)
by
Keith Woolner

05-21

comment icon

0

Analyzing PAP (Part One)
by
Keith Woolner

04-18

comment icon

0

Sensible Revenue Sharing
by
Keith Woolner

07-18

comment icon

0

Doctoring The Numbers: The Burroughs Hypothesis
by
Rany Jazayerli

09-22

comment icon

0

From The Mailbag: Umpire Stolen Base Rates and Scott Sheldon
by
Baseball Prospectus

01-10

comment icon

0

Field General or Backstop?
by
Keith Woolner

<< Previous Tag Entries Next Tag Entries >>

More research is needed before we can truly know the effects of sleep on player performance.

Last week, we talked about the effects of sleep (or lack thereof) on a player’s performance, and it was all nice and theoretical, and at the end, I mumbled something about how a brilliant researcher might, in the future, be able to come up with some way to quantify these sorts of things. Welcome to the future. (See what I did there?)

The rest of this article is restricted to Baseball Prospectus Subscribers.

Not a subscriber?

Click here for more information on Baseball Prospectus subscriptions or use the buttons to the right to subscribe and get access to the best baseball content on the web.


Cancel anytime.


That's a 33% savings over the monthly price!


That's a 33% savings over the monthly price!

Already a subscriber? Click here and use the blue login bar to log in.

This is a BP Fantasy article. To read it, sign up today!

April 21, 2010 12:49 pm

Fantasy Beat: When Sample Size Matters

6

Marc Normandin

Contrasting fantasy to real life from a sample size perspective.

I face a dilemma almost daily as a fantasy analyst, given my background in sabermetrics. I know that sample size is important--without a proper sample size, it's hard to take a player's recent performance (for better or worse) seriously. But fantasy baseball is a game that requires quick decisions--you aren't the only person wondering if a player is for real or not, and there is always someone more desperate than you are for any help they can get. We know when statistics matter for baseball analysis of the real thing--you can thank a certain Baseball Prospectus author for that information--but oftentimes (okay, all of the time) you don't have enough time to wait for the information you need for an informed decision.

For example, I wrote about how Jeff Francoeur was worth keeping an eye on due to a potentially newfound understanding of the strike zone. He's taking more walks even if he isn't taking more pitches, and it may just have to do with recognizing which pitches he should and can drive and which ones he should sit on. As far as regular baseball analysis goes, I'm more cautious towards Frenchy because we don't have the sample size to know if this is random variation or not, but as a fantasy analyst (and owner) I scooped up Francoeur off of waivers in one league in the hopes that his performance is for real. When you can't afford to wait for the necessary information, you have to learn to read what is available to you to the best of your ability. You're going to swing and miss like our friend Francoeur, but when you do connect, it's going to go a long way.

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

This is a BP Premium article. To read it, sign up for Premium today!

April 8, 2010 1:02 pm

Manufactured Runs: April is the Cruelest Month

2

Colin Wyers

First-month stats don't give analysts much to analyze.

April really is a great time to be a baseball fan. Even in the worst case (say, being a Cubs fan and watching Carlos Zambrano getting lit up list a Christmas tree on Opening Day), having baseball is better than not having baseball. And April is truly a time when all baseball fans can have hope. Nobody’s been eliminated yet. Nobody’s even out of the race yet. Now, of course, some things are more likely than others—but that’s not what hope is about, is it?

So it’s a great time to be a fan. But it’s a horrible time to be a baseball analyst. (That's still a net win, really, as baseball analysts are generally also baseball fans.) Why do analysts suffer? Because there’s an expectation that since there’s baseball going on, and since one is a baseball analyst, one must, well, analyze that baseball. The thing is—there’s not really a whole lot one can say about a month’s worth of ballgames, at least in the way of useful analysis. There’s little we can know in April that we didn’t already know in March.

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

This is a BP Premium article. To read it, sign up for Premium today!

January 22, 2010 11:54 am

Under The Knife: Frickin' Laser Beams, Part 1

43

Will Carroll

The effects of LASIK on player performance, started with a specific example.

with Chase Gharrity

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

This is a BP Premium article. To read it, sign up for Premium today!

August 5, 2009 1:47 pm

Changing Speeds: PECOTAs Wild Pitches

17

Ken Funck

Which moundsmen has BP's projection tool missed with any regularity?

Several weeks ago in this space I took a look at batters that PECOTA has habitually overrated or underappreciated over a period of several seasons. Today I'll take a look at starting pitchers to see if we can identify those that continually flummox PECOTA by making a mockery of their pre-season forecasts year after year.

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

This is a BP Premium article. To read it, sign up for Premium today!

July 23, 2009 12:36 pm

Changing Speeds: PECOTA's Strikeouts

55

Ken Funck

Who consistently surpasses or underwhelms their projections?

One of baseball's enduring charms is its ability to defy prediction. Each time we think we're absolutely sure of something-say, that the 2008 Tigers will score a bajillion runs, or Juan Pierre will be a disaster filling in for Manny Ramirez-our forecasts are confounded by baseball's eternally fickle nature. Sophisticated projection tools, such as Nate Silver's PECOTA, are designed to help take some of the guesswork out of predicting how teams and players will perform during a given season, and often produce surprisingly accurate forecasts on the whole. But even PECOTA is prone to big misses, especially in individual player projections, which help to preserve the game's air of mystery.

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

Mike Ferrin talks with Brian Cartwright in this special edition of Baseball Prospectus Radio. Click to download the mp3.

Read the full article...

This is a BP Premium article. To read it, sign up for Premium today!

February 12, 2009 11:29 am

Future Shock: Royals Top 11 Prospects

24

Kevin Goldstein

GM Dayton Moore's watch has involved the slow assembly of premium talent, but how soon until it changes the KC's fortunes on the field?

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

This is a BP Premium article. To read it, sign up for Premium today!

March 18, 2008 12:00 am

Prospectus Today: It Doesn't Count

0

Joe Sheehan

If you're watching leaderboards at this time of year, you may need to ask yourself why.

Here's a look at a couple of leaderboards:

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

This is a BP Premium article. To read it, sign up for Premium today!

March 13, 2008 12:00 am

Prospectus Hit and Run: Running Afoul

0

Jay Jaffe

Has the perceived decrease in foul territory brought by the new stadium boom contributed to the surge in home runs over the past two decades?

Last time around, after discussing how the baseball itself may have changed in a manner that helped to boost home run rates over the past two decades, I took a look at the myth of the shrinking ballpark. To recap, the notion that the stadium construction boom that's taken place over the past 20 years has left us with a game full of bandboxes is actually a false one, at least when it comes to fence distances:

The remainder of this post cannot be viewed at this subscription level. Please click here to subscribe.

Joe settles whether some of the first week's events are trends or accidents.

Let’s play the always-entertaining game, "Confirmation Bias or Small Sample Size," where all my preseason predictions are correct, no matter what happened in the first week:

Read the full article...

Jim cleans up some old business, ponders the all-time greats at second base, and tries to avoid throwing things at the TV set.

\nMathematically, leverage is based on the win expectancy work done by Keith Woolner in BP 2005, and is defined as the change in the probability of winning the game from scoring (or allowing) one additional run in the current game situation divided by the change in probability from scoring\n(or allowing) one run at the start of the game.'; xxxpxxxxx1160158525_18 = 'Adjusted Pitcher Wins. Thorn and Palmers method for calculating a starters value in wins. Included for comparison with SNVA. APW values here calculated using runs instead of earned runs.'; xxxpxxxxx1160158525_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160158525_20 = 'The number of double play opportunities (defined as less than two outs with runner(s) on first, first and second, or first second and third).'; xxxpxxxxx1160158525_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160158525_22 = 'Winning percentage. For teams, Win% is determined by dividing wins by games played. For pitchers, Win% is determined by dividing wins by total decisions. '; xxxpxxxxx1160158525_23 = 'Expected winning percentage for the pitcher, based on how often\na pitcher with the same innings pitched and runs allowed in each individual\ngame earned a win or loss historically in the modern era (1972-present).'; xxxpxxxxx1160158525_24 = 'Attrition Rate is the percent chance that a hitters plate appearances or a pitchers opposing batters faced will decrease by at least 50% relative to his Baseline playing time forecast. Although it is generally a good indicator of the risk of injury, Attrition Rate will also capture seasons in which his playing time decreases due to poor performance or managerial decisions. '; xxxpxxxxx1160158525_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160158525_26 = 'Average number of pitches per start.'; xxxpxxxxx1160158525_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160158525_28 = 'Singles or singles allowed.'; xxxpxxxxx1160158525_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160158525_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160158525_31 = 'The Baseline forecast, although it does not appear here, is a crucial intermediate step in creating a players forecast. The Baseline developed based on the players previous three seasons of performance. Both major league and (translated) minor league performances are considered.

Read the full article...

<< Previous Tag Entries Next Tag Entries >>