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Articles Tagged No-hitters 

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06-26

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BP Daily Podcast: Effectively Wild Episode 479: A Move Each Contender Should Make
by
Ben Lindbergh and Sam Miller

07-30

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5

Baseball Therapy: Leave Me In, Coach!
by
Russell A. Carleton

07-15

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BP Daily Podcast: Effectively Wild Episode 243: No-Hitters, Tim Lincecum, and Pitch Counts/Joe Blanton and ERA Estimators
by
Ben Lindbergh and Sam Miller

07-03

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BP Daily Podcast: Effectively Wild Episode 237: Stats That Won't Last/No-Hitters and No-Walkers/The Worst Shortstop Ever/A Pitcher Who Can Hit/The All-Bunting Team/Trading Top Prospects for Trout/Pint-Sized Power Hitters
by
Ben Lindbergh and Sam Miller

05-13

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7

BP Daily Podcast: Effectively Wild Episode 201: Drafting Age-25-and-Under Starters/Still No No-Hitters
by
Ben Lindbergh and Sam Miller

05-29

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18

Baseball ProGUESTus: No No-No, No Cry
by
Craig Glaser

04-24

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7

Overthinking It: The No-Hitters That Almost Weren't
by
Ben Lindbergh

04-08

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8

Baseball ProGUESTus: The Rookie Effect
by
Brian Mills

06-08

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6

One-Hoppers: Observing Perfection
by
Jay Jaffe

10-16

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Future Shock: Monday Morning Ten-Pack
by
Kevin Goldstein

10-16

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Prospectus Today: LCS, Day Six
by
Joe Sheehan

10-14

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Future Shock: Where Did the Tigers and the Athletics Come From?
by
Kevin Goldstein

10-14

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Prospectus Today: LCS, Day Four
by
Joe Sheehan

10-14

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Playoff Prospectus: The Best and Worst of Mets and Cardinals Postseason Pitching
by
Jim Baker

10-13

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Prospectus Today: LCS, Day Three
by
Joe Sheehan

10-12

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Prospectus Today: The Games Go On
by
Joe Sheehan

10-12

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Player Profile
by
Marc Normandin

10-11

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Remembering Buck O'Neil
by
Alex Belth

10-11

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Prospectus Today: LCS, Day One
by
Joe Sheehan

10-09

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Completely Random Statistical Trivia
by
Keith Woolner

10-09

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Prospectus Today: Division Series, Day Six
by
Joe Sheehan

10-07

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Prospectus Today: Division Series, Day Four
by
Joe Sheehan

10-06

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Prospectus Today: Division Series, Day Three
by
Joe Sheehan

10-06

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Prospectus Matchups: October Musings
by
Jim Baker

10-05

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Prospectus Today: Division Series, Day Two
by
Joe Sheehan

09-14

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You Could Look It Up: No Hitters Ain't That Special, Part Two
by
Steven Goldman

09-08

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You Could Look It Up: No Hits For You
by
Steven Goldman

03-27

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Future Shock: How Do Teams Draft?
by
Kevin Goldstein

02-24

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Fantasy Focus: Building a Fantasy Farm System
by
Jeff Erickson

06-09

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

06-24

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Testing the ''Mistake Hitter'' Hypothesis
by
Cliff Roscow

07-18

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Doctoring The Numbers: The Burroughs Hypothesis
by
Rany Jazayerli

03-05

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Lost in America
by
Keith Scherer

10-12

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Call It In The Air!
by
Dave Pease

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Ben and Sam banter about seeing no-hitters and team philosophies, then discuss potential solutions for each contender's biggest need.

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July 30, 2013 6:28 am

Baseball Therapy: Leave Me In, Coach!

5

Russell A. Carleton

Is there a downside to trying to protect a pitcher by cutting an excellent outing short?

Last week, we talked about Tim Lincecum's 148 pitch no-hitter and found that while there might be some consequence for a pitcher's next start due to such a long outing, it was relatively small and generally gone by the second start. So there's not much penalty in the short term for leaving a pitcher in to throw a lot of pitches; what about the penalty for taking him out?

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Ben and Sam discuss whether we should care about pitch counts in no-hitters, then talk about the gap between Joe Blanton's actual and estimated ERA.

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Ben and Sam answer the most listener emails they've ever answered.

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Ben and Sam draft starting pitchers age 25 and under, then discuss whether there's any significance to the fact that we haven't seen a no-hitter yet this season.



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No Mets pitcher has ever thrown a no-hitter? How unlikely is their no no-no streak, and how many no-hitters would we expect them to have?

Believe it or not, most of our writers didn't enter the world sporting an @baseballprospectus.com address; with a few exceptions, they started out somewhere else. In an effort to up your reading pleasure while tipping our caps to some of the most illuminating work being done elsewhere on the internet, we'll be yielding the stage once a week to the best and brightest baseball writers, researchers and thinkers from outside of the BP umbrella. If you'd like to nominate a guest contributor (including yourself), please drop us a line.

Craig Glaser is an Application Developer at Bloomberg Sports, where he helped design and implement the algorithms that make Bloomberg’s fantasy baseball tool Front Office tick.  He has previously written articles for The Hardball Times, Surviving the Citi, Amazin’ Avenue, and his own site, Sabometrics. A member of SABR, he has recently participated in panels at the SABR Analytics and 50th Anniversary of the Mets conferences.  In a prior life, he studied Experimental Economics and Cognitive Psychology at NYU, focusing on how people perceive probabilities, a field of study that continues to color his view of life and the sport of baseball. You can find his musings about sports, probability, and everything else on Twitter @Sabometrics.
 


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April 24, 2012 8:00 am

Overthinking It: The No-Hitters That Almost Weren't

7

Ben Lindbergh

Philip Humber's perfect game ended with a controversial call, but close plays to preserve no-hitters are the norm, not the exception.

Since the start of the 2009 season, 12 nine-inning no-hitters have been pitched. Over the same span, 24 nine-inning one-hitters have been pitched. The former will be remembered. The latter will not, except by Anibal Sanchez, who threw three of them. (Don’t feel too bad for Anibal Sanchez, since he already had a no-hitter. Anibal Sanchez: pretty good at pitching.)

The difference between a no-hitter and a one-hitter is—wait for it—one hit. But it’s too simple to say that, really. A hit can be a long home run or a hard line drive that lands somewhere on the field. It can also be an infield dribbler, a well-placed pop-up, or a routine fly that would have been caught by literally anyone but Raul Ibanez. This is a hit:

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Do early-season phenoms fade once the rest of the league learns to stop giving them pitches to hit?

Believe it or not, most of our writers didn't enter the world sporting an @baseballprospectus.com address; with a few exceptions, they started out somewhere else. In an effort to up your reading pleasure while tipping our caps to some of the most illuminating work being done elsewhere on the internet, we'll be yielding the stage once a week to the best and brightest baseball writers, researchers and thinkers from outside of the BP umbrella. If you'd like to nominate a guest contributor (including yourself), please drop us a line.

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Another look at the frequency of no-hitters and perfect games.

Today Tommy Bennett takes a stab at some mathematical modeling regarding the possibility of a pitcher throwing a perfect game, a feat to which we baseball fans are almost in danger of becoming jaded, given the fact that we've seen two official ones plus another with a big ol' asterisk attached in roughly one-third of a season. Last week, I crunched some numbers on behalf of San Jose Mercury News writer Dan Brown (no, not that guy), who once upon a time gave my Futility Infielder site its first mainstream media mention, not to mention its long-enduring slogan, "the scrappiest place on earth." At the risk of exposing the limitations of my mathematical skillz — I hail from the Liberal Arts wing of BP, which means I can only wade so far out into the sea of spreadsheets before I'm over my head — the least I could do was return the favor by adding some back-of-the-envelope figgerin' to his assignment to investigate the sudden spate of perfectos.

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October 16, 2006 12:00 am

Future Shock: Monday Morning Ten-Pack

0

Kevin Goldstein

Kevin checks out the newsmakers in the winter leagues.

\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.'; xxxpxxxxx1160988517_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.'; xxxpxxxxx1160988517_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160988517_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).'; xxxpxxxxx1160988517_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160988517_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. '; xxxpxxxxx1160988517_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).'; xxxpxxxxx1160988517_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. '; xxxpxxxxx1160988517_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160988517_26 = 'Average number of pitches per start.'; xxxpxxxxx1160988517_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160988517_28 = 'Singles or singles allowed.'; xxxpxxxxx1160988517_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160988517_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160988517_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.

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October 16, 2006 12:00 am

Prospectus Today: LCS, Day Six

0

Joe Sheehan

Our servers, like the Cardinals bullpen and the A's, crashed. Only two of those get to come back.

\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.'; xxxpxxxxx1161098296_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.'; xxxpxxxxx1161098296_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1161098296_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).'; xxxpxxxxx1161098296_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1161098296_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. '; xxxpxxxxx1161098296_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).'; xxxpxxxxx1161098296_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. '; xxxpxxxxx1161098296_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1161098296_26 = 'Average number of pitches per start.'; xxxpxxxxx1161098296_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1161098296_28 = 'Singles or singles allowed.'; xxxpxxxxx1161098296_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1161098296_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1161098296_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.

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October 14, 2006 12:00 am

Future Shock: Where Did the Tigers and the Athletics Come From?

0

Kevin Goldstein

Even Alexis Gomez came from somewhere (Kansas City). Kevin tells us how the Tigers and A's acquired the rest of their postseason difference-makers.

\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.'; xxxpxxxxx1160846402_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.'; xxxpxxxxx1160846402_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160846402_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).'; xxxpxxxxx1160846402_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160846402_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. '; xxxpxxxxx1160846402_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).'; xxxpxxxxx1160846402_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. '; xxxpxxxxx1160846402_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160846402_26 = 'Average number of pitches per start.'; xxxpxxxxx1160846402_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160846402_28 = 'Singles or singles allowed.'; xxxpxxxxx1160846402_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160846402_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160846402_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.

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