The New Ballgame: Understanding Baseball Statistics for the Casual Fan Read Online Free PDF Page A

who reaches base on a fielding
error spoils a perfect game.
Cycle
    A player has hit for the cycle when he gets a single, double, triple and home
run in the same game.
    Official major league rules can be found online at.
http://mlb.mlb.com/NASApp/mlb/mlb/official info%official rules/forewordjsp

     
WHY BASEBALL
ARGUMENTS NEVER END
A Brief Statistical History of Baseball

    aseball is the ultimate
second-guessing
game. There's enough time
between pitches to think
about the possibilities.
There's enough time between batters to think about the alternatives. There are
enough strategic moves in a typical game to think about what could have been.
Fans who have "owned" their own salaried players in fantasy baseball leagues
and who have "managed" 1,000 or more games with simulations like Strat-O Matic are sure they know better. They've been there, done that, enjoyed the
same successes and wallowed in the same mistakes as the real managers and
GMs. Second-guessed daily, exasperated big-league managers lament that their
decisions are brilliant when they work and dumb when they don't.

    A competitive sport played by competitive people and enjoyed by competitive fans, baseball is fertile for passionate argument and scholarly analysis. But it's tough to win those debates about what we've learned from the past
and what we can expect in the future, or which teams and which players are
the best (now, and all-time). For all of the new data (statistics) we acquire and
the ever-improving means to analyze it, the art of baseball-performance on
the field-stays ahead of the science. Just when we think that 100-plus years
of study means we've seen enough baseball, or at least enough of the game's
box scores, to be immune to surprise, along comes a team like the 2005 Chicago White Sox-who not only out-performed expectations, but even outperformed (in wins) all the statistics they produced. Baseball keeps surprising
us. It's a team game, after all, and team-dependent statistics are serpentine,
making cause and effect difficult to isolate. For every general statement one
alert fan wants to make about the game and its players, another alert fan is
going to be able to cite the noteworthy exceptions that disprove the absolute
truth of the first claim.
    This chapter is designed to help you become a more alert fan.
    So remember:
It's a team game
    • Teams underachieve when star players under-perform. They overachieve when enough lesser players have career years. Before the 2005 season, almost nobody picked the Chicago White Sox to win it
all. Even rarer was the forecaster (general manager, media analyst, or
fantasy-league expert)-if there was one-who predicted that White
Sox pitcher Jon Garland would finally fulfill his potential, winning
18 games, losing 10, and producing a fine 3.39 ERA. In five previous years with the Sox, Garland had a combined won-lost record of
46-5 1, a career ERA of 4.68 (never better than 4.38), and had never
won more than 12 games in a season. A team without a dominant
superstar, the Sox enjoyed career seasons from Garland, Jose Contreras, Neal Cotts, Cliff Politte, and catcher A.J. Pierzynski, who hit
18 home runs after never hitting more than 11 in any other season.
The Sox got dramatic rebound seasons from outfielders Jermaine
Dye and Scott Podsednik, third baseman Joe Crede, designated hitter
Carl Everett, and pitchers Freddy Garcia and Mark Buehrle, whose
performances all had been in decline for one or more years. The Sox
depended heavily on the unexpectedly strong rookie contributions of
second baseman Tadahito Iguchi and pitcher Bobby Jenks.

    No doubt, the improvement by some of these players fueled the improvement by others. Starting pitchers, for instance, win more and
pitch more innings if their teammates hit better. They have lower
ERAs if the relief pitchers who succeed them are more brilliant than
ever.
    Give much credit for the Sox success to Chicago General Manager
Ken