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  2. Sabermetrics - Wikipedia

    en.wikipedia.org/wiki/Sabermetrics

    Cook's 1964 book Percentage Baseball was one of the first of its kind. [4] At first, most organized baseball teams and professionals dismissed Cook's work as meaningless. The idea of a science of baseball statistics began to achieve legitimacy in 1977 when Bill James began releasing Baseball Abstracts, his annual compendium of baseball data.

  3. Baseball statistics - Wikipedia

    en.wikipedia.org/wiki/Baseball_statistics

    Baseball statistics include a variety of metrics used to evaluate player and team performance in the sport of baseball. Because the flow of a baseball game has natural breaks to it, and player activity is characteristically distinguishable individually, the sport lends itself to easy record-keeping and compiling statistics .

  4. Category:Statistical data sets - Wikipedia

    en.wikipedia.org/wiki/Category:Statistical_data_sets

    Download as PDF; Printable version; ... Social statistics data (3 C, 30 P) Sports records and statistics ... Category: Statistical data sets.

  5. Win Shares - Wikipedia

    en.wikipedia.org/wiki/Win_Shares

    Win Shares is a 2002 book about baseball written by Bill James and Jim Henzler. The book explains how to apply the concept of sabermetrics to assess the impact of player performance in a combination of several areas, including offensive, defensive, and pitching on their team's overall performance.

  6. Baseball Prospectus - Wikipedia

    en.wikipedia.org/wiki/Baseball_Prospectus

    Baseball Prospectus writers often successfully argue that traditional baseball statistics such as RBIs, wins, and batting average are poor reflections of a player's true contributions. For example, they have argued that RBIs are too dependent on factors outside of the player's control, namely the production of other hitters in the lineup.

  7. PECOTA - Wikipedia

    en.wikipedia.org/wiki/PECOTA

    PECOTA, an acronym for Player Empirical Comparison and Optimization Test Algorithm, [1] is a sabermetric system for forecasting Major League Baseball player performance. The word is a backronym based on the name of journeyman major league player Bill Pecota, who, with a lifetime batting average of .249, is perhaps representative of the typical PECOTA entry.

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  9. NERD (sabermetrics) - Wikipedia

    en.wikipedia.org/wiki/NERD_(sabermetrics)

    The premise for NERD was developed in Cistulli's piece "Why We Watch" in which he establishes the five reasons that baseball continues to captivate the American imagination from game to game: "Pitching Matchups," "Statistically Notable (or Otherwise Compelling) Players," "Rookies (and Debuts)," "Seasonal Context," and "Quality of Broadcast". [5]