The proliferation of advanced analytical tools in the past decade has enhanced the enjoyment level of baseball for many fans. Yet one overlooked aspect of the data explosion is the benefit derived by major league clubs, particularly in the fields of player development, advance scouting and performance forecasting.
Research presentations and panel discussions at last week's SABR Analytics Conference in Phoenix fully illustrated, in particular, the harmonious relationship between data collection and analysis, traditional scouting and player development. All endeavors strive to predict players' future value by weighing many inputs and assessing the probability of various outcomes.
Baseball America reported from the Analytics Conference, focusing on presentations and discussions with obvious currency in the field of scouting and player development, and this blog post collects all the links in case you missed them the first time.
• Research Confirms Hard-Throwers' Advantage. Analysis of a batter's point of contact, as measured by Hit f/x, tells us a lot about his expected power output.
• Observations From Day One Of The SABR Analytics Conference. Pitchers Javier Lopez and Brandon McCarthy discuss the role of detailed analytical information in major league clubhouses.
• Hitters Quickly Show Distinct Groundball, Flyball Profiles. Groundball and flyball tendencies for hitters are more stable—and perhaps more telling—than those same rates for pitchers.
• Proliferation Of 'Big' Data Allows For Complex Analysis. The interactivity between the hundreds of thousands of data points available in today's game necessitates a new, more complex outlook on graphical analysis. Distilling the vast Pitch f/x expanse, for example, could heighten the impact of advance scouting and increase a team's success in player acquisition.
• Notes & Quotes From Days Two And Three Of SABR Analytics Conference. Panel discussions featuring major league general managers and player-development executives reveal the ways in which front offices value scouting information and performance analysis.
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