![]() ![]() Want to know Joe Morgan’s longest consecutive streak of games where he came to the plate at least twice? The answer: 235 games. You can also do absurdly specific searches. Not only do you get the regular Bill-Terry’s-batting-average data, but you also get a large selection of sabermetric stats, breakdowns by tens of different criteria (left/right, day/night, April/September, and so on), and the ability to manipulate the data in ways that other websites don’t allow. That site has pretty much rendered printed baseball encyclopedias obsolete. As a result, and not surprisingly, much of the groundbreaking research these days has to do with pitch analysis.Įasily the best source for precalculated historical statistics is (B-R). That is, for every pitch thrown by any pitchers in MLB, they’ll tell you the type of pitch, where it crossed the plate, and how much it broke vertically and horizontally. The main attraction of the MLB website is that it provides PITCHf/x data. MLB’s website provides copious statistical data, sortable and printable, updated instantly as games progress. My four favorites - in rough order of increasing detail - are: There is no shortage of almost any kind of data. James found that he had to keep compiling those stats even into the 1980s famously, in his 1981 book, he reprinted a letter from the Chicago Cubs refusing to provide him with such “intelligence-type” stats. At the time, Bill marketed his book as “featuring 18 categories of statistical information that you just can’t get anywhere else.” When Bill James started writing his self-published Baseball Abstracts back in the late 1970s, he had to compile situational statistics himself, from the daily box scores, without a computer. ![]() But if you wanted more esoteric statistics, like Joe Morgan’s career performance with the bases loaded, you were out of luck. Some things weren’t too bad - if you wanted to know Bill Terry’s batting average in 1933, there were two encyclopedias, Macmillan and Neft/Cohen, that would tell you. Intuitively enhance the resolution of 2D and 3D data down to 120 nm using 15 published deconvolution algorithms, powered by efficient multi-CPU/multi-GPU processing.Back in the beginning days of sabermetrics, data was hard to come by. Segment, classify, and denoise images based on deep learning algorithms accessible through a dedicated user interface for training AI models.Īcquire and correlate images from different instruments such as light and electron microscopes, with a sample-centric workspace and a dedicated file management system.Ĭustomize and automate image acquisition, processing, and analysis with a dedicated Python script editor for recording, debugging, and code completion.Īcquire and analyze molecular dynamics using FRAP, FRET, and ratio imaging within a dedicated analysis workspace using the most established algorithms. Visualize and analyze 3D/4D data of unlimited size with the flexible pipelines and machine learning tools of the stand-alone Vision4D software platform. ZEISS Nanoscale and Correlative AnalysisĮmploy extended image processing functions and perform automatic 2D image analysis guided by an intuitive software wizard.Įmploy extended image processing functions, visualize 3D/4D image stacks with advanced rendering tools, and perform 3D image analysis guided by an intuitive software wizard. ![]()
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