1. KCR- Wil MyersClick here to scan analyses by Jason Hunt.
2. SF – Brandon Belt
3. OAK – Michael Choice
4. CHC – Brett Jackson
5. COL – Nolan Arenado
6. CLE – Jason Kipnis
7. NYM – Wilmer Flores
8. LAA – Jean Segura
9. SEA – Nick Franklin
10. ATL – Matt Lipka
11. MIN – Kyle Gibson
12. TEX – Robert Erlin
13. STL – Zack Cox
14. PIT – Jameson Taillon
15. PHI – Jonathan Singleton
16. BOS – Drake Britton
17. DET – Nick Castellanos
18. HOU – Jay Austin
19. WAS – Eury Perez
20. LAD – Zach Lee
21. ARI – Matt Davidson
22. BAL – Manny Machado
23. CHW – Jared Mitchell
24. TAM – Matt Moore
25. NYY – Gary Sanchez
26. FLA – Matt Dominguez
27. CIN – Billy Hamilton
28. MIL – Ryan Gennett
29. SD – Simon Castro
30. TOR – Anthony Gose
Browsing is not idleness; or rather, it is active idleness – an exploring capacity...Browsing is the opposite of “search.” Search is precise, browsing is imprecise. When you search, you find what you were looking for; when you browse, you find what you were not looking for. Search corrects your knowledge; browsing corrects your ignorance. Search narrows, browsing enlarges. It does so by means of accidents, of unexpected adjacencies and improbable associations. Leon Wieseltier
The Law of Truly Large Numbers
The Law of Truly Large NumbersWith a large enough sample, any outrageous thing is likely to happen. The point is that truly rare events, say events that occur only once in a million [as the mathematician Littlewood (1953) required for an event to be surprising] are bound to be plentiful in a population of 250 million people. If a coincidence occurs to one person in a million each day, then we expect 250 occurrences a day and close to 100,000 such occurrences a year.Going from a year to a lifetime and from the population of the United States to that of the world (5 billion at this writing), we can be absolutely sure that we will see incredibly remarkable events. When such events occur, they are often noted and recorded. If they happen to us or someone we know, it is hard to escape that spooky feeling.
http://www.wired.com/wiredscience/2012/05/methods-for-studying-coincidences/
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