By ESPN.com Leading statistician and best-selling author Nate Silver will join ESPN later this year in a multi-faceted role that will include coverage of sports, economics, culture, science and technology on ESPN’s website. …read more
Source: FULL ARTICLE at ESPN Headlines
By Matt Cantor
Nate Silver, celebrity political statistician and former baseball analyst, has just thrown the New York Times a curveball: He’s departing his longtime home at the paper for a gig at ESPN. Nate Silver’s contract at the Times , where he soared to fame for his election predictions, is due to expire… …read more
Source: FULL ARTICLE at Newser – Home
By Kevin Spak
Harry Reid might want to think carefully before revising the filibuster rules —because there’s a decent chance he’ll soon be on the other end of them. Nate Silver at the New York Times has crunched the race-by-race numbers, and based on them and his own best guesses and assumptions, concluded… …read more
Source: FULL ARTICLE at Newser – Home
By John Johnson As the manhunt for Dzhokhar Tsarnaev continues, one of the questions getting tossed around is whether the powers-that-be overreacted by shutting down the city of Boston. ( Business Insider rounds up some of the remarkable photos being tweeted of the “ghost town.”) Some samples: Nate Silver of the New…
From: http://www.newser.com/story/166536/bostons-a-ghost-town-is-that-a-smart-move.html
By Rob Quinn 
Source: FULL ARTICLE at Newser – Home
If your goal is to win: Rely on advanced models like KenPom [1], Sagarin [2], and Nate Silver‘s rankings [3] to compare teams. Everyone has their pet heuristic (always pick experience, defense wins championships, mid-majors are underrated, Duke will always win/choke — the list goes on), but the best data-driven methods consistently outperform everything else. Sometimes actual basketball knowledge like matchups or tendencies is useful, but I only use this information for games that the models tell me are toss ups. Understand the ramifications of your scoring system. If you use a standard 1-2-4-8-16-32 scoring system, correctly picking the national champion gets you 63 out of a possible 192 points, and an entirely correct national championship is worth 94. Get these picks right and you’re assured a finish near the top. Get them right with non-top seeds and you have a really good chance of winning most small to moderately sized pools. For example, I’m considering picking Florida (a 3 seed) over Louisville as my national championship. I’ll probably be the only person to pick Florida in my pool of around 15 people (except my dad, since he uses the same strategies I do), so if Florida wins, everything else I do is irrelevant. Know where you can separate yourself. Congratulations on getting your point for picking that 1-16 game correctly, but everyone else got it too so you haven’t actually made any progress. You’ll gain or lose ground based on your picks that go against conventional wisdom and toss up picks, so choose carefully. It’s tempting to pick the sexy mid-major double-digit seed to make a Sweet 16 run, but ask yourself if you can really defend that pick or if you’re just trying to show how smart you are (guilty right here). On the flip side, if you find a game where the selection committee has blatantly mis-seeded the teams (UCLA-Minnesota and Memphis-St. Mary’s this year), relish in the glory of the points you just gained with a probability greater than 0.5. Tailor your picks to the size of your pool. If you’re in a large competition, you need more picks that might separate you from everyone else and can justify picking upsets more aggressively. On the other hand, if you’re in a small pool, you can probably stick with your “maximum likelihood” bracket and still have plenty of places to build a lead. Determine your goal (winner, top 3, in the money, etc.) and the size of your pool and adjust your picks accordingly. If your goal is to have fun: UPSET CITY BAY-BEEE! Every year I pick a few wild upsets and obnoxiously talk them up to anyone who will listen. When they actually work out, I look like a genius and get to brag about it for years, and when they don’t, I just stay quiet. Last year, I picked St. Louis to knock of Michigan St (lost by 4) and Belmont to take down Georgetown (not close). This year, Davidson is upsetting Marquette and …read more
Source: FULL ARTICLE at Forbes Latest
By John Johnson 
Source: FULL ARTICLE at Newser – Home
By Zach Slaton, Contributor Day Two of the 2013 Sloan Sports Analytics Conference is already underway, but here are a few brief thoughts from Day One. The Soccer Analytics panel is at 1 PM this afternoon, but the next best thing was on Thursday night at the third annual Soccer Analysts meet up at McGreevy’s. All credit goes to Sarah Rudd and Ravi Ramineni for arranging an event that had 30+ soccer nerds discussing their latest theories, favorite teams, and sharing a few beers along the way. You’ll find very few gatherings with so many of the foremost soccer analytics writers and practitioners present and engaged in casual, off-the-record conversation. A small sampling of attendees included two out of the four Soccer Analytics panelists – Chris Anderson and Blake Wooster – along with Manchester City’s Gavin Fleig, the “reclusive” Orbinho (his own Twitter profile description, not mine), and the entrepreneurial Howard Hamilton, amongst others. There were even a few people unable to attend the conference who still attended the meet up knowing the fun and value in the Soccer Analysts event. All had a good time, new connections were made, and everyone made it back to their hotels in time to not make the first day of the conference too tiring. The theme of the day one panels was certainly data presentation and making data consumable by non-analysts. There is a sense from the conference’s size, its range of participants, and the general zeitgeist of sports analytics outside of the conference that the battle for acceptance has been won by the data nerds. Trouble With the Curve moments now seem to be the exception rather than the rule, but there is still a lot to be done by data analysts to ensure their models are used in the most effective manner possible by those who are not as numbers-inclined. The conference has emphasized cleaner and leaner data presentation as being key to such success, with an outstanding emphasis on Tufte principles in the Data Visualization panel. Data analysts who want to be effective and move up within organizations should heed the conference’s advice and focus as much on their presentation, visualization, and general “people” or EQ/EI skills as their data management and programming skills. Betting analytics has its own panel on Saturday, but that didn’t stop gambling from coming up during Friday’s panels. Blackjack legend Jeff Ma and Nate Silver, known for his poker exploits amongst others, provided interesting commentary on the True Performance and the Science of Randomness panel. They actively encouraged attendees to use gambling and games-of-chance of the legal variety as one of the best training grounds for the use of probabilistic thinking and applied statistics. Elsewhere on day one the Business of Sport panel provided some useful comparisons between the prevalence of betting organizations as sponsors of teams in Europe (even to the point of having their logos on jerseys) and such organizations’ complete absence in official relationships with North American professional sports teams and leagues. Gambling is always a …read more
Source: FULL ARTICLE at Forbes Latest
By John Johnson 
Source: FULL ARTICLE at Newser – Home
By John Johnson 
Source: FULL ARTICLE at Newser – Home
By Kevin Spak 
Source: FULL ARTICLE at Newser – Home
By Kelly Phillips Erb, Contributor
Tax season can be intimidating for seasoned pros, not to mention the fear it strikes into the hearts of newbies. To help you out (and inspired by the smart and savvy @samsharf), I’ve put together a series on getting started with your taxes. WAIT! DON’T STOP READING! Even if you’re not a newbie – maybe you’ve done your own taxes for years or maybe you have a tax pro who does your taxes for you – there might be a tip or two for you here, too. Since 2001, Congress has made nearly 5,000 changes to the Tax Code bringing it to nearly 4,000,000 words. That’s a lot to take in. It’s constantly changing. And nobody – not even Nate Silver – can know everything. …read more
Source: FULL ARTICLE at Forbes Latest
By Dorothy Pomerantz, Forbes Staff Thanks to Nate Silver‘s amazing ability to predict elections, statistic are all the rage right now. But can numbers predict who will win Oscars? A company called Farsite thinks so. These number crunchers out of Columbus, Ohio, have turned their analytic skills to Hollywood’s biggest award show.
Source: FULL ARTICLE at Forbes Latest
By Gil Press, Contributor Norman Nie was not surprised by the accurate predictions of the presidential elections’ results from Nate Silver and others. “A lot of it,” he told me recently, “is good statistics and good science and good statistical programming packages.” The increasing amount of money spent by the media on polling, Nie believes, improved the accuracy of predictions by increasing the number of observations. In addition, with so much knowledge available now about every individual, the hypotheses and models used by the forecasters were developed on solid foundations. Says Nie: “40 years after The Changing American Voter, we really understand the voter’s decision.”
Source: FULL ARTICLE at Forbes Latest
By John Johnson 
Source: FULL ARTICLE at Newser – Home
By Chris Conover, Contributor New York Times numbers guy Nate Silver devotes his entire column today to analyzing growth in the size of government (federal, state and local) relative to the economy 40 years ago. Although his print headline reads “Health Care Drives Increase in Government Spending,” he concludes that only about half of […]
Source: FULL ARTICLE at Forbes Latest
By Bruno Aziza, None By now, I’m sure that you have read all the predictions New Year’s aficionados have come up with. 2012 was a special year for Big Data and predictions; Nate Silver won big with Obama’s re-reelection, while on the other extreme, the Mayans visions didn’t pan out (thankfully!). Big Data has caught so much attention in the past year that many have predicted 2013 would be “The Year of Big Data”.
Source: FULL ARTICLE at Forbes Latest
Source: FULL ARTICLE at AOL
By Neal Colgrass 
Source: FULL ARTICLE at Newser – Great Finds
