Posts Tagged ‘ Sports ’

Euro 2016 update

June 26, 2016
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Euro 2016 update

Big news out of Europe, everyone’s talking about soccer. Leo Egidi updated his model and now has predictions for the Round of 16: Here’s Leo’s report, and here’s his zipfile with data and Stan code. The report contains some ugly histograms showing the predictive distributions of goals to be scored in each game. The R […] The post Euro 2016 update appeared first on Statistical Modeling, Causal Inference, and Social…

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Stan makes Euro predictions! (now with data and code so you can fit your own, better model)

June 11, 2016
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Stan makes Euro predictions! (now with data and code so you can fit your own, better model)

Leonardo Egidi writes: Inspired by your world cup model I fitted in Stan a model for the Euro Cup which start today, with two Poisson distributions for the goals scored at every match by the two teams (perfect prediction for the first match!). Data and code are here. Here’s the model, and here are the […] The post Stan makes Euro predictions! (now with data and code so you can…

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A research project for you! Using precursor data to evaluate the Leicester odds.

June 3, 2016
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OK, here’s a research project for someone who’s interested in sports statistics. It’s from this comment by Paul in a recent thread: What I would like to see (has anyone done it?) is an analysis of the performance of EPL teams that had similar pre-season odds to Leicester over the last 15-20 years or so. […] The post A research project for you! Using precursor data to evaluate the Leicester…

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NBA is hiring; no height requirement

June 2, 2016
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Jason Rosenfeld writes: I’m looking to hire a basketball analyst to join my basketball analytics team here at the NBA League Office in NYC. Looking for someone who is graduating now or graduated recently (probably better suited for an undergrad, though grad students are welcome to reach out as well). Looking for a background in […] The post NBA is hiring; no height requirement appeared first on Statistical Modeling, Causal…

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Freak Punts on Leicester Bet

June 2, 2016
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Freak Punts on Leicester Bet

I went over to the Freakonomics website and found this story about Leicester City’s unexpected championship. Here’s Stephen Dubner: At the start of this season, British betting houses put Leicester’s chances of winning the league at 5,000-to-1, which seemed, if anything, perhaps too generous. My [Dubner’s] son Solomon again: SOLOMON DUBNER: What would you say […] The post Freak Punts on Leicester Bet appeared first on Statistical Modeling, Causal Inference,…

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Splitsville for Thiel and Kasparov?

May 23, 2016
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The tech zillionaire and the chess champion were always a bit of an odd couple, and I’ve felt for awhile that it was just as well that they never finished that book they were talking about. But given that each of them has taken a second career in political activism, I can’t imagine that they’re […] The post Splitsville for Thiel and Kasparov? appeared first on Statistical Modeling, Causal Inference,…

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Nick and Nate and Mark on Leicester and Trump

May 20, 2016
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Just following up on our post the other day on retrospective evaluations of probabilistic predictions: For more on Leicester City, see Nick Goff on Why did bookmakers lose on Leicester? and What price SHOULD Leicester have been? (forwarded to me by commenter Iggy). For more on Trump, see Nate Silver on How I Acted Like […] The post Nick and Nate and Mark on Leicester and Trump appeared first on…

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Beautiful Graphs for Baseball Strike-Count Performance

May 16, 2016
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Beautiful Graphs for Baseball Strike-Count Performance

This post is by Bob. I have no idea what Andrew will make of these graphs; I’ve been hoping to gather enough comments from him to code up a ggplot theme. Shravan, you can move along, there’s nothing here but baseball. Jim Albert created some great graphs for strike-count performance in a series of two […] The post Beautiful Graphs for Baseball Strike-Count Performance appeared first on Statistical Modeling, Causal…

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Leicester City and Donald Trump: How to think about predictions and longshot victories?

May 13, 2016
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Leicester City and Donald Trump:  How to think about predictions and longshot victories?

Leicester City was a 5000-to-1 shot to win the championship—and they did it. Donald Trump wasn’t supposed to win the Republican nomination—last summer Nate gave him a 2% chance—and it looks like he will win. For that matter, Nate only gave Bernie Sanders a 7% chance, and he came pretty close. Soccer There’s been a […] The post Leicester City and Donald Trump: How to think about predictions and longshot…

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Super-informative ping-pong graphic

May 11, 2016
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Super-informative ping-pong graphic

Via Twitter, Mike W. asked me to comment on this WSJ article about ping pong tables. According to the article, ping pong table sales track venture-capital deal flow: This chart is super-informative. I learned a lot from this chart, including:...

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