This year’s Oscar Ceremony, as always, has attracted the interest of a great audience, including the Hollywood, mass media and movie lovers. When I was back in China like five, six years ago, I would watch the real-time streaming Oscar Ceremony in the afternoon, and can name about what prize goes to whom or which. This year I was just waiting to read the media’s post. Except for the “funny mistake”(not funny at all) of announcing La La Land as best picture but actually the prize belongs to Moonlight, making some fast media quickly post the final wrong full Oscar result, this Oscar’s winning result fits with most of the prediction on fivethirtyeight, as you can see from here and here.
Firstly, let’s go to the prediction article. The author has collected the points of each nominee for different categories from multiple movie guilds. As we can see, all the predictions except the best picture one turns out to be right. This is a simple data visualization, just ranking the Oscar nominees by their total points from each source in a table. Although we did not know how the author get the data from those sources and what he or she did to get the result numbers. Anyway, these predictions are making Oscar less to be expected. Please also refer here to see the model used in these predictions, this is simply math.
The other article calculated the probability predicted by the betting organization. It has also borrowed the result from the first article. The visualization in this article is a set of line charts, that carefully record the implied probability based on Paddy Power betting odds. For the main categories, we will again find that La La Land supporters will lose the bet at best picture to Moonlight.
At last, I should say those visualizations are very concise and easy to understand, no fancy tables or animations. Also in my opinion, Oscar is about art, but art is very difficult to evaluate nowadays, in this sense, I think I trust data more, which is relatively more impartial. As long as we have data, we can visualize it, and make it as a living. 😀 Thanks, data, thanks, Oscar.