Recent comments in /f/dataisbeautiful

tree-of-thought OP t1_j81k88j wrote

Reply to comment by CheeseTheGood in Recent Superbowl Win Probabilities, Ordered by "Excitement" [OC] by tree-of-thought

I know, it's a real problem!

I think simply factoring in the sum of scores (or maybe the sum of scores averaged over every play of the game) would go a long way towards pushing that one down the rankings.

It's also been pointed out to me that SB 38 is remembered as especially exciting, but it's right in the middle of my rankings.

¯\_(ツ)_/¯ I'm sad the first attempt has such glaringly "wrong" results, but this is why we get feedback and iterate!

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ISBN39393242 t1_j81eroi wrote

Reply to comment by NotDom26 in [OC] Sugarcane was first introduced to Brazil in 1532. Half a millennium later, the country produces over 700M tonnes yearly (roughly the same amount as all of Asia, and 7x the amount produced by Africa) by latinometrics

i agree, which is also why this label is confusing. why just “north of mexico?” are the plantations in caribbean countries not included, even though they are not at all “north of mexico”? i would imagine they contribute significantly to sugar cane output, possibly even more than mexico or the US.

i only mentioned canada and the US because they are the parts of N.A. north of mexico, but it adds to further confusion about the other regions of N.A

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Oldfolksboogie t1_j8187o9 wrote

Reply to comment by Fun-Management-7027 in [OC] Sugarcane was first introduced to Brazil in 1532. Half a millennium later, the country produces over 700M tonnes yearly (roughly the same amount as all of Asia, and 7x the amount produced by Africa) by latinometrics

Gotchya, and ty for the more granular breakdown.

Either way, I just know that, like Trump, he's all development, all the time, people and the environment be damned.

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tree-of-thought OP t1_j8171sh wrote

Reply to Recent Superbowl Win Probabilities, Ordered by "Excitement" [OC] by tree-of-thought

Source: nflfastr. They have rich play-by-play data for every NFL game of the last ~25 years. I was able to get a time series of win probabiltiy for every Super Bowl since the 2000 season.

Tools: R. nflfastr to get the data, data.table to clean it and develop excitement scoring metrics, and ggplot2 to visualize.My collaborator built interactive visualizations for this project in Flourish. Those visualizations are linked lower in this comment.

Explanation: I've seen win probabilty graphs used as a shorthand for the excitement of a game. I wanted to develop a metric which takes in a win probability time series and outputs an "excitement score."Ultimately, I decided on three different factors that should contribute to the excitement score...

  1. How close is the average win probability to zero? This is intended to capture how surprising was the eventual outcome.
  2. What is the average absolute distance between the win probability and 50%? This is intended to capture how closely contested the game was.
  3. What is the root mean square of all the changes in win probability from one play to the next? This is intended to capture how "back and forth" the game was.

I took each of these scores, scaled (but did not center) them, and then used their euclidean norm as the composite score.

Visit this webpage for more information on this topic!

The plots above are ordered by the composite score descending from left to right, top to bottom.It seems to work pretty well! Especially at the lower end of the scale--those are all pretty clearly games that were lopsided and foregone conclusions early on.

I've gotten the feedback that Super Bowl LIII between the Patriots and Rams is evidence of a "bug" in the metric. That game was very tight--which accounts for its high score (in the metric sense), but it was tight because it was low scoring (in the FOOTBALL sense!) with neither team performing very well.

Stuff I might tinker with to make it better:

  1. Assign different weights to the three constituent metrics
  2. Weight the constituent metrics differently at different points in the game.
  3. Factor in how much scoring is happening
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Fun-Management-7027 t1_j815w76 wrote

Reply to comment by Oldfolksboogie in [OC] Sugarcane was first introduced to Brazil in 1532. Half a millennium later, the country produces over 700M tonnes yearly (roughly the same amount as all of Asia, and 7x the amount produced by Africa) by latinometrics

Not trying to protect Bolsonaro from huge problems of his government in Brazil, but sugar cane is not cultivated in areas of the Amazon Forest (northwest), but instead its farms are located on the middle and south of the country. The major products that are produced in deforested areas are soy beans and beef

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Roadkill_Bingo t1_j8145pm wrote

Reply to [OC] Sugarcane was first introduced to Brazil in 1532. Half a millennium later, the country produces over 700M tonnes yearly (roughly the same amount as all of Asia, and 7x the amount produced by Africa) by latinometrics

Off topic but if the implementation of ethanol in the US was really about climate change, we’d import sugar cane from Brazil instead of subsidizing corn. Way more efficient in terms of caloric yields.

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ISBN39393242 t1_j813zlu wrote

Reply to comment by inconvenientnews in [OC] Sugarcane was first introduced to Brazil in 1532. Half a millennium later, the country produces over 700M tonnes yearly (roughly the same amount as all of Asia, and 7x the amount produced by Africa) by latinometrics

that’s a vague and arbitrary term. why couldn’t it just be interpreted as meaning canada, since north america means canada, us, and mexico, and canada is northernmost of all 3?

imo it’s not an intuitively understood or previously defined term, so it’s a poor label. it would be better to say “US and canada,” or smth. does canada even grow any? if not, why not just say US?

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ElectionOver4Hours t1_j80yd2m wrote

Reply to From Swiping to Sexting: The Enduring Gender Divide in American Dating and Relationships - The Survey Center on American Life by TrixoftheTrade

Interesting read.

The main thing appears to be that women have hugely unrealistic expectations and refuse to 'date down'. Now, I'm not saying settle for being unhappy.

But no man will be 25, earning hundreds of thousands, compassionate, tall and highly educated. Men in this category won't date these women for the same reasons anime girls won't date otaku men.

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