My Moneyball moment

Earlier this year, I had a job interview for a Finance role, wherein I had to give a pitch about myself. I found the task a little daunting (how does one sell themselves without sounding egotistical?), but I remembered one of the fundamental tenets of good film writing: show, don't tell.

Rather than tell my interviewers what I could do, I thought I'd show them. I said I had some experience with R, and put my money where my mouth was in the form of this graph:

So there you go: my very own "Jonah Hill in Moneyball" moment. And just like Hill's character convinced Brad Pitt with his expert understanding of baseball economics, I convinced my interviewers thanks to my graph of goals scored by Chelsea players!

And they say films don't teach you anything. ;)

Statistical Analysis of the 141 films I watched in 2017, with BBFC analysis.

Just like last year, when I put my hard-earned coding skills into practice by analysing all the marks I’d awarded every film I watched in 2016, I repeated the process again this year.

The arithmetic mean of the 141 films was 6.64, a fractional increase from last year, meaning that my discernment skills to have improved slightly. That being said, the lowest mark out of 10 I gave last year was a 2, whereas I gave 1/10 to two films this year, and zero out of 10 to one, Darren Aronofsky’s bloated stinker, mother!, which is the worst film I’ve ever seen in my entire life, and featured that movie ingredient that I am so averse to: Jennifer Lawrence screaming her head off.

Statistical Analysis of Usage of My Odeon Limitless Card

I went on a 4-hour R course last year, and since then, I’ve just been fixated with adapting the code they gave us to draw pretty graphs with, in order to nerd out over my personal interests (chiefly, films and football).

This post will be much like the one I did six months ago when I analysed my film-watching habit of 2016 across all mediums, only here, I’m just analysing the 69 titles I saw on my Odeon Limitless card with some attempts at ~science behind the graphs I present.

Review of the 133 films I watched in 2016 [with BBFC analysis]

I’m slowly going through my review of 2016 releases, one blog post per week (backlog: un et deux). As I still have quite a lot of the 2016 awards-nominated films to see and thus don't want to complete my 'review of the year' without giving them a chance first, I thought I’d buy some time by looking at all the films I watched in 2016, not just the ones that were released that year.

I watched 133 films in total last year, in a mixture of mediums, from at the cinema (my Cineworld Unlimited and Odeon Unlimited cards have both recouped their charges), at the cinema with ISENSE, whatever that is, on DVD, on the TV, on Netflix and Amazon Prime, and a few other mediums that I shan’t detail.

The arithmetic mean for the 133 films I gave out of ten was 6.54, which unfortunately shows some erroneous decision-making on my part, given I generally only watch a film if I expect it to be 7/10 in quality.

However, the appearance of a couple of lesser-seen films with my favourite actresses in, Saoirse Ronan and Rooney Mara, on Netflix, including a couple of real stinkers (Lost River, Dream Boy, Dare, Trash), would have no doubt bought this average down. Plus, while catching up with the 2015 Oscar-contention films, there were a handful which I didn’t think were that great, but watched for the sake of completeness (eg The Revenant and The Big Short), so they, too, would have skewed the average.

I recently went on an R course, so here be three graphs that indulge my statistical fascination with films (and the BBFC in particular).

What I go to school for.

I went on an R course recently just so I could produce this rather fabulous graph, of the certificates of films I've seen, and at which cinemas, since procuring my Odeon Limitless card in July.

Statistics can be fun sometimes!

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Level 4 of my BBFC game, by the way, is purposely very very tricky. Match the film to the film which has the identical rating and short insight as it.

(Note: the short insight of the pairs don't have to be in identical order, for example, one might say 'strong language, violence, sex' and the other 'strong language, sex, violence'. That would still count as a match. Also, because the BBFC are inconsistent with 'ands', some might have an 'and' linking the reasons and others won't).