Writing the High ROI Screenplay (Part 6)

This week we continue with part six in a twelve part series of JT Velikovsky’s doctoral thesis: “Understanding And Exploring The Relationship Between: Creativity; Theories Of Narratology; Screenwriting; And Narrative Fiction Feature Film-Making Practices.”

By JT Velikovsky

So – what struck me – in reading those 100 Screenwriting Textbooks – was firstly, this:


A lot of what they said was a consensus – but –in many cases, they also all said different stuff to each other.

(i.e. So – wait, which one of these books is actually right? Are they all right? Some of them contradict each other…)

The second thing I noticed, in reading them was: almost none of them used an empirical methodology.

And – the ones that did? Looked at films written/made by – very experienced, very `credited’ very `produced’ writers… (for whom: `the rules of the game’ are a little different, to someone aiming to `break in’…)

Let me give an example:

So – James Cameron’s scripts – since and including The Terminator, all read a certain way in terms of tone, genre, story.

But – James Cameron is also: a writer-director. When he writes a line in his script (noting that, the actual screenwriting is shockingly, awesomely great) he also has an idea about, how he’s going to shoot it, for whatever budget he’s going to get. A spec screenwriter can’t expect to have their script financed as easily as a Cameron picture.

Another example is Shane Black –who, famously, sold a spec (The Long Kiss Goodnight, which is a much better script than film, in my opinion) for $4m.

Note that – he includes `throwaway gags’ in his screenplays, like in Lethal Weapon:



The kind of house that I’ll buy if this movie is a huge

hit. Chrome. Glass. Carved wood. Plus an outdoor

solarium: a glass structure, like a greenhouse only

there’s a big swimming pool inside. This is a really

great place to have sex.


Scene 49/Page 43 – LETHAL WEAPON (screenplay by Shane Black, 1986)

But – prior to becoming a highly paid screenwriter, Shane Black was also in the movie Predator (1987)…

Spot the screenwriter. A bespectacled nerd, reading comics? C’mon – seriously; as if…
© Predator, 1987, 20th Century Fox – written by Jim Thomas & John Thomas.

So – the authors of these Screenwriting Manuals had: screenwriting/story/narratology `theories’ that were not derived from any`specific data set’ – but, overall seemed to be based largely on intuition – and their own experienceof: reading many scripts

i.e. The authors had (often) been professional script readers (as, had I, as it happens) and had therefore seen (and even: read) thousands of screenplays (as had I) and – they had `gleaned some patterns’ from that whole experience.

Which – is all completely logical, and understandable:

i.e. If you look at about 1000 of anything, e.g.: patents for mousetraps; prime numbers; bikinis, man-kini’s) you are bound to spot `patterns’ in there somewhere, right?

All of these is a beautiful-and-unique snowflake. But there are also patterns.

We humanoids are good like that: pattern recognition (aka `intelligence’) is apparently one thing that we have lots of, and apparently, more than any other lifeform that we share the planet with. In fact we’re sometimes too good at it, see (or Google): Pareidolia. (Namely – seeing significant patterns where, there’s actually just chaos, e.g. Say, `The Virgin Mary In My Toasted-Cheese Sandwich’). To my thinking, a lot of screenwriting manuals accidentally fell into this trap. Some of the stuff they thought made a successful screenplay: doesn’t necessarily. i.e. The empirical evidence shows otherwise.

There were of course many screenwriting books that had a lot of fascinating theories, and yet they seemed to use arbitrarily-chosen films, to illustrate their point.

Their example ranged from: Oscar-winning big-budget films – to low-budget indie films. But – aren’t the rules different, for how different types (and even: genres) of films get financed – and then, made? (Actually, yes.)

So I went off looking for screenwriting books that had very strict criteria for their data sets.

There weren’t many: and some, for example, looked at films that made over $250m at the box office.

But – when I researched how many of those $250m+ films were spec screenplays, hardly any of them were…

So – it didn’t make a lot of sense to teach spec screenwriters how to write high-budget screenplays if: they were rarely-if-ever, made from spec scripts to begin with. Most of those, were adaptations of existing successful novels. And – that’s fine to study too, but – only super-experienced screenwriters get hired to adapt best-selling novels, right?

So – I went looking at different `sets’ of films. Highest International Box Office. Biggest Budgets.  Movies With Lowest Budgets to Earn $1 Million at US Box Office, etc.

And–some interesting patterns emerged, once I looked at a very specific data set:

The Top 20 Return-On-Investment Films Of The Past 70 Years.


Interestingly, the average budget of these films is: $1.9m. (Even with, the $10m and $11m ET and Star Wars in there. Some of these incredibly-viral feature films were made for $7k. Amazing.)

And again, the key point is, the data set itself is empirical.

That is – anyone who wants to study the Top 20 ROI Films of the Past 70 Years – is stuck with: this exact same set of 20 films.

(A Side Note – When they see the list, some people want to know if, these figures are `inflation-adjusted’. Answer: No, they’re not, but – neither is the international box-office total in each case – so: it doesn’t actually matter. The point is – if you divide the box office by $10, you get the approximate number of people who bought a cinema ticket to see these movies. Also, to be really accurate – you also need to adjust for ticket-price inflation… But – the ROI at the time the film was released means that `the dollars of the budget’ were of equivalent value, at the time that it was made – and seen.)

Anyway – the bigger point is –a pretty bad (sloppy) way to `analyse’ film stories/screenplays is, this –

Just think of a pattern: Say, “Films with love stories in them.” Then – pick films with a good love story, regardless of whether that film actually reached a wide enough audience to make a profit…

Or – say, an extreme (i.e. exaggerated, for the purpose of illustration here, and because sarcasm is also sometimes fun) let’s examine `serious’ sci-fi films where say: The Alien Guys All Arguably Look Kind of Pretty Damn Silly.

Battlefield Earth would likely qualify, as would Enemy Mine. And then,we might come up with a theory that: this is a good thing to do in your film – and it will succeed (in `finding the film’s intended audience’).

Arguably though, Battlefield Earth totally sucks as a movie, and also: empirically, didn’t do so well, in `finding its audience’. (The film cost $80m – not even including the Marketing – and made only $29m back,at the international box office. Yikes.)

“I am going to make you as happy as a baby Psychlo on a straight diet of kerbango.”
(Battlefield Earth – © 2000 Warner Bros Pictures – Written by Corey Mandell and J.D. Shapiro, based on the novel by L Ron Hubbard.)

So – a scientific and empirical approach to film narratology means – we need to actually first clearly define the data set.

And then – look for patterns – within that data set alone.

E.g. Say maybe, “I am now going off to find: the Top 20 Films at the Box Office – With A Talking Mouse in Them.”

e.g. Presumably, the resulting list of (say) 20 films would include Stuart Little. And, maybe some Mickey Mouse movies, etc.

A Talking Mouse Picture

Then say – okay: so that is the list of the Top 20 Talking Mouse Films, and, we can’t change the list…i.e. – It is, what it is.

So –we say: I’m now going to analyse them – for any common characteristics.

And – maybe on examination,you may find:

1) the mouse always white

2) there is always a love story


3) there is always a cat, as the villain.

(Then again, that stuff all feels pretty obvious – as the `Talking Mouse Genre’ is usually just like that.)

Anyway, as I say – some very interesting patterns emerged, from a very specific data set:

The Top 20 Return-On-Investment Films Of The Past 70 Years.


Next month’s post:

Part 7: `I’ll elaborate.’

– JT Velikovsky


image020JT Velikovsky is a million-selling transmedia writer and consultant (films, games, TV, comix, novels) and produced feature film writer.

His doctoral thesis research on Film/Story/Screenplays of The Top 20 ROI Films can be found here.

Photo Credits: JT Velikovsky

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