How to create compelling videogame characters, by Far Cry 3's lead writer

"How the world reacts to your character tells you who you are," says Jeffrey Yolahem.

The latest contender in the crowded autumn/winter release schedule is Far Cry 3, an open-world FPS from Ubisoft, which comes out next week. I played Far Cry 2 back in 2008, and it was notable as a sequel which discarded much of its heritage and tried to do something new. Far Cry 3 isn't that beholden to its predecessors, either, and one of the key messages from the developers was that they wanted this to be a game which was self-aware. 

The Guardian's preview described it this way:

Quite why Jason [the protagonist] is suddenly so good at killing people is often questioned, and the unspoken answer to that question is that he's the lead character in an action game. Before the player arrived and took control, he wasn't, and as he meets his friends after he's come under new management (as it were) they note the change, and they're a little disturbed. Jason isn't behaving normally at all. Jason is a violent protagonist because you've made him into one, and the game isn't shy about telling you that.

...

Jason is given a flamethrower by a man who claims to be from the CIA but might just be a conspiracy nut with a lot of professional-looking equipment in his basement. He's told to go and burn down drug plantations to attract the attention of bigger, more important warlords to the island, so he does. As well as burning crops, the flamethrower burns people – groups of soldiers that might have posed a problem beforehand are now easy pickings, as Jason leaps out from cover and immolates whole squads of them.

Combat, always a careful combination of recon and timing, becomes far too easy and there's a jolt of pleasure in that because it's been so difficult beforehand. And then Jason says "Man, I fucking love this gun!" to no one in particular, and you realise that Jason's enjoying this as much as you are and you're playing a game while Jason is burning men to death in a drug-field.

That raises inevitable comparisons with Spec Ops: The Line, which disrupted the gleeful fun of most military FPSs with its inclusion of post-traumatic stress disorder (read Tom Bissell's excellent piece on it here), and points to an interesting avenue for shooters: irony and postmodernity.

Anyway, I wanted to talk a little bit more about the writing of Far Cry 3, and spoke to its lead writer Jeffrey Yohalem, who previously worked on the Assassin's Creed series. Here's an edited version of our chat.

How do you approach writing your characters?

I try to take a different line of thought with each character. I think of Lewis Carroll, and tried to take a bunch of things in society I wanted to talk about. So with Dr Earnhardt, the line is drugs, and escape through drugs. What would drive someone to do that?

How much of games writing is dictated by technical challenges?

That's what this game is all about - it's a game about videogames. Each Far Cry game is about darkness - our references are Heart of Darkness, Apocalypse Now, the Deer Hunter. But we wanted to take extreme versions of the ideas and characters in those, rather than the opposite. Take the CIA agent you meet - and yes, there's a CIA agent, the cliche lines run so deep. But we wanted to subvert it, make it something the player doesn't expect. So you're asked to think about why a CIA agent would take the time to talk to you when the world is ending. In this, players are talking about videogames, but without breaking the fourth wall. 

You can work within the limitations as long as you acknowledge them.

With such dark reference points, were you worried, therefore, about making it fun? Doesn't that undermine the message?

The answer is not punishing people: I'm thinking of those movies that make themselves a painful experience to watch. We didn't want to do that. 

Do you think the protagonist in an FPS should be a character in themselves, or a blank slate on to which the player can project him or herself?

In this game, Jason gets tattoos - that's a big part of it. And you can definitely use the gameplay and the game system to create emotions about your lead - look at those old adventure games like Cyberia or The Longest Journey.

And there are ways to create character without dialogue. Take Half-Life 2: you see the lead character takes the tram, he works in a laboratory; you see how people treat him - they are respectful to him. How the world reacts to your character tells you who you are.

FPS games don't tend to have the best record in having interesting female characters. Does that bother you?

I hope our female characters are complex - and when those female characters are treated sexually, it's subverted.

Why did you choose to be a games writer?

When I was little, I would play games. And the ones that were really good felt like someone else was in the room. I was friends with those videogames. But 99 per cent of games create no warmth - yet the one per cent that do (like Beyond Good and Evil, or Prince of Persia), are like having someone there. 

And I love how you experience games: not passively, like a book; but not in one session, like a movie. I love that I sleep between sessions of playing, and I find that I'm dreaming about it. 

A still from Far Cry 3.

Helen Lewis is deputy editor of the New Statesman. She has presented BBC Radio 4’s Week in Westminster and is a regular panellist on BBC1’s Sunday Politics.

OLIVER BURSTON
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How science and statistics are taking over sport

An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others.

In the mid-1990s, statistics undergraduates at Lancaster University were asked to analyse goal-scoring in a hypothetical football match. When Mark Dixon, a researcher in the department, heard about the task, he grew curious. The analysis employed was a bit simplistic, but with a few tweaks it could become a powerful tool. Along with his fellow statistician Stuart Coles, he expanded the methods, and in doing so transformed how researchers – and gamblers – think about football.

The UK has always lagged behind the US when it comes to the mathematical analysis of sport. This is partly because of a lack of publicly available match data, and partly because of the structure of popular sports. A game such as baseball, with its one-on-one contests between pitcher and batter, can be separated into distinct events. Football is far messier, with a jumble of clashes affecting the outcome. It is also relatively low-scoring, in contrast to baseball or basketball – further reducing the number of notable events. Before Dixon and Coles came along, analysts such as Charles Reep had even concluded that “chance dominates the game”, making predictions all but impossible.

Successful prediction is about locating the right degree of abstraction. Strip away too much detail and the analysis becomes unrealistic. Include too many processes and it becomes hard to pin them down without vast amounts of data. The trick is to distil reality into key components: “As simple as possible, but no simpler,” as Einstein put it.

Dixon and Coles did this by focusing on three factors – attacking and defensive ability for each team, plus the fabled “home advantage”. With ever more datasets now available, betting syndicates and sports analytics firms are developing these ideas further, even including individual players in the analysis. This requires access to a great deal of computing power. Betting teams are hiring increasing numbers of science graduates, with statisticians putting together predictive models and computer scientists developing high-speed software.

But it’s not just betters who are turning to statistics. Many of the techniques are also making their way into sports management. Baseball led the way, with quantitative Moneyball tactics taking the Oakland Athletics to the play-offs in 2002 and 2003, but other sports are adopting scientific methods, too. Premier League football teams have gradually built up analytics departments in recent years, and all now employ statisticians. After winning the 2016 Masters, the golfer Danny Willett thanked the new analytics firm 15th Club, an offshoot of the football consultancy 21st Club.

Bringing statistics into sport has many advantages. First, we can test out common folklore. How big, say, is the “home advantage”? According to Ray Stefani, a sports researcher, it depends: rugby union teams, on average, are 25 per cent more likely to win than to lose at home. In NHL ice hockey, this advantage is only 10 per cent. Then there is the notion of “momentum”, often cited by pundits. Can a few good performances give a weaker team the boost it needs to keep winning? From baseball to football, numerous studies suggest it’s unlikely.

Statistical models can also help measure player quality. Teams typically examine past results before buying players, though it is future performances that count. What if a prospective signing had just enjoyed a few lucky games, or been propped up by talented team-mates? An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others. In many sports, scoring goals is subject to a greater degree of randomness than creating shots. When the ice hockey analyst Brian King used this information to identify the players in his local NHL squad who had profited most from sheer luck, he found that these were also the players being awarded new contracts.

Sometimes it’s not clear how a specific skill should be measured. Successful defenders – whether in British or American football – don’t always make a lot of tackles. Instead, they divert attacks by being in the right position. It is difficult to quantify this. When evaluating individual performances, it can be useful to estimate how well a team would have done without a particular player, which can produce surprising results.

The season before Gareth Bale moved from Tottenham Hotspur to Real Madrid for a record £85m in 2013, the sports consultancy Onside Analysis looked at which players were more important to the team: whose absence would cause most disruption? Although Bale was the clear star, it was actually the midfielder Moussa Dembélé who had the greatest impact on results.

As more data is made available, our ability to measure players and their overall performance will improve. Statistical models cannot capture everything. Not only would complete understanding of sport be dull – it would be impossible. Analytics groups know this and often employ experts to keep their models grounded in reality.

There will never be a magic formula that covers all aspects of human behaviour and psychology. However, for the analysts helping teams punch above their weight and the scientific betting syndicates taking on the bookmakers, this is not the aim. Rather, analytics is one more way to get an edge. In sport, as in betting, the best teams don’t get it right every time. But they know how to win more often than their opponents. 

Adam Kucharski is author of The Perfect Bet: How Science and Maths are Taking the Luck Out of Gambling (Profile Books)

This article first appeared in the 28 April 2016 issue of the New Statesman, The new fascism