“My father told me I should go into word processing”

Actor Gillian Anderson on slapstick, motherhood and the perils of Googling yourself.

You're starring in the slapstick comedy Johnny English Reborn, which seems an unusual choice for you. Was that part of the appeal?
I generally like to make choices based on who I'd like to work with - and I liked the idea of playing the MI7 [spy agency] role with Rowan Atkinson. I think the thing that surprised me the most was how technical it was . . . I was aware of how I needed to work my technical muscle in a way that I hadn't before.

Is the atmosphere on the set of a comedy film different from that on, say, a period drama?
There's a heightened sense of comedy around and there's a bit more laughter. On the other hand, it seems to be more serious, because it's quite serious business, comedy.

Is there snobbery about doing a broad comedy?
Very early on, when I signed on to this project, I had read on IMDb [that] somebody was commenting on why I would choose to be in this film. And I thought, hang on a second - if I was doing a Jim Carrey film, nobody would be having that reaction.

It worries me that you are reading IMDb comments. Do you google yourself a lot?
No! I was looking up something else.

Some people do.
Ha, the first thing I do when I get up every single morning, after I feed the kids, is I go and google "Gillian Anderson".

Are your children affected by your fame?
No, the very, very first situation that we had was when we went to see Cars, and at the movie theatre we were handed a popcorn box with my picture from Johnny English Reborn facing me. My almost-five-year-old said: "Mummy, that's you!" really loudly and proceeded to turn the box around to find out where Daddy was.

It was very funny, but that was the first time that any kind of explanation was needed. And
I can't even remember what we said to him at the time - we sort of tried to push it under the table. It's too early for him.

If any of your children wanted to act, what would you say?
Well, I have a 17-year-old, and that would be the one to come to me soonest. Fortunately she is not interested. I have to say I'm a bit relieved she doesn't want to be an actor.

Because of the lifestyle or the insecurity?
Yes, because the statistics show, I think, that only 5 per cent of actors are working at any one time. My father gave me a lecture at one point when I was younger and told me that I shouldn't be an actress because I should probably get a real job, and that I should go into - what was it back then; computers were really young? - it was word processing.

You've done several period dramas. Are the roles available better?
It's a joy to do that kind of stuff. Every time somebody comes to me and says do Dickens, do Ibsen or Chekov or whatever, it's an honour. If there were two roles sitting in front of me and one of them was Ibsen and one of them a modern piece, I'd probably choose Ibsen. The other side of that is, yes, there is a shortage of good material for women that is as provocative and complex as some of the writing in the classics. But I don't feel like I'm choosing those [the classics] because there's nothing else out there. I am choosing those because I want to do them.

You were in A Doll's House at the Donmar Warehouse in London. What is it like to act in such an intimate theatre?
Each theatre has its own, very strong person­ality. There's something quite arresting about being in a space that small. The closeness of the audience lifts you in a very different way.

Why do you like Ibsen?
Ever since I don't know for how long, people have come to me and said, "You have to do Hedda Gabler; that's a role that's made for you." I'm not sure how much of an insult that is.

In March, you chose Barack Obama as the person you "most admire". Is that still true?
Well, I don't know about most admire. I still think he is a person I admire, but it has been a horrible ride for him since he came into office. And I just cannot imagine waking up every single day and having that burden on your shoulders and not just wanting to crawl under the covers and say, "I'm done." I still hold him in high esteem; he is doing his utmost for everybody. I am amazed what he still handles and the grace he continues to operate under.

Do you vote?
Yes, but in the States. Very enthusiastically for Obama coming into office, and this time round it will be Obama again, no matter who comes up on the Republican side.

Was there a plan for your career?
No, I've gotten lucky.

Are we all doomed?
No, not at all. Only some of you.

Defining Moments

1968 Born in Chicago. Grows up in London and Grand Rapids, Michigan
1993 Lands star role in the X Files TV series
1994 Marries her first husband, Clyde Klotz, and gives birth to her daughter, Piper
1997 Wins an Emmy, Golden Globe and Screen Actors Guild Award for The X Files
2005 Stars in the BBC's Bleak House
2006 Gives birth to her son Oscar
2008 Her second son, Felix, is born
2010 Is nominated for an Olivier Award for her role in A Doll's House at the Donmar

Johnny English Reborn is in cinemas now.

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.

This article first appeared in the 17 October 2011 issue of the New Statesman, This is plan B

OLIVER BURSTON
Show Hide image

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