Miliband should sack Ed Balls

Labour cannot hope to rebuild its economic credibility while Balls remains shadow chancellor.

In his upcoming reshuffle, Ed Miliband should replace Ed Balls as shadow chancellor.

The Labour party is currently becalmed, and with it Miliband's leadership. In the 12 months since he replaced Gordon Brown, Labour's poll rating has risen one per cent according to the most recent Populous poll, two points according to MORI. Despite riots, war and economic stagnation Labour's leader cannot break beyond the margin of error.

Those wondering whether phone hacking would be a game changer have their answer. It has changed nothing. Despite his deft response to the crisis almost half of Labour supporters cannot picture Ed Miliband as prime minister, and his general approval ratings are plumbing new depths.

But it's not only Ed Miliband the polling furies have chosen to mock. Unemployment is rising. Business confidence declining. Growth estimates are being frantically revised down. Yet unbelievably, the Conservative party has now opened up a ten point lead over Labour on the issue of who has the best economic policies for the country. Even more staggering, their lead has actually increased since March. The worst things get for the economy, the better things seem to get for George Osborne and his party.

There is a simple reason for this paradox. Labour's own economic policy has no clothes. The deficit is the defining issue in British politics. And Tory attempts to brand Labour as deficit deniers have succeeded beyond their wildest dreams. In fact, they have not so much branded shadow ministers as embalmed them, placed them in a glass case and erected a sign "Deficit Denier, official exhibit, 2010 - present".

No one within the Labour party is prepared to even glance at, never mind acknowledge, this elephant in the shadow cabinet room. Nor are they prepared to acknowledge the even larger elephant balancing upon its shoulders. The person who must take responsibility for this parlous state of affairs is Ed Balls.

Labour's shadow chancellor is one of the few political heavyweights on the front bench. But in this specific brief he is an albatross around his party's neck. All the opinion polls indicate the public blames the economic policies of the previous Labour government for the cuts to thier services, along with the hardship they are experiencing, more than the coalition. And Ed Balls is the individual in the shadow cabinet more closely associated with those policies than any other.

Ed Miliband is acutely aware of the toxic legacy of the Brown premiership. Hence his reluctance to even raise the issue of the economy in the wake of the publication of the Darling memoirs. But if he is wary of discussing economics when David Cameron has a copy of Back from the Brinksitting on his lap, how can he hope to make a case whilst he has Ed Balls sitting on his own?

Nor is this just an issue of legacy. Ed Balls was instrumental in rebuilding Labour's economic credibility from the rubble of the 1992 election defeat. He did it by adhering to a simple golden rule. If Labour couldn't ditch their tax and spend image they were unelectable. Prudence became the watch word. Shadow ministers were banned form making any commitments on spending. Gordon Brown, at Ball's urging, pledged to stick to Tory spending limits, and did so even after Labour's landslide 1997 election victory.

Yet as shadow chancellor Ed Balls seems intent on unlearning every rule he once imposed with iron, and occasionally brutal, discipline on others. Labour's policy has not just regressed to tax and spend. It's now cut tax and spend. New expenditure commitments are tossed around like confetti. Tax cuts bounced out with no internal consultation. Prudence has been ditched, replaced by that leather clad vixen, Ms Pump Primer.

What is Ed Balls thinking? It's not just that he's trying to get the voters to embrace an economic agenda they rejected decisively at the 2010 election. They're being asked to endorse economic policies they rejected at the 1979 election. The perception of fiscal profligacy isn't a dead end for the Labour party. It's political hemlock. We know this because Ed Balls told us it was. And he was right.

Labour's economic policy is no longer grounded in political reality, but in a combination of misguided loyalty, stubbornness and Keynesian economic orthodoxy. Ed Balls seems to believe distancing himself from the policies of Gordon Brown would represent a form of betrayal. It would not. It's just the price of doing business for a new party of opposition. He also seems to equate dogma with strength. Yet by sticking unflinchingly to the failed strategy of a failed manifesto he is reinforcing every negative stereotype his enemies have ever sought to construct around him. "The reckless thing to do is plough on regardless", he told Tribune this week. Too right.

Ed Balls is shadow chancellor. His is not chancellor. His prescriptions for the nation's ills may be economically sound. But they are politically unsustainable. Saying 'I was right, you were wrong' to your political opponents, is one thing. Saying it to the voters is a different matter entirely.

He seems unable, or unwilling, to acknowledge this. A destructive combination of loyalty, stubbornness and pride have locked him into a strategy from which he cannot escape. Which is why, at the next shadow cabinet reshuffle, Ed Miliband needs to set Ed Balls and his party free.

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