Clash of the titans

Pierre Boulez conducts Daniel Barenboim and the Berlin Staatskapelle.

With Daniel Barenboim and Pierre Boulez - titans of the classical world - sharing a stage, the question of musical dominance was always going to arise. While a programme of Liszt piano concertos promised the traditional rivalry between soloist and orchestra, it was the altogether quieter rivalry of soloist and conductor that proved more compelling in performance, as Boulez's restraint and precision faced off with Barenboim's expressive showmanship.

Conducting Barenboim's own orchestra, the Berlin Staatskapelle, Boulez was always going to be at a disadvantage. Often directed by Barenboim from the piano, you could hardly blame the players for responding to their director's gestures and barely-concealed cues, yielding two concertos that while solid enough, lacked the energy that comes from absolute clarity and specificity of interpretation.

The contrast between the two musicians was encoded into the programme itself, with the bravura of Liszt's concertos framed in each half by one of Wagner's orchestral works. With Barenboim absent the hall lost much of its rather manic electricity, but while even Boulez's control couldn't lend substance to the youthful indiscretion that is the Faust Overture, his clean textures made something unusual of the Siegfried Idyll.

The Staatskapelle's smooth-edged sound is a miracle of many years' making, and the tenderness of Wagner's birthday gift to his wife offered a sympathetic vehicle for this peculiar sweetness. Originally (and pragmatically) scored for just 15 musicians, Wagner's Idyll here enjoyed slightly expanded orchestration, allowing for the scope and rather awkward acoustic of the Royal Festival Hall auditorium. Its spirit however remained resolutely that of a chamber performance, balancing intimacy (the most vulnerable of string pianissimos) with Boulez' habitual emotional coolness. The result was oddly exhilarating, its passions (and there were plenty) keener for being hard-won.

Hearing Boulez conduct such repertoire is only more fascinating than it is bizarre. While his musical boundaries have broadened considerably in recent years, encompassing Wagner and Mahler, such Romantic extremes as the Liszt concertos represent new territory, encountered for the very first time in the current concert tour. It was only natural then that Barenboim should take the lead here, his personality pounded hard into the keyboard and flung out at the eager audience.

The impact of the Piano Concerto No. 2 may have been enough to reduce Matthew Arnold to the "sweetest, bitterest tears", but I'd imagine few were tempted to that condition last night. While the woodwind offered a suitably moody opening, and instrumental solos (exquisite cello in particular) tugged plaintively at the heartstrings, there was a thrust and force to Barenboim's playing that spoke briskly of action rather than contemplation. At his bravura finest in the dramatic authority of the Marziale, it was his textural contributions - the delicate moments of arpeggiation and motivic dialogue - that reminded me of his musical intelligence and maturity.

There was no ignoring however the intrusive smudge of the sustaining pedal, blurring much of the passagework and clouding the tone of the RFH's Steinway. It was an issue that persisted in the E flat concerto, where it was again balanced by the Mozartian lyricism of the Allegretto, hands unfolding themselves into flurries of filmy ornamentation.

Yet rather like the infamous solo triangle, placed rather intrusively centre-stage at Barenboim's left elbow, something still jarred about this performance. While the finale was an Olympian parade of muscular will, its scope and volume seemed alienated from the earlier movements, a trumpet-call of victory without the validation of a battle. Barenboim is surely unequalled among pianists for visual drama and musical personality, impressing them upon score and audience with equal authority, yet where he lacks is surely in narrative. His colourful episodes each emerge distinct and complete, but the connecting conceptual thread - the guide rope with which Boulez never loses contact - is often lost.

Royal Festival Hall, London, 13 June

Alexandra Coghlan is the New Statesman's classical music critic.

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