Akala: "Hip-hop is a modern day minstrel show"

Akala’s "Hip-Hop History Live": an exploration of black history like no other I've seen before.

Its 6.45 on a Friday evening at the Southbank Centre. The race for a chair is on. As the Clore Ballroom fills up, I set off, searching every room, every corner to retrieve a seat. Every nook and cranny of the Southbank has been stripped of furniture. I managed to unearth a stool. The fact that I was accompanied by hundreds of others only goes to show rapper Akala’s growing popularity.

The setting was a strange one. Following the farcical dash for seats, a remarkably mixed audience sat down in the ballroom for this free event. A corporate, sharp, yet colourful space, the Southbank had the feel of a university open day, as every fan politely sat down in front of a makeshift stage. Hardly the typical hip-hop venue.

Yet what followed was far from typical. Opening with a passionate volley of the sort of conscious rap he has become renowned for, Akala embarked on an ambitious history of hip-hop. Presented with both spoken word and rap, each as absorbing as the other, the MOBO award-winning rapper began with ancient African history, and finished with modern day hip-hop. By far the coolest lecture I’ve ever been to.

In his “intellectual beat-down” of accepted opinion, Akala launched a tirade against commonly held misconceptions. First, Chapter 1, “Africa in History” bemoaned the omission of ancient Egyptian history from ‘black history’, quoting the likes of Herodotus to explain that the ancient Egyptians were of course, black. He goes on to explain the technology that Africa possessed, how it had “Swahili houses built in Elizabethan times”, how three quarters of a million books survive from Timbuktu. It was clear from the start that Akala has done his research as he urges us to respect ancient black history.

The lecture-cum-performance then became darker, more poignant. Chapter 2 tackled the “Maagamizi”, the title of a track in Akala’s new album, meaning “human-caused disaster”. Colonialism was such a Maagamizi, “the African holocaust because we paid one hell of a cost” as the track explains. Disturbing too were parts of Chapter 3, “African survival in the New World”. Akala warned parents of the young children in the room (of which there were a surprising amount) that his material would be disturbing, as the Jim Crow laws and lynching were explained.

A more obvious musical history then began to emerge. Akala plays us black jazz from 1936, Ella Fitzgerald’s scat, clips of Mohammed Ali teasing journalists with short, snappy rhymes and the main thesis of the entire performance quickly became clear. Modern-day hip-hop wasn’t created in a vacuum. Instead, it is the product of thousands of years of evolution, borne of the struggles and cross-cultural character of black history. Of the more recent examples, Ella Fitzgerald’s scat was the most revealing. Akala observed that if you put an English accent and a 140bpm beat on it, it would essentially be grime.

Akala’s passion intensifies even further as he moves on to the “Golden age of Hip-Hop” in Chapter 4. Wu-Tang Clan, Public Enemy, and the entire hip-hop scene from the mid-80s to the early 90s represented the “black CNN and much more” he explained. Rap in this era was a world away from its modern MTV equivalent, as MCs addressed issues of real importance to the black community.

That all changed in the mid-90s, as the final chapter “The Art and Politics of Power” laments. Quoting a Mos Def track, Akala reminds us that “old white men is running this rap shit”. “Hip-Hop is a modern day minstrel show” he said. A handful of powerful corporations now control the business, playing down to the lowest, most misogynistic, racist stereotypes. In one moving moment, after a touching mention of Trayvon Martin which brought applause from the audience, Akala lists the names of a series of unarmed African Americans killed by the police. “Raise your hand if you’ve heard of these people” he asks. Barely anyone recognised the victims. In the 80s, he explained, it was the hip-hop MCs who kept the black community informed about such atrocities. Of course, the rich, white, old men who run the industry would never allow such potent resistence in their “product”.

Refreshingly, Akala also rejects the acceptance of the ‘N word’ amongst the black community. It’s a racist word, with a racist history. Full stop.

After finishing with a short jam session, complementing his intelligence with undoubtable musical skill, Akala received a standing ovation. I have never seen anything like his performance, and doubt I will any time soon. Brimming with intelligence, packed with talent, it was never boring, nor patronising. It was relevant, insightful and immensely entertaining.

“Hip-Hop isn’t dead”, explained Akala, “it’s just gravely ill”. I can think of no-one better than Akala himself to nurse it back to health.

Akala: Bold, blunt and brutally honest. Photograph: Getty Images.
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