Comics review: Marc Ellerby's Ellerbisms

A comic strip that began life with few pretensions.

Ellerbisms began life with few pretensions. It was to be a diary comic like so many others: a page of a Moleskine a day, illustrated with something which happened to Marc Ellerby in the last twenty-four hours. These are the bread-and-butter of the indie cartoonist's world, and, along with gag strips, make up the majority of webcomics (once you exclude the furries, at least). But, as Ellerby says:

Then I met a Swedish girl called Anna and it stopped being so sporadic (and boring).

What you end up reading is a chronicle of a relationship, messy bits included, written as it happened. To this end, Ellerby has also added a new prologue and epilogue, as well as adding a few pages in near the beginning to elaborate on the context of some of the strips. This is a good idea; those early strips, already the weakest part of the book, occasionally make reference to events which Ellerby simply didn't get round to illustrating in real time, and the extra content helps the story hold together as one coherent piece.

New artwork next to old does serve to emphasise how much better a cartoonist Ellerby is now than he was when he started. But thanks to his decision to excise the first few months of Ellerbisms strips, and turn the book from "the complete collection" to "the complete Marc and Anna", there's little of the genuinely amateurish stuff left in. His very first strip remains as a nostalgic title page, and it's a nice scene in its own right; but if the first twenty pages were like it, readers might never hit the good stuff.

Which would be a shame. Like Joff Winterhart's Costa-nominated Days of the Bagnold Summer, Ellerbisms' short episodes, frequently just a page each, build up a detailed, touching portrait of the young couple (whereas Bagnold Summer's episodic nature was an affectation, this is the real deal). We see them fighting over nothing, singing and preparing, and their holidays, working days, and days out in the park. The end, when it comes, isn't surprising, because we have come to know the pair so well that the writing was on the wall. But it is saddening nonetheless.

Not that Ellerbisms is a mopey book. It wears its page-a-day heritage on its sleeve, and the pages of silliness and gags are frequently laugh-out-loud funny. But without that emotional core, it would feel like so many other good but ephemeral webcomics.

Ellerby has also worked hard to make Ellerbisms worth reading as a book, rather than just mooching off the still-available free archives. As well as the aforementioned extra content – and removed content, because what's not collected is as important as what is – it's also packaged together with production values (including delicious rounded corners, a hat-tip to the Moleskine heritage) that well exceed what was necessary to get it out the door. It's all part of Ellerby's – and diary-comics co-conspirator Adam Cadwell's – audacious self-publishing venture, Great Beast.

The two are publishing high quality editions of their complete diary comics – Cadwell's The Everyday is available in hardback, nigh-on unheard of for a self-published webcomic – as well as their other works, like Cadwell's six-part Blood Blokes, about hipster vampires, and Ellerby's Chloe Noonan: Monster Hunter, a sort of Buffy-without-powers. If it works, it will let them cut out the middleman, and may just make publishing these sort of comics, if not quite profitable, then at least break-even. If it doesn't, it will have been an expensive experiment.

No matter what the quality of the physical objects produced, Great Beast will live or die on the skill of its artists. While Chloe Noonan has failed to find the commercial success it deserves, leading to a reboot being planned, it shows that Ellerby has the chops to make something fun and accessible. Hopefully it will find the audience it deserves, and give Ellerby a ticket to riches. But Ellerbisms is proof that he can do much more than just that.

What you end up reading is a chronicle of a relationship. Photograph: Getty Images.

Alex Hern is a technology reporter for the Guardian. He was formerly staff writer at the New Statesman. You should follow Alex on Twitter.

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