What Downton Abbey can teach us about dying without a will

Where there's a will, there's a way.

Downton Abbey devotees and law students alike must have heaved a collective sigh of relief with the return to our screens of that compulsive lesson in legal history, cunningly disguised as a period costume drama.

Those who have not been drawn into the mystery and intrigue of the occupants of Downton Abbey, who seem to have suffered more communal misfortune than one would reasonably expect of an extended family (but no doubt a requirement for the television ratings), can stop reading now.

All others, take note for our first tutorial, of the references to the outdated (even then) but shortly to be amended laws on intestacy (Matthew failed to make a will) resulting in Lady Mary’s diminished share in the estate and looming spectre of heavy death duties.

While death at an early age is always tragic and as was observed of Matthew, he anticipated being around for many years thence, what happens on intestacy generally seems to come as something of a shock.

The rules, which determine the distribution on a person’s death of any of his or her property not governed by a valid will, are largely contained in the Administration of Estates Act 1925 (spookily coinciding roughly with the current Downton period - will Lord Grantham vote on it in the House of Lords?) and the Intestates’ Estates Act 1952.

By and large these have not kept pace with the requirements or expectations of modern family life. Back in 2009 the Law Commission published a consultation paper on various aspects of the rules, some of which have been included in the Inheritance and Trustees’ Powers Bill 2013 which is working its way through the House of Lords as I write.

Under the current provisions, however, in the absence of a valid will by Matthew, because his estate is likely to have been valued at more than £250,000 and he was survived by a wife and child, Lady Mary's entitlement today would still be limited. She could claim for herself a statutory legacy of £250,000 and all of Matthew's personal chattels.

The balance of Matthew's estate would then be divided in two with Lady Mary receiving a life interest (ie income only) in one half of the estate. The gorgeous George would be entitled to the other half of the estate on statutory trusts and the half of the estate in which his mother has a life interest, on her death.

This was probably not the result she and Matthew (or indeed Lord Grantham) were hoping to achieve by virtue of their collective and cumulative efforts in the previous three series. Do note, however, that in certain circumstances, the provisions of intestacy can be varied in the same way as one can vary a will.

However, in my experience what is sometimes more surprising for clients is not necessarily the effects of intestacy but the fact that despite having gone to the trouble of officially anticipating one’s demise and providing for it (as far as one's property is concerned) in a considered manner, one can find oneself inadvertently rendered intestate.

For example, if a testator divorces (or ends a civil partnership) his will takes effect as if his former spouse or civil partner had died before him, subject to express contrary intention. Similarly, marriage revokes a will unless it was drafted expressly in contemplation of the said nuptials. Of course, as a solicitor, Matthew should have known this, but perhaps he took too great a heed of the adage 'A solicitor who acts for himself has a fool for a client.'

Other topics for discussion in future tutorials might be the content of Nanny West’s employment contract (did she breach a condition that both charges should be treated equally?), the grounds for divorce in other jurisdictions or the extent to which the estate could qualify for agricultural, business or even heritage property for inheritance taxes. Who ever thought Downton was an education?

Sophie Mazzier is counsel at City private wealth law firm Maurice Turnor Gardner LLP

This piece first appeared on Spear's Magazine

Photograph: Getty Images

This is a story from the team at Spears magazine.

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