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Bodies on the Line: Quantifying how defenders affect chances.

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From blogs to the BBC, the concept of ‘expected goals’ has entered the mainstream media's lexicon. It has caught on because it’s a useful concept; it’s a useful concept because football is a low-scoring game. Chance (or luck) can be the difference between victory and defeat, a good day or an off-day. Expected goals, however, measures what would have happened on an average day.

It’s a simple quantity to measure. Shots are assigned a number between the 0 or 1: the proportion of similar shots (from the same position, for example) that have resulted in a goal. I’ll refer to this as ‘chance quality’. You then add up the chance quality for every shot taken by a team in a match to calculate the number of goals that you would have ‘expected’ them to score that day[1].

One problem with typical measures of chance quality is that they tend to ignore the other team. How many of their defenders were between the shot-taker and the goal? How effectively were they denying him the time and space …

From excess to success: Neymar, inflation, and the price of an EPL title.

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Like stock markets in the late nineties, the English transfer market is soaring ever higher. In 2010, EPL clubs spent nearly £500m; in 2014 they broke the £1bn mark and this season total spending should exceed £1.5bn. While the number of transfers each season has risen gradually since 1992, the huge increase in spending has been driven by exponential inflation in transfer fees. In 1993/94, £3.75m was enough to buy one of the best midfielders in the league: Roy Keane. These days, it’s difficult to imagine that sum buying you anything but a budget squad player. A top-class midfielder now costs upwards of £50m, and could easily be significantly more.

Such rapid inflation renders meaningless comparisons of club spending over a long time horizon. £7m is peanuts by today’s standards but was the maximum spent in 1992, in this case by a Jack Walker-funded Blackburn (of which about half went on Alan Shearer). If we want to measure and compare player investment over time we must convert past t…

Pundit Consensus Forecasts

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In my last blog, I demonstrated that the weekly EPL predictions of Mark Lawrenson (for BBC Sport) and Paul Merson (for Sky Sports) consistently beat the betting market. Betting a constant amount on their predictions (home win, away win or draw) over the last 3 years would have resulted in an 8% profit, on average, for both pundits. I also showed that a lot of this performance is down to their ability to predict draws, something that the bookmakers – and most statistical models – are quite poor at doing.

So far I’ve treated Lawrenson and Merson’s predictions separately, but what if we combine them? Can we improve their predictive power? They may feature on rival networks, but in this post I’m going to look at what happens when Merson and Lawrenson work as a team.

Consensus Forecasts
From the 2014/15 season through the 2016/17 season there were 1101 EPL matches for which Merson and Lawrenson both made a prediction. But how frequently did they make the same prediction? The grid in Figure…

How are Lawrenson and Merson beating the market?

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For the last six seasons, ex-Liverpool player and regular BBC pundit Mark (‘Lawro’) Lawrenson has been attempting to predict the outcome of every EPL match. Over on Sky Sports, ex-Arsenal player Paul Merson has been doing the same thing. Their predictions are published on the BBC Sport and Sky Sports websites the week before each match. But how good are they?

Last season I performed a little experiment to assess the performance of the pundit’s predictions against a clear baseline: the betting market. I placed a £1 bet on each predicted outcome – home win, away win or draw – made by Merson and Lawro, selecting the best odds offered for that outcome by one of four bookmakers[1]. Over the course of the season that amounted to 777 bets: 379 on Lawro’s predictions and 378 on Merson’s.

I did surprisingly well out of my little experiment. By the end of the season, Lawro was £63 in profit and Merson £52. This amounts to a return on investment of 17% and 14% respectively – significantly above …

Tinker, Tailor, Mould a Side: Squad Rotation in the EPL

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One of the key features of Chelsea’s title winning season was the consistency of their starting lineups. After the 3-0 thrashing by Arsenal in September, Conte switched to a 3-4-3 formation and Chelsea embarked on a 13-match winning streak in the league that ultimately propelled them to the title. The foundation of this formation – Luiz, Cahill and Azpilicueta – started each of the next 32 games, and the wing-backs, Moses and Alonso, missed only three between them.

Such consistency is partly due to luck with injuries and suspensions, but Conte also resisted the temptation to tinker with his team. Other managers opted to ring the changes, for tactical purposes or to rest players. In the closing weeks of the season Mourinho was compelled to defend his rotation policy, citing fixture congestion and the need to maximize his chances of Europa League success. However, frequent changes to United’s starting lineup were a feature of their entire season not just the final few months.

In this a…

Why are EPL clubs preferring to recruit foreign managers?

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A few weeks ago I read a very interesting article by Sean Ingle in the Guardian comparing the performance of foreign managers in the EPL with their British & Irish counterparts. Using data compiled at the University of Bangor in Wales, the headline statistic was that foreign managers have averaged 1.66 points per game since 1992/93, compared to just 1.29 for those from the UK & Ireland. As Ingle points out: this amounts to a whopping 14 extra points over the course of the season.

My first thought was that these results might be misleading because of a potential selection bias. If overseas managers have tended to work for the top EPL clubs then of course they would have a higher average points per game, simply because a larger proportion of them managed big clubs than their domestic counterparts. In that case it’s not fair comparison. In the first part of the blog I will look at this in more detail: will the result reported in the Guardian stand up to further scrutiny?

Neverthe…

Keep calm and let them carry on: are mid-season sackings worth it?

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It’s February and your club is in trouble. Following a run of poor results, they are hovering just above the bottom three. Fans and pundits alike are writing them off. The remainder of the season is destined to be a grim struggle for the points: a few snatched draws, the odd scrappy win, but mostly meek surrender to mid-table and above teams.

The board panics and fires the manger, it seemed the only remaining option. Granted, he did well last season – bought in some good players and promoted others, got them playing attractive football. But now the team needs defibrillation: a new manager with fresh ideas, inspiring players keen to prove themselves to him. A five game honeymoon period and, come spring, everything will be rosy again. After all, it worked so well for Sunderland last season.

This story seems to play out several times each season, but does it actually make any sense to fire a manager mid-season? A few years ago, Dutch economist Dr Bas ter Weel compared points-per-game won…

The Wisdom of Crowds: A Census of EPL Forecasts

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Introduction
We're nearly two-thirds of the way through the 2016/17 EPL season, which seems a good time to try to predict what might happen. Chelsea’s nine-point cushion and relentless form make them clear favorites for the title; not since Newcastle in 1996 have a team blown such a lead. Just five points separate second from sixth as the remaining superpowers battle for Champions League places: who will miss out? Perhaps the mantra ‘most competitive EPL season ever’ is best reserved for the relegation fight, though. Six teams, two points and an ever-changing landscape. Amongst them: last season’s heroes, Leicester. Too good to go down?

Most TV pundits are definitive in their predictions, indeed they are typically paid to be so. Others prefer to let the numbers do the talking. Football analysts around the world build mathematical models to measure team strength and calculate the probability of match outcomes. Rather than saying “team A are likely to beat team B”, they'll say …