Poisson-Belgium 0-0

“Statistical match predictions are more accurate than many people realize (…) For the upcoming Qatar World Cup, Penn’s model suggests that Belgium (…) has the highest chances of raising the famous trophy, followed by Brazil”

Even Nature had to get entries on the current football World cup, with a paper on data-analytics reaching football coaches and teams. This is not exactly prime news, as I remember visiting the Department of Statistics of the University of Glasgow in the mid 1990’s and chatting with a very friendly doctoral student who was consulting for the Glasgow Rangers (or Celtics?!) on the side at the time. And went back to Ireland to continue with a local team (Galway?!).

The paper reports on different modellings, including one double-Poisson model by (PhD) Matthew Penn from Oxford and (maths undergraduate) Joanna Marks from Warwick, which presumably resemble the double-Poisson version set by Leonardo Egidi et al. and posted on Andrews’ blog a few days ago. Following an earlier model by my friends Karlis & Ntzoufras in 2003. While predictive models can obviously fail, this attempt is missing Belgium, Germany, Switzerland, Mexico, Uruguay, and Denmark early elimination from the cup. One possible reason imho is that national teams do not play that often when players are employed by different clubs in many counties, hence are hard to assess, but I cannot claim any expertise or interest in the game.

Domhnach na Fola

The Quaker [book review]

I ordered The Quaker, a book by Liam McIlvanney mostly because Liam is the son of WIlliam McIlvanney, whose Glasgow’s Laidlaw trilogy I found stunning. I was intrigued by the attempt at following in his father’s Tartan Noir steps. To make the link stronger this book won the 2018 (William) McIlvanney Prize for crime book! While there are many similarities between the stories, if only because they both take place in Glasgow in the 1960’s, where slums were gradually demolished to become high rises (themselves demolished much later in one of Ian Rankin’s stories, if in Edinburgh), where the police was partly corrupted by local gangsters, and where (im- and e-) migration was spinning the demographics of the city, the styles are different and The Quaker does not read as a clever pastiche. It is definitely a unique and brilliant book, from the vivid depiction of the Glasgow of these times (possibly helped by the fact that many locations were familiar to me from my several visits at the University of Glasgow), to the pretty convincing plot, to the psychological depths of many (male) characters. The women in the story are indeed mostly victims of the serial killer or witnesses, possibly towards reflecting the state of gender inequality in the 1960’s (as far as I remember there were more women at the fore in WIlliam’s books), with the inclusion of a victim of the Magdalene asylums. The outlying nature of the main detective is another feature common to father and son: while McCormack does not carry philosophy books to work, he remains apart from the other detectives, including a secret that threatens both the case and his career.

Bayes @ NYT

A tribune in the NYT of yesterday on the importance of being Bayesian. When an epidemiologist. Tribune that was forwarded to me by a few friends (and which I missed on my addictive monitoring of the journal!). It is written by Siobhan Roberts, a Canadian journalist writing about mathematics (and obviously statistics). And it brings to the general public the main motivation for adopting a Bayesian approach, namely its coherent handling of uncertainty and its ability to update in the face of new information. (Although it might be noted that other flavours of statistical analysis are also able to update their conclusions when given more data.) The COVID situation is a perfect case study in Bayesianism, in that there are so many levels of uncertainty and imprecision, from the models themselves, to the data, to the outcome of the tests, &tc. The article is journalisty, of course, but it quotes from a range of statisticians and epidemiologists, including Susan Holmes, whom I learned was quarantined 105 days in rural Portugal!, developing a hierarchical Bayes modelling of the prevalent  SEIR model, and David Spiegelhalter, discussing Cromwell’s Law (or better, humility law, for avoiding the reference to a fanatic and tyrannic Puritan who put Ireland to fire and the sword!, and had in fact very little humility for himself). Reading the comments is both hilarious (it does not take long to reach the point when Trump is mentioned, and Taleb’s stance on models and tails makes an appearance) and revealing, as many readers do not understand the meaning of Bayes’ inversion between causes and effects, or even the meaning of Jeffreys’ bar, |, as conditioning.

Xi’an street food [jatp]