When Sports Rules Go Awry: How TheConversation led to a collaborative paper

Whilst looking through Conversation articles I came across an article entitled “When scoring an own-goal is the only way to win” by Liam Lenten.

By coincidence, I had just read another article about an analysis of sporting rules from the perspecive of Operations Research, written by a good friend of mine – Mike Wright from Lancaster.

The two articles had some similaraties and, after reading Mike Wright’s article I was already planning to write a follow up. Reading Liam’s Conversation article I posted some comments and he was kind enough to respond.

One thing led to another and we agreed to write a paper together.

I am pleased to report that this article (“When Sports Rules Go Awry“) has just been accepted in the European Journal of Operational Research.

The abstract of the paper reads:

Mike Wright (Wright, M. OR analysis of sporting rules – A survey. European Journal of Operational Research, 232(1):1–8, 2014) recently presented a survey of sporting rules from an Operational Research (OR) perspective. He surveyed 21 sports, which consider the rules of sports and tournaments and whether changes have led to unintended consequences. The paper concludes: “Overall, it would seem that this is just a taster and there may be plenty more such studies to come”. In this paper we present one such study.

This is an interdisciplinary paper, which cuts across economics, sport and operational research (OR). We recognize that the paper could have been published in any of these disciplines but for the sake of continuity with the paper that motivated this study, we wanted to publish this paper in an OR journal. We look at specific examples where the rules of sports have led to unforeseen and/or unwanted consequences. We hope that the paper will be especially useful to sports administrators, helping them to review what has not previously worked and also encouraging them to engage with the scientific community when considering making changes.

We believe that this is the first time that such a comprehensive review of sporting rules, which have led to unexpected consequences, has been published in the scientific literature.

When Sports Rules Go Awry is really a review of where sporting rules have been introduced by sports administrators, but which have led to unintended consequences. For example, when it is sensible to score an own goal. The paper has several tanking (the act of deliberately dropping points or losing a game in order to gain some other advantage) examples.

We hope that the paper will be of interest to anybody who likes sports, as well as sports administrators.

It is pleasing to note that TheConversation was instrumental in making this paper happen. If it were not for them, I would have been unaware of Liam’s work. The paper may have still be written (either by Liam or me) but it would not have been as good as the paper that has now been accepted.


If you are interested, you can see my Conversation articles here and Liams articles are here.


This post also appeared on the University of Nottngham blog pages.

Geocoding: Trials and Tribulations

For the past few months I have had a small project on the back burner to try and make geocoding easier.

The motivation can be traced back to the data collection I had to do for the data I needed for my research on minimising the amount of travelling that football supporters have to do over the Christmas holiday period (if you are interested in this see this link).

When I collected the original data I used greenflag.com. I could have used theaa.com or rac.co.uk. The problem with the latter two is that you had to type in the to/from postcode into a web form. At least with greenflag.com the postcodes were part of the URL so it was a simple case of generating the correct URLs (which I did with Excel), uploading to a web site and then clicking on each link.

But this was a long winded process in that I had to a) click on every to/from link (about 900) and then scroll the screen to collect the actual mileage. That takes a long time and as I have done this for seven seasons I thought it was about time to try and automate the process.

The obvious candidate was to use Google maps. When I started the sports scheduling research Google maps did not provide the facilities that I required. Things have moved on since then and Google maps now has an API which makes this type of automation a possibility.

So, over the last few months I have been investigating how to use Google maps, which does not come without its problems. For example, it is not that accurate when using UK postcodes, you have to learn the API, ideally you need to geocode UK postcodes to longitude and latitude etc.

I think that I have now resolved most of these problems and am just doing the last stages of test. So, more soon.

MISTA Conference: Almost There

The MISTA conference is almost upon us.

It was an early start this morning (3am) in order to get to Dublin on the 06:35 flight out of East Midlands Airport. We were actually in the hotel by 09:00 and, thankfully, they had rooms ready so it was not too bad.

We spent the day getting things ready, as far as we could. The real work will start tomorrow and it looks like being a long day. I think we’ll open the registration desk at 07:30 and we’ll return from the Guinness Storehouse at around midnight.

In between that, we have a Plenary Talk by Moshe Dror (“‘Strong’-‘Weak’ Precedence in Scheduling: Extended Order Implications“), followed by 36 papers, split into nine sessions (the full program can be downloaded from here).

For me (and this is a personal viewpoint; not talking as the conference chair) the highlight is the Sports Scheduling session as this is a particular interest of mine, as you’ll see from my previous blog postings. The papers in this session are:

  • Mathematical Modeling for Maximising Gate Receipt Problem, Abdul-Hamid N.H., Kendall G. and Sagir M.
  • A Heuristic for Minimizing Weighted Carry-Over Effects in Round Robin Tournaments, Guedes A.C.B. and Ribeiro C.C.
  • Soccer Schedules in Europe: An Overview, Goossens D.R. and Spieksma F.C.R.
  • Round-Robin Sports Scheduling from a Graph Colouring Perspective: A Case Study in Rugby Union Scheduling, Lewis R. and Thompson J.

… but there are many other excellent papers also being presented throughout the day and your preferences will depend largely on your research interests.

Predicting the Results of Football Matches

I have recently become interested in trying to predict the results of football matches.

The interest grew from wondering what else I could use the data for, that I had collected for generating football fixtures (see JORS paper). The data included the travel distances between all the teams in each division. I also maintained the fixtures that were actually played over the Christmas/New Year period so that I could compare the fixtures I generated against those that were actually played. Needless to say, it took a long time to collect all this data.

As I had gone to all the time and trouble of collecting the data I want to maximise its usage, so I began to look for other uses that I could put it to, and prediction seemed an obvious challenge.

With this in mind, for most of last season I collected additional data that I think might be important in predicting football matches. For example, I have been updating all the scores as each fixture was played. I have also been keeping a record of the odds that bookmakers were offering. Just collecting this data was a large data collection exercise in itself and I certainly did not get the odds on every fixture, but I have enough to be going on with.

I’m not totally sure what I am going to do with this data yet but I know if I don’t collect some of it as and when it is available, it becomes almost impossible (or at least a lot more difficult) to collect.

I have started programming some support functions. For example, given a date and a set of results I can generate the relevant league table for that point in the season.

My ultimate goal is to develop a prediction model and test out how good it is on the 2008-2009 season and, if I find a good model I will try and predict the fixtures for the 2009-2010 season before the matches are actually played.

The new season starts quite soon (kick off is 8th August 2009, but there is one match scheduled on the 7th August 2009).

If I am going to have ever chance of testing the prediction model over the coming season, I need to get programming!