Paying homage to our fondness of brain-teasers, every month we post a new challenge created by the Forensic Technology team, focusing on logical, analytical and coding problems.

For this month’s challenge, we are heading over to Rio (figuratively) and getting into the spirit of the Paralympic games. Using the publicly available data for the last two Paralympics (Beijing and London), we want you to predict using a mathematical model how many gold medals ParalympicsGB will win in Rio.

We are deliberately leaving this open-ended, so use any applicable data that you unearth to feed into your model. This could include funding levels per sport, previous numbers of gold medals won in past Paralympics, as well as a healthy dose of probability and statistics.

As a starter, here is the number of medals that ParalympicsGB have won in the last two Paralympics:


A good place to find information about ParalympicsGB are here, here and here.

Post your predictions and models below, and we will see who can get the closest result. Why not try and accurately predict the overall gold medal total before the end of the Paralympics!

After the Paralympics have finished, can you refine your model to predict the total number of gold numbers actually won? We’ll be posting our model and prediction next month, along with Challenge #4.

What's the answer?

Well done ParalympicsGB! With 147 medals they have made everyone proud and with 64 of those being gold they have done better than our model predicted…

Our simplistic model is based on 4 formulae that each predict the total gold medal haul of the GB Paralympics team. These use different factors we think strongly correlate with a country’s sporting performance. We then averaged the 4 results to generate our final prediction of 58 gold medals. The resources used for the data input into the formulae are referenced below.


1) We took an average of the ratios of gold medals won in the previous 2 Paralympics against the UK’s GDP during those years. We then multiplied this against last year’s GDP to get our first gold medal figure.

2) We looked at the ratio of total gold medals won in the previous Paralympics versus the total funding that went into them. Multiplying this by the funding that went into this year’s Paralympics gave us our second prediction.

3) In this formula we started looking at each sport individually and the ratio of golds won against funding invested into that sport in previous Paralympics. Multiplying this by the funding invested for the 2016 games and summing over all sports we participated in this year we arrive at our third gold medal prediction.*

4) Like 3) we looked at summing ratios over all sports but instead of funding per sport we looked at the upper bound of total number of medals UK Sport predicted we would win to get our final gold medal value.*

*Note that where ParalympicsGB participated in new events in 2016 we used an average of all the ratios of the other sports to provide data when summing over all sports.

We used a variety of sources for data, including UK Sport, Trading Economics, and two Wikipedia pages here and here.

We would like to hear your thoughts about our model. Would you have considered other factors and how? Could you have improved our model e.g. should we have used different GDP figures? 

If you are someone who enjoys problem-solving, logical thinking and technology, check out our Forensic Technology graduate roles to see if they are the right fit.


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