Tibco Spotfire: Training Analytics with footbal data

Has the reduction of clubs in Portuguese league improved competitiveness?

At Polarising we challenge people to get to know Tibco Spotfire using available data online and answer their own questions. This way it’s possible to have hands-on experience with the technology and find out that self-service capabilities are one of Tibco Spotfire strenghts, therefore a perfect tool for immediate insight.

Technology is not our only passion, football also accelerates our hearts. So, let’s find out if the reduction of clubs in the Portuguese league had any impact on competitiveness. First, let’s assume that goal average per game and the number of draws as the match final result are indicators that measure football quality.

Figure 1 is a combined chart, a visualization that combines the features of the bar chart and the line chart. Bars represent the number of matches in a season, they show that between 2007 and 2014 less matches were played since only 16 clubs were in the main Portuguese league. In the remaining seasons they were 18. By putting the goal average line along the bars, the comparison becomes quicker and easier. Only three seasons after the club reduction the goal average increased, then in the last season before the number of clubs returned to 18 (2013/2014) the goal average dropped, and it’s curious that the attendance average made the opposite movement in that same season (see Figure 3).


Figure 1

Figure 2 is a simple line chart showing the percentage of draw as final time result (blue line) and the percentage of 0-0 as final time score (green line). The intention is to see the weight of draws in each season as well as the evolution of number of matches without goals.


Figure 2

We may conclude that there is no clear evidence that less clubs in the league means more goals and less draws. But it’s possible to identify that season 2012/2013 stands out since it had simultaneously the highest average of goals per match (2,78) and the lowest percentage of matches ending with no goals scored (6%).

Public attending games could also be an indicator of football quality and competitiveness, so let’s take a look into stadium attendance statistics. In the following line chart (Figure 3) a Polynomial Curve Fit was added to better understand observed data. The highest attendance average occurred in season 2007/2008 (11242), since then the average has declined slightly. But in the last two seasons – 18 clubs – the descending trend seems to change.


Figure 3

Europe crisis cannot be ignored has it directly affects fan wallets and club budgets, therefore a year with low attendance average may be explained by others factors not related to football. Some definitive conclusions could be taken after crossing this data with other economic and financial indicators.

In conclusion, it’s clear that these charts bring more light over data, and to take advantage from Analytics you must have available and trustful sources, prepare data, and access a powerful tool, yet simple to use, to present information such as the one we used: Tibco Spotfire.


BI & Analytics Consultant at Polarising


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