Singapore Sports Institute sets its sights on gold with Tableau’s high-performing data analytics

As part of its Vision 2030 master plan, Singapore Sports Institute (SSI) is working to develop homegrown athletes and coaches, and to make Singapore a force on the global sporting stage. Competing at the biggest sporting events means harnessing the power of data, and to achieve that requires the help of robust data analytics. With Tableau, SSI established an intuitive and user-friendly data ecosystem for decision-making across multiple stakeholders. Today, SSI uses Tableau to analyze performance from over 70 high-performance athletes across sports including swimming, badminton, and table tennis—helping them effectively train for competitions and forecast success.

Singapore Sports Institute is a statutory board of the Ministry of Culture, Community and Youth (MCCY). The board has a single mission: to inspire and transform Singapore through innovative, fun and meaningful sporting experiences. With its Vision 2030 master plan, SSI hopes to create greater sporting opportunities for Singaporeans and support the development of professional capabilities and standards in coaching.

Learning from professional and amateur sporting organisations across the globe to identify and sharpen details in training regimes using data, the government established the Singapore Sports Institute in 2009, a group that supports the development of Team Singapore athletes as well as the country's sports medicine and sports science industry.

Performing at the very top level in athletics boils down to the minute details in the preparation and planning stages. As such, to predict favourable outcomes for the games, SSI collects high performance sports data from the national athletes.

Benoit Ammann, Deputy Director of SSI, explains: “Analysing sports data is both an art and a science. The science is in analysing the data collected, and the art is in the application of this data to each athlete’s training plans.”

However, before a business intelligence solution was implemented, data analysis at SSI was far from standard protocol.

Different stakeholders like coaches, sports scientists, physiologists, and nutritionists kept their own records of individual athletes, and would manually key and analyse data on Microsoft Excel spreadsheets. This resulted in a high degree of variation and inaccuracies, as each party had different ways of gathering, interpreting and using data.

“The data is not really very powerful unless you share it,” says Mr Ammann. He explains that, despite adopting the correct approach and direction to support the athletes, these stakeholders often overlook the correlation between their individual decisions and the desired overall outcome.

“If you change something in an athlete’s diet, for example, how does that impact their psychology, their sleeping patterns, or their peak performance?” Mr Ammann describes that changes in any of these variables, along with data inconsistencies, can make it challenging to effect quick and informed decisions on athletes' training plans.

Performance data from SSI is critical in SSI’s selection of the athletes who represent the nation at major sport events, such as the Olympics. Prior to establishing such a system, the process of selecting athletes for Team Singapore was time-consuming and prone to errors. It was based on manual calculations of multiple variables, without necessarily giving more weight to certain variables that have a statistically significant impact on peak performance.

When it comes to performance data, where variables can have dramatic effects on competition outcomes, there has to be little – if any – room for misinterpretation. The SSI needed a robust data platform to quickly and easily make sense of the volume of raw data collected from multiple sources. It also had present the information in a manner that was not just clear and concise, but also usable by all the stakeholders involved in different aspects of an athlete’s development.

In looking for data analytics solutions that would tell a coherent and consistent story to the stakeholders involved, the SSI team evaluated various business intelligence solutions. However, some of the options required basic knowledge of coding, and were not sufficiently user-friendly.

For Mr Ammann, the decision to use Tableau's data analytics solutions came from his previous interactions with similar organisations. “I heard of Tableau being used in commercial companies, but my first encounter with it was during the time when I was working with other sports institutes who were already using Tableau for a while.” These encounters also underscored to him the importance of data analytics in sports science. “The success of these teams, and the fact that they have been using Tableau to analyse their data, affirmed our decision to adopt Tableau as well.”

“Implementing Tableau at SSI was a relatively straightforward process due to its ease of use and flexibility”, said Mr Ammann. He found that it was easy to seek help from Tableau to solve technical challenges and keep dashboards up-to-date through Tableau's training sessions, online tutorials and customer conferences.

After Tableau proved its usefulness and accuracy at a competition two years ago, the buy-in from SSI’s internal stakeholders was almost unanimous. SSI then accelerated its process to introduce Tableau to other departments within Singapore Sports Institute, to enable more data-driven decisions.

SSI now uses Tableau to support over 70 high performance athletes across sports including swimming, badminton and table tennis. Given that high performance sports analysis involves scrutinising athletes’ performance down to the millionth of a second, Tableau’s data-crunching capabilities support the coaches and scientists in their efforts to fine-tune the athletes’ training regimes, while maintaining a holistic approach to their overall fitness and well-being.

“The biggest impact that Tableau has had on SSI is the creation of an intuitive and user-friendly ecosystem that has enabled all our stakeholders to be aligned, especially where performance data is concerned,” said Mr Ammann.

Tableau offers individual stakeholders an advanced technology platform to facilitate information sharing. Using Tableau, datasets are easily collated, analysed, and presented on a dashboard that can be created within an hour. This has facilitated a more objective and data-driven decision-making process at SSI, instead of relying on arbitrary statistics and parameters.

The science of analysing competition data, collected from top athletes in Singapore over a two-year duration, is applied to predicting the outcome of major sporting events, such as the upcoming 2017 Southeast Asian Games.

The competition selection process is a tedious one, involving both quantitative and qualitative data sets. With the use of Tableau, SSI can simplify the analysis of individual athletes’ performance data gathered from past competitions – such as their overall score and individual timing – and make informed predictions and projections for future games. Tableau’s ease of use also helps SSI to create data-driven presentations that facilitate internal sharing and alignment.

Tableau is proud to support SSI’s adoption of data analytics technology as an integral component of SSI’s Vision 2030.