Sports Analytics

Inspiration The inspiration for our project lay solely with our team competing in Fantasy Football against one another. We wanted to use sports data to find out which players had the greatest impact the past couple of seasons and be able to see trends, as well as which player would perform better against certain teams for the upcoming season.

What it does? Our dashboard uses Metrics as KPIs for the scores and player stats. We designed the Semantic Model to be able to try and see scores, when the game occurred, and the players individual stats and how they join. From this, we can see the player's stats and how they perform against teams to help make more valuable insights as a fantasy football team manager.

How we built it Our Project was built using .csv files containing dimensional data for players and teams, in conjunction with fact tables pertaining to stats and games.

Challenges we ran into The intent with our project was to have three dashboards. Overall, we intended to have the first dashboard be a landing page in which we would be able to see an overview of the entire league. Once seeing the overall performance of each team in the league, our intention was to be able to drill through to the second dashboard that would filter specifically to the selected team and similarly show some of the overview data in addition to team specific metrics. From there, we planned to drill through the team specific metrics (ex: on the Team Dashboard it would show the best performing players.) to an individual player specific dashboard where key insights would help the end user make decisions based off the individual players’ performance and impact. Compared to Tableau Desktop, there is no dashboard action capability that allows drill throughs. This caused a major challenge for our overall dashboard concept and design.

Accomplishments that we're proud of We are proud we have got a better understanding of the nuances of Tableau Next versus the Tableau products we are already familiar with. In addition, it was very nice to be able to see how the Salesforce can be utilized while paired with Tableau natively within the platform.

What we learned We learned there are a handful of limitations that we could not find many workarounds for. As mentioned above, we wanted to find a way to add filter actions that allow drilling through to see the data structured from a higher level to the lowest level. We learned given the current state of Tableau Next, it is not entirely capable.

What's next for Sports Analytics? Sports Analytics will be going steady as we try and find ways to make our dashboard truly come to life.

Built With

• api-sports