PotentiaPRO is an advanced analytics company providing predictive outcomes and comparative effectiveness information for professional sports
Data Architecture, Data Management, Data Analytics, Product Development
Sports, Entertainment
Microsoft SQL, SSAS, OLAP cube, .NET, Python, C#, Microsoft Excel, AWS Amazon, iOS


Fantasy football is extremely popular among NFL amateurs. It's an easy and exciting way to step into the shoes of a football scout. Real-world statistics are crucial for fantasy sports. The better real NFL players perform during the season, the more points their fantasy "owners" score. Back in 2015, fantasy football fans had few to no tools to check NFL statistics. The client trusted our team of data scientists to develop and launch a full-fledged service. The goal was to let fantasy “owners” have all the available NFL statistics at their fingertips. So that they could compare one player to another, or players from NFL history to current rookies to make accurate, data-driven decisions during the draft rounds.

We took on the following challenges:
Provide data cleansing by modifying an avalanche of dirty data.
Orchestrate data across heterogeneous sources.
Architect a database warehouse for terabytes of data.
Design a proprietary similarity algorithm to compare players based on different criteria.
Provide reasonable query execution time.
Provide fast data updates.
Provide an end-user with easy-to-navigate relevant statistics baked in a pixel-perfect app.


Predictive Analytics model to predict football schemes during a game, depending on various input criteria; processed the data from sensors inserted into players' shoulder pads; adopted hard-won insights from Todd Steussie, an ex-player and VP of PotentiaMetrics, who took on the Product Owner role on the project.
ScoutSight’s proprietary similarity algorithm provides fans with unparalleled access to player stats combined with a powerful algorithm to understand how this year's NFL Draft prospects compare to current NFL players.
Custom Cascading filters to provide data cleansing: to detect and replace gaps, duplicates, and irrelevant data. Since the format of NFL data sources varies from season to season, a critical part of the project was to filter all available datasets to unify data.
ETL to fetch out all the data on players, their characteristics, scores, events, and games from multiple heterogeneous systems, and transform the data into a proper format for further querying and analytical purposes.
OLAP cubes in SSAS to store data for quick querying and analyzing terabytes of data. It allows gaining insight into the information through fast, consistent, and interactive access.
AWS Integration to establish complex workflows between distributed systems, and guarantee solid data delivery to thousands of fantasy football fans.
API to connect the data sources with the end-user iOS application.
An easy-to-use iOS ScoutSight application as a reporting system for data analytics; a responsive and clean user-friendly design.
Load testing against the IIS server with a huge number of streams, queues. In order to gauge the performance of the app, more than 1,000 users were involved.


Thousands of dedicated NFL fans were provided with an opportunity to easily navigate all previously inaccessible and unstructured data in a single place.
The data-powered iOS app allows non-professional fantasy sports fans to filter and compare up-to-date sports statistics.
Predictive indexes make it possible to compare players’ stats — hence, to foresee how NFL Draft prospects will perform as rookies.
The service allows users to significantly decrease the time and efforts needed to collect and analyze data, which helps to gain a competitive advantage in building a winning roster team for fantasy football.
Fantasy 'owners' get timely and actionable insights to make smarter decisions based on statistics rather than passion.
The Scouting Notebook feature allows users to save players, comparisons and entire rosters to hit better scores during fantasy draft rounds.

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