UX DESIGNER
My Roles
Tools I used
SCOUT
UX Engineering
Product Design
Interaction Design
C#
Raspberry PI 4
Python + TENSOR FLOW
Keyshot
Figma
Miro
Adobe Creative Suite
Team Members
Sullivan Wilcox
Chris Bartoldus
Satchel Hallmark
Awards
Project Overview
​Create an AI assistant specializing in a certain area paired with a physical device that is kept in your person to record your data in real-time. Ultimately connected to the AI version of yourself existing and living in the metaverse.
If you would like to view the fully detailed version of our project, showcasing everything...
Feel free to download the process book!
NFL scouts struggle to efficiently manage hundreds of college football prospects, which hinders their ability to identify and analyze talent for their team’s draft each year.
The Problem
Our Solution
A software and product providing NFL scouts with college player tracking data and additional insights on how a prospect might transition professionally, while putting all their tracking, athletic, and medical information they need about a player in one place.
My Focus: UX Engineer | Product Developer
As a UX Designer, I was involved in every step of the process --including research, software implementation, UI design, user testing, and others.
1. Product 3D Modeling & Rendering: Camera, UWB Chips, UWB Receivers
2. Software and products: Design and built
3. User testing
4. UWB Chips, and UWB Receiver: 3D printing, sanding and painting
5. Camera: Building with Raspberry PI 4 + Tensor Flow
6. Camera: Coding and prototype to tracks and recognizes specific objects (Football, Human, Sports gear). Fed into the AI
7. Vision Video: Creation
8. Motion Design: Creation of motion visuals and microinteractions
The following images and videos are clips of my experience during the Engineering side of things. You can see our team in an open soccer field with a power generator that we brought to test our product in the real world.
You can also see the camera in action -- Moving and tracking objects.
The camera failing (Our first prototype was too heavy and unable to move)
(You might have to click or tap on the images to see the full image)
Take a look at our final deliverables at the bottom of this page!
Design Process
01. Research
03. Prototyping
02. Concept
04. Final Product
01. Research
NFL SCOUTS
Evaluate the talent of college football players and are responsible for identifying players that have the potential to succeed in the NFL.
IN A 2021 INTERVIEW WITH ESPN:
"AN NFL SCOUT VERIFIED HE'S SPENT ONE-FIFTH OF HIS LIFE ON THE ROAD, AS PART OF HIS SEARCH FOR THE NEXT NFL STAR. EACH NFL SCOUT WILL TYPICALLY TRACK AROUND 300 PLAYERS"
Currently, scouts analyze college athletes by:
Tracking D1 athletes
Since 2016 the NFL has been using Zebra Technologies RFID chips to track real-time player data like location, speed, and acceleration for every player.
The Senior Bowl is a post-season college football all-star game that showcases the best NFL Draft prospects. They just inked a deal with Zebra and Next Gen Stats to track draft prospects.
Opportunity Space:
Create a way to implement existing RFID technology into college players to help scouts make wiser choices based on accurate athletic data while giving scouts autonomy over their time and lives.
Who would use our product?
With our target users in mind, we created a persona and journey map to represent our current archetype and the experience that they currently go through. With the journey map, we can spot problem areas which we can use to facilitate their lives.
In summary: Michael is a busy father who loves his profession and strategically builds teams for the NFL, however, his career leaves him with a terrible work/life balance and does not allow him to be around his family most of the time. With outdated methods of keeping track of athletes, scouts end up burnt out.
02. Concept
SCOUT
A player tracking system for NCAA College Football making it easier for professional scouts to analyze, compare, and manage prospective talent.
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The idea:
To use camera tracking technology in conjunction with our software to provide our users real-time accurate athletic data.
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How might we:
Combine player tracking data with machine learning to create an analytical sports AI that can aid in player and team development?
With the idea in mind, we created a diagram to represent how our product would look like in action. The product contains a camera, multiple Ultra-Wideband Receivers and Ultra-Wideband Chips
The camera will focus on whichever athlete is chosen and transmit data between it and the UWB chips and receivers to communicate all athletic tracking information. That information will then be stored on our software.
We then moved-on to create lo-fi versions of our product and software. I focused on the 3d modeling and product side. Once we created the concepts, we began user testing our lo-fis.
Once we finished our User Testing with actual Scouts we knew what we had to do and began prototyping.
03. Prototyping UI and Product Design
04. Final Deliverables
