Helping working dads manage a recreational basketball league in their spare time
Dribble is a mobile web app dedicated to streamlining the management of recreational basketball leagues for working dads during their spare time. Dribble automates tasks and alleviates the burden on managers to monitor the league throughout the day, allowing them to stay on top of their game!
Business Goal
Cosmopolitan Basketball League aims to transition to digital tools to run more efficiently and minimize financial losses, by exploring new approaches to resolve time conflicts, manage data, and monitor league progress.
01 Product Preview
Swiftly tackle urgent issues
Alleviating the stress of texting teams, players, referees, or scorekeepers to find replacements
Gauge how your teams are growing
Interpreting convoluted tables on your own means less time spent accessing team growth
Describe what you see live, we’ll document it for you
Scorekeeping made easy: no more tracing tiny cells or flipping between sheets
02 Challenges
Something small to you might mean the world to your user
Learning the lingo of the game: Understanding current systems, tools, and core needs by talking to the folks who keep the league running
Competitive Analysis
Building on Foundational Features to Meet the Need
I started off the project by familiarizing myself with other companies within the sports industry to determine what each offered and lacked that could allow Dribble to stand out among all. I found that having basic features: messaging, scheduling, registration are essential. However, too many features confused and overwhelmed users from carrying out their daily goals.
User Research Insights
Adopting Meaningful Abbreviations
What seemed vague and foreign to me was specific and informative for most players and scorekeepers to share valuable observations and crucial ideas.
To learn these terms, I annotated the league’s scoresheets and tools. Additionally, I explored sports entertainment sites that players frequent to find terms that they are well-versed in.
User Research Insights
Understanding Familiar formats: Graphs
Many users watch sports and follow sports analysts who use graphs and charts to compare team rankings and player stats. I learned to identify differences in stat data users look for to gauge progress and improvement.
These visualizations often spark observations and conversation from fans, so I wanted to apply these common data displays to my design.
Quantitative and Qualitative Data
Talking to the people who make the league run: managers, players, and scorekeepers
I set up one on ones with scorekeepers and managers, and sent out a survey to basketball players to understand their use of the current system and tools.
User Research Insights
Understanding Core Needs
To understand our users, I identified 3 key user pain points.
Personas
Busy working dads by day, coaches by night
Cosmo isn’t your typical NBA sports team, it’s a local recreational basketball league made of passionate working adults and high school students who simply love to ball.
Each season brings in about... 500 players 30 teams 4 divisions 3 scorekeepers 3 referees
02 Challenges
Going mobile for quick and easy access during breaks
Busy working dads are drained from juggling the changing needs of 500 players in their small pockets of free time
Key Feature 01
Taking your summary of issues to-go
Managing over 100+ players, many issues tend to slip through the cracks and build up, bringing the season to a halt: adding players to the roster, time conflicts, cancellations from referees, scorekeepers, teams, players, etc.
Process 01
Gently poking the user about urgent issues to fix
User testing revealed users were initially overwhelmed by the first iterations: alarming attention-demanding labels + lists of issues
1. I minimized the use of red by consolidating tags to restore users’ focus.
2. Grouping issues into approachable short lists reduces cognitive load. Significantly boosted user motivation to fix issues!
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Process 02
Helping users recognize, accurately diagnose, and gracefully recover from errors
The initial iterations simply alerts and helps users locate the issue, but leaves them to scour teams’ availability sheets to resolve the issue.
The final iteration goes beyond to give users a solution to their issue: uses AI to find an available person with an additional tap.
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02 Challenges
Going mobile for quick and easy access during breaks
Busy working dads might fail to notice that some teams may not be in the best environment to grow: teams that are doing too well or falling behind
Key Feature 02
Ensuring all teams are in a position for growth
I wanted to explore new ways to help find outliers because extremes are a sign of mismatch.
League managers do not have time to review graphs of data each day. Simplified previews allow managers to spot differences and outliers in data at a glance.
Process 02
Capturing the most crucial data points in a bundle of highlights
Initial iterations were informative... but overwhelming. So I decided to allow the user to explore where their curiosity leads them.
Previews display data highlights. When clicked, users are directed to larger bodies of data for a closer look.
Process 03
Making small changes to help users make the right interpretations
Recorded stats provide useful sports data, but results are not always interpreted correctly.
My changes between iterations all worked together to highlight teams who are not in a place of growth (outside of the average range)
Process 04
The user may not always know what they need
Users wanted to visualize outliers efficiently with color. However what they really needed was a less alarming way to distinguish outliers.
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Allowing the user explore data to judge if a team is an outlier.
Experimenting with color to draw attention to outlier teams.
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Finding alternate ways to display data and highlight outliers.
03 Improving Technical Feasibility
Hold up, are these even technically feasible?
I presented my initial ideas to developers
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📍 Technical Feasibility
Constraint: Complex Databases
Databases are too complex and time-consuming to set up
Constraint: Standardization
Databases are too complex and time-consuming to set up
Constraint: Complex Databases
Databases are too complex and time-consuming to set up
Scorekeepers have their hands full and heads down marking tallies during the game, missing crucial live plays
Research Insight
Scorekeepers only have two hands to hold 5 things
What scorekeepers are using now: 1. Clipboard with Team A's Scorecard 2. Another clipboard with Team B's Scorecard 3. Pencil 4. Scoreboard Remote 5. Timer
Research Insight
A need to make inputting data more efficient by digitizing the scoresheet
During the game, scorekeepers have their heads down, meticulously marking tallies on scorecards. Scorekeepers are stuck tracing cells instead of players.
Even after the game concludes, scorekeepers continue their work at home, counting up tally marks and manually entering values into spreadsheets.
Key Feature 03
What if you could mark stats without taking your eyes off the game?
I explored new ways for scorekeepers to spend less time looking down at the clipboard.
Process 01
Making the helpful speech tool the focus of the page
In User Testing, Scorekeepers expressed how the Speech tool would greatly improve their focus on the game if it was more accessible, not just a convenient side feature.
Process 02
Designing for Familiarity
Following the scorekeeper’s intuitive motion and classic sequence of thoughts when recording during the heat of the game. Order of thought: team, action and player
Motion: Allow faster switching between teams by saving bundles of plays to history
Process 03
Designing for Clarity
As scorekeepers voice each player’s action, there is a need to translate a dense paragraph of spoken words into simple, informative stat tags that are easy to read and logged into the game’s history.
Design System
Touched with Community
A reflection of the passionate people who make the league possible.
03 Impact
Reduced percentage of cancelled games by -8%, significantly minimizing financial losses by 27%! (we used to lose -$26,400 a year...)
Of the 96 games that happen per month, the league previously averaged about 11 cancelled games per month. Only 3 games were cancelled in September.
League managers only take a minute of their day to check on team progress
Managers used to analyze tables of convoluted team data by making mental comparisons to spot extremities. Now, they can identify variation by quickly glancing through graphs.
Scorekeepers look up for 93% of the game
Scorekeepers previously only looked up for 65% of the time when the ball is in play.
04 Reflection
🌍
Something small to you might mean the world to your user!
I initially discounted the value of abbreviated terms and spelled out terms in my lofi prototype. I earned a few disapproving furrowed brows during the first rounds of user testing.
🎁
Learn continuously from your user
I loved that each time I conducted a user test, I discovered a new usability issue, and in turn, a UX term or heuristic! I look forward to learning from my users.
💎
Document, document, and document!
Document your rationale, your research insights, the numbers you spent hours crunching, each inspiring story from an interview. Your design artifacts are GOLD.
