dataCoach

liz rutledge | thesis documentation site | parsons mfa design + technology

Current version of my exhibition plaque copy, trimmed all the way down to 195 words! It was definitely tricky trying to preserve the important “talking points” while not overwhelming the target audience (i.e. someone who doesn’t necessarily know what I’m talking about and whose interest is primarily as a passer-through/viewer as opposed to an academic critic). I’d love any feedback on whether or not I was too aggressive or not aggressive enough with my trimming shears!

The copy:

Sports represent the convergence of three main elements: practiced skill, physical effort, and data. And while the larger field of data visualization is experiencing unprecedented growth, the commonly available set of tools for collecting, visualizing, and analyzing game data for youth, high school, and recreational sports communities remains limited. In order to narrow this gap, dataPlay provides non-professional athletes with some of the same tools as their professional counterparts through a focused system of easy to use, cloud-based tools for the mobile collection, visualization, and analysis of sports statistics in real time.

The purpose of the dataPlay system is threefold: 1) to facilitate and encourage the collection of data, 2) to enhance traditional game statistics by tagging each piece of data with the location and time at which it was recorded, and 3) to enable deeper comprehension of the data through visual exploration of these preserved cause and effect relationships. With a full suite of tabs that allow scorekeepers, coaches, parents and players to augment their current practice with rich data tools, dataPlay investigates how the thoughtful reconfiguration of existing technologies can empower a wider sports community by helping them transform data into knowledge.

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New coach to talk to + team to test with!!!

Just confirmed with New School server master extraordinaire Scot Weir that we’ll be meeting in the coming week to discuss my project, prototypes, system and more! Scot is in the awesome position of having been a newbie parent who knew nothing about lacrosse mere years ago, who has since risen up the ranks of helping at practice to becoming head coach of his daughter’s lacrosse team this season. (In fact, he just received his Level II Certification, which takes all sorts of work and testing…quite the metamorphosis!)

The plan is to have him test what I’ve got working so far, ask for his feedback on the functionality I’m still finessing, and then visit his team to talk to the girls about what they would love to see in a visualization, what their PARENTS would love to see in a visualization, and to have some combination of Scot and the parent scorekeeping volunteers test the full system at full fidelity. SUPER exciting!

Updates soon!

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Not fully polished yet but testing the interactions between the data collection interface and representing/visualization that data through the visualization interface. It currently doesn’t update on its own (you’ll see me refreshing the window on the right) but the final version will be making ajax calls at intervals to keep it updating live.

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I haven’t had time to format these nicely yet, but here is some of the feedback I received from Firehawks U-15A coach Lauren Hechlinger after testing my prototype!

User Testing: Firehawks U15-A
User Testing: Firehawks U15-A
User Testing: Firehawks U15-A
User Testing: Firehawks U15-A Girls Lacrosse
User Testing: Firehawks U15-A Girls Lacrosse
User Testing: Firehawks U15-A Girls Lacrosse

Feedback

DATA COLLECTION
goalie shots chart
often will have injured girls note these shots (made and saved)

“great because this makes it a one-person job”

numbers not faces/roster
have numbers go right to left for easier 1-digit entry

take advantage of parent volunteers

VISUALIZATION
cause and effect in vis

larger field for easier comprehension

bar charts smaller—even just lines (like Pennant)

let them scrub through manually though, no arrows etc (will become contrived)
at each key play, show by default the 30 seconds before that and 30 seconds afterwards (if not goal)

still include box score for easy transcription at end

OBSERVATION
separate possession view for injured player or parent volunteer
just key in the number of whoever has the ball at that moment to know exact possession times (including buttons for on the ground and out of bounds)

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dataPlay: Visualization Dashboard

Further description to come! (Information aspects also analyzed in a future presentation post: Information Design Assessment: Play Recording and Visualization Dashboard Interfaces

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Pervasive web technologies and the popularity of cloud computing have materially changed the way that data is collected, stored, and distributed—a change that has raised both the quantity and quality of publicly-available data. As a result, the data visualization community is experiencing unprecedented growth and visibility, simultaneously encouraging innovation and increasing the distance between industry leaders and certain smaller groups within the field.

Data_coach investigates this gap from the perspective of one of these niche fields: the collection and visualization of statistics for non-professional sports. Statistics tracking and analysis in professional sports has seen significant progress in the last 10 years, producing systems that are able to automatically track player movement and use that data to identify relevant statistics and trends in extraordinarily high fidelity. These systems, however, are prohibitively expensive and require extensive technical expertise to deploy, which greatly restricts their applicability to the wider sports community. Without access to these innovative tools, this larger community is forced to settle for a limited array of tools that lack robust integration between data collection and visualization, and which are often difficult to use. Data_coach addresses this problem by providing recreational and scholastic athletes with a focused system of easy to use, cloud-based tools for the mobile collection, visualization, and analysis of sports statistics in real time. This unique combination of low-cost web, mobile, and cloud-based technologies, the structure of which is driven by the fundamental principles of information design, is scalable to a wide array of sports and represents a new way of thinking about game data collection and visualization.

The overarching purpose of data_coach is to allow athletes and coaches to glean insight from their data through a series of interactive visualizations—effective visualizations, however, require good data, which first needs to be collected. In light of this fact, data_coach is designed around three main goals: 1) to facilitate and encourage the collection of data, 2) to enhance traditional game statistics by tagging each piece of data with the location and time at which it was recorded, and 3) to enable deeper comprehension of the data through visual exploration. This system will not only allow for the immediate visualization and interpretation of the data as the games are taking place, but will more also provide the coaches and players with a dataset that preserves the spatiotemporal (and consequently cause and effect) relationships between events. As a result, athletes and coaches will be able to visualize team or player-level trends over the entire season, drill down into a specific game-changing play to examine an exact sequence of events, or review stats across any timespan in between—without the prohibitive costs of professional-grade tools.

Data_coach: Lacrosse represents one possible implementation of this system: an iPad app that is tailored specifically to the young, rapidly growing sport of lacrosse. Through a case study focused on several youth lacrosse teams in New York and the Bay Area, data_coach: Lacrosse will demonstrate the proposed value of this type of system: how the thoughtful reconfiguration of existing technologies can empower a wider sports community by allowing them to transform data into knowledge.

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