dataCoach

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

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Thesis Statements

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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Driven largely by the rising popularity of interactive and pervasive web technologies and the vast amounts of data that the recent push to the cloud has made available, the field of data visualization has experienced a great surge in growth over the past several years. As the bleeding edge of the industry is pushed forward at a faster and faster rate with the help of complementary fields such as art, science, politics, and design, however, the distance between this rapidly moving frontier and certain smaller areas within the greater field of data visualization—specifically, those that lack the public interest or funding necessary to keep up with the state of the art—grows larger.

The collection and visualization of sports statistics for the non-professional athlete is a particularly interesting example of one of these trailing areas. Despite advances in the larger field, and most notably despite the incredible technological advances we have seen in professional sports for tracking and analyzing statistics, the commonly available set of tools for collecting, visualizing, and analyzing game data for members of sports communities that do not have the financial backing (and R&D labs) of the professional sports industry has remained relatively stagnant. In order to resolve this gap, and consequently provide these recreational and scholastic athletes with more sophisticated data tools, it is imperative that we study the techniques that have thrust the larger field of data visualization into the spotlight and apply them to the creation of intuitive and innovative interfaces for non-professional sports. And while no single product can bridge this gap on its own, I am working to bring us one step closer to that goal by creating 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 this system is threefold: 1) to facilitate and encourage the collection of data, 2) to enable deeper comprehension of the data through visual exploration, and 3) to enhance traditional game statistics by tagging each piece of data with the location and time at which it was recorded before sending it to the cloud. This will not only allow for the immediate visualization and interpretation of the data as the games are taking place, but will also provide the coaches and players with something much more meaningful: a dataset that preserves the spatiotemporal (and consequently cause and effect) relationships between events. This additional information will provide greater insight into the strengths and weaknesses of the players without sacrificing the traditional methods that they have grown accustomed to, resulting in a richer understanding of the data—all without the prohibitive costs of professional-grade tools.

data_coach explores one possible implementation of this system: an iPad app that is tailored specifically to the needs of lacrosse—a young, rapidly growing sport that currently lacks the level of infrastructure present in more established sports communities. Through a case study focused on several youth lacrosse teams in New York and the Bay Area, and calling upon my own 18 years of experience as both player and coach, my project will demonstrate how the thoughtful reconfiguration of existing technologies can empower a wider sports community by helping them transform data into knowledge.

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There is a growing gap between the rapidly expanding field of data visualization and sports statistics tracking at the non-professional level. I seek to bridge this gap by creating an ecosystem of easy to use, cloud-based tools for real-time mobile statistics collection and visualization. The purpose of this system is threefold: 1) to facilitate and encourage the collection of data, 2) to enable deeper comprehension of the data through visual exploration, and 3) to enhance traditional game statistics by tagging each piece of data with the location and time at which it was recorded. This will allow for both immediate data analysis and the preservation of spatiotemporal relationships between events—without the steep learning curve or prohibitive costs of professional-grade tools.

data_coach explores one possible implementation of this system: an iPad app tailored to the needs of lacrosse. Through a case study focused on several youth lacrosse teams in New York and the Bay Area, my project will demonstrate how the thoughtful reconfiguration of existing technologies can empower a wider sports community by helping them transform data into knowledge.

My thesis blog can be viewed at http://lizrutledge.com/mfa-thesis.

view this post!

There is a growing gap between the rapidly expanding field of data visualization and sports statistics tracking at the non-professional level. I seek to bridge this gap by creating an ecosystem of easy to use, cloud-based tools for real-time mobile statistics collection and visualization. The purpose of this system is threefold: 1) to facilitate and encourage the collection of data, 2) to enable deeper comprehension of the data through visual exploration, and 3) to enhance traditional game statistics by tagging each piece of data with the location and time at which it was recorded. This will allow for both immediate data analysis and the preservation of spatiotemporal relationships between events—without the steep learning curve or prohibitive costs of professional-grade tools.

GametimePLUS explores one possible implementation of this system: an iPad app tailored to the needs of lacrosse. Through a case study focused on several youth lacrosse teams in New York and the Bay Area, my project will demonstrate how the thoughtful reconfiguration of existing technologies can empower a wider sports community by helping them transform data into knowledge.

My thesis blog can be viewed at http://lizrutledge.com/mfa-thesis.

view this post!