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Playar Prototype
Intorduction
The game of cricket is a sport of fine margins, it takes a fraction of a second to hit a ball that's traveling at a speed of over 130 kmph or get out to it. Hence, in this sport decision-making within that split second is crucial for players.
A common problem coaches and players face is to analyze their game in real-time or simulate real game situations during their practice session, so that they can prepare themselves better and extract actionable data to improve their performance. PlayAR is a cricket app designed to help players improve their performance.
It achieves this by providing real-time batting analysis through advanced performance data, simulations, and actionable insights. The app addresses common problems coaches and players face by evaluating their performance in real-time and simulating their net practices with real-world situations, such as batting during high-pressure death overs or adapting to specific pitch conditions like those at the Chinnaswamy Stadium. This is achieved by video recording players' batting performance and converting key metrics, such as launch angle, launch speed and ball contact points, and delivering valuable feedback tailored to improving their practice sessions.
The game of cricket is a sport of fine margins, it takes a fraction of a second to hit a ball that's traveling at a speed of over 130 kmph or get out to it. Hence, in this sport decision-making within that split second is crucial for players.
A common problem coaches and players face is to analyze their game in real-time or simulate real game situations during their practice session, so that they can prepare themselves better and extract actionable data to improve their performance. PlayAR is a cricket app designed to help players improve their performance.
It achieves this by providing real-time batting analysis through advanced performance data, simulations, and actionable insights. The app addresses common problems coaches and players face by evaluating their performance in real-time and simulating their net practices with real-world situations, such as batting during high-pressure death overs or adapting to specific pitch conditions like those at the Chinnaswamy Stadium. This is achieved by video recording players' batting performance and converting key metrics, such as launch angle, launch speed and ball contact points, and delivering valuable feedback tailored to improving their practice sessions.
The game of cricket is a sport of fine margins, it takes a fraction of a second to hit a ball that's traveling at a speed of over 130 kmph or get out to it. Hence, in this sport decision-making within that split second is crucial for players.
A common problem coaches and players face is to analyze their game in real-time or simulate real game situations during their practice session, so that they can prepare themselves better and extract actionable data to improve their performance. PlayAR is a cricket app designed to help players improve their performance.
It achieves this by providing real-time batting analysis through advanced performance data, simulations, and actionable insights. The app addresses common problems coaches and players face by evaluating their performance in real-time and simulating their net practices with real-world situations, such as batting during high-pressure death overs or adapting to specific pitch conditions like those at the Chinnaswamy Stadium. This is achieved by video recording players' batting performance and converting key metrics, such as launch angle, launch speed and ball contact points, and delivering valuable feedback tailored to improving their practice sessions.
Objective
The primary objective of this project was to create an early prototype that offered a smooth user experience, simplified onboarding, quick setup and calibration for accurate batting analysis.
The entire process was a collaborative effort between the founder, engineering team and myself. Throughout the development cycle, there were constant iterative cycles between all the stakeholders to achieve the best MVP. Testing and feedback were key characteristics of our process. We conducted frequent testing sessions with coaches and players to refine the tech, design and features based on their feedback.
While developing the various versions, we invested significant effort in implementing the core features and functionalities that would enable us to create an MVP. We made a conscious effort to ensure that the user experience was tailored to the device, striking a balance between native and custom elements. The design exercise also demanded the need for a design system that would ensure scalability, consistency and a streamlined future development.
The primary objective of this project was to create an early prototype that offered a smooth user experience, simplified onboarding, quick setup and calibration for accurate batting analysis.
The entire process was a collaborative effort between the founder, engineering team and myself. Throughout the development cycle, there were constant iterative cycles between all the stakeholders to achieve the best MVP. Testing and feedback were key characteristics of our process. We conducted frequent testing sessions with coaches and players to refine the tech, design and features based on their feedback.
While developing the various versions, we invested significant effort in implementing the core features and functionalities that would enable us to create an MVP. We made a conscious effort to ensure that the user experience was tailored to the device, striking a balance between native and custom elements. The design exercise also demanded the need for a design system that would ensure scalability, consistency and a streamlined future development.
The primary objective of this project was to create an early prototype that offered a smooth user experience, simplified onboarding, quick setup and calibration for accurate batting analysis.
The entire process was a collaborative effort between the founder, engineering team and myself. Throughout the development cycle, there were constant iterative cycles between all the stakeholders to achieve the best MVP. Testing and feedback were key characteristics of our process. We conducted frequent testing sessions with coaches and players to refine the tech, design and features based on their feedback.
While developing the various versions, we invested significant effort in implementing the core features and functionalities that would enable us to create an MVP. We made a conscious effort to ensure that the user experience was tailored to the device, striking a balance between native and custom elements. The design exercise also demanded the need for a design system that would ensure scalability, consistency and a streamlined future development.
Design
In our initial explorations, we started with a mobile approach, an iOS native app that would use Apple's on-device machine learning and computer vision. This choice was driven by the platform's robust capabilities for real-time processing through on-device computations. Since we were working on a prototype, we knew our form factor (referring to the physical design and interface layout) would change based on feedback and tests. However, we ensured that our core design principles were versatile enough to function well regardless of the form factor. There were a few key design principles that guided us throughout the process:
Data would not be intrusive or overwhelming.
Insight to performance orientation.
Data should work like Lego (customization).
Finding what you want and when you want should be easy.
Eventually, the product might get sophisticated enough that it would be able to figure this out by itself with AI.
The iOS approach incorporated a native feel and a few custom components like drawers, illustrations, steppers, etc that allowed us to make the interface unique, delightful and intuitive.
In our initial explorations, we started with a mobile approach, an iOS native app that would use Apple's on-device machine learning and computer vision. This choice was driven by the platform's robust capabilities for real-time processing through on-device computations. Since we were working on a prototype, we knew our form factor (referring to the physical design and interface layout) would change based on feedback and tests. However, we ensured that our core design principles were versatile enough to function well regardless of the form factor. There were a few key design principles that guided us throughout the process:
Data would not be intrusive or overwhelming.
Insight to performance orientation.
Data should work like Lego (customization).
Finding what you want and when you want should be easy.
Eventually, the product might get sophisticated enough that it would be able to figure this out by itself with AI.
The iOS approach incorporated a native feel and a few custom components like drawers, illustrations, steppers, etc that allowed us to make the interface unique, delightful and intuitive.
In our initial explorations, we started with a mobile approach, an iOS native app that would use Apple's on-device machine learning and computer vision. This choice was driven by the platform's robust capabilities for real-time processing through on-device computations. Since we were working on a prototype, we knew our form factor (referring to the physical design and interface layout) would change based on feedback and tests. However, we ensured that our core design principles were versatile enough to function well regardless of the form factor. There were a few key design principles that guided us throughout the process:
Data would not be intrusive or overwhelming.
Insight to performance orientation.
Users dictate what they want, hence customization would be key.
Data should work like Lego and allow users to customize it for their needs.
Finding what you want and when you want should be easy.
Eventually the product might sophisticated enough that it would be able to figure this out by itself with AI.
The iOS approach incorporated a native feel and a few custom components like drawers, illustrations, steppers, etc that allowed us to make the interface unique, delightful and intuitive.
Eventually, we transitioned to a desktop (Mac) approach where we incorporated some of the same principles that we started off with. We prioritized users’ ability to customize their experiences, such as adjusting metrics displays or selecting specific performance parameters to focus on, access their recordings easily through an intuitive dashboard, and the overall ease of using the product.
In this iterative version of the product, we had to implement a different setup method, which required seamless integration with the app's functionality. The Mac approach also provided more screen space, allowing us to experiment with layouts and visualizations.In this iterative version of the product, we had to implement a different setup method, which required seamless integration with the app's functionality.
Eventually, we transitioned to a desktop (Mac) approach where we incorporated some of the same principles that we started off with. We prioritized users’ ability to customize their experiences, such as adjusting metrics displays or selecting specific performance parameters to focus on, access their recordings easily through an intuitive dashboard, and the overall ease of using the product.
In this iterative version of the product, we had to implement a different setup method, which required seamless integration with the app's functionality. The Mac approach also provided more screen space, allowing us to experiment with layouts and visualizations.In this iterative version of the product, we had to implement a different setup method, which required seamless integration with the app's functionality.
Eventually, we transitioned to a desktop (Mac) approach where we incorporated some of the same principles that we started off with. We prioritized users’ ability to customize their experiences, such as adjusting metrics displays or selecting specific performance parameters to focus on, access their recordings easily through an intuitive dashboard, and the overall ease of using the product.
In this iterative version of the product, we had to implement a different setup method, which required seamless integration with the app's functionality. The Mac approach also provided more screen space, allowing us to experiment with layouts and visualizations.In this iterative version of the product, we had to implement a different setup method, which required seamless integration with the app's functionality.
Overall, throughout the MVP building process and early prototype testing, our goal was to design from a user’s perspective, ensure the core offerings work well and the product does not get bloated too early, gather early feedback to further iterate on the product and ensure it meets users’ needs and accomplishes the goals it set out to achieve.
Overall, throughout the MVP building process and early prototype testing, our goal was to design from a user’s perspective, ensure the core offerings work well and the product does not get bloated too early, gather early feedback to further iterate on the product and ensure it meets users’ needs and accomplishes the goals it set out to achieve.
Overall, throughout the MVP building process and early prototype testing, our goal was to design from a user’s perspective, ensure the core offerings work well and the product does not get bloated too early, gather early feedback to further iterate on the product and ensure it meets users’ needs and accomplishes the goals it set out to achieve.
Contribution
All the app version screens, prototypes, design system and website landing page was designed by Abhinav. He worked closely with the founder and engineering team.
All the app version screens, prototypes, design system and website landing page was designed by Abhinav. He worked closely with the founder and engineering team.
All the app version screens, prototypes, design system and website landing page was designed by Abhinav. He worked closely with the founder and engineering team.
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