Sports Science and Analytics

Sports analytics , Data Science, IoT, Physics-based Modelling

IRIS Webinar

The work plan will focus on four sports - cricket, tennis, running and football - using three methodological approaches - physics-based, data-driven and sensor and IoT driven. Eight cross-cutting problems have been identified which address the science of various aspects of sporting including ball bounce and impact, machine vision technology for aiding sporting decisions, Monte Carlo and graph theoretic models of sport, understanding the role betting, reinforcement learning for aiding game time decision making and developing IoT systems for capturing real time data from match-time and practice sessions.

  • Finally, these work packages will be integrated into a model that can be used by athletes or sporting clubs for training as well as decision making.

Sports Science and Analytics

Nandan Sudarsanam

Principal Investigator


Luis A. Nunes Amaral

Area of Interest

Luis A. Nunes Amaral

Co-Principal Investigator

Chemical and Biological Engineering
Mahesh Panchagnula

Area of Interest

Mahesh Panchagnula

Co-Principal Investigator

Applied Mechanics
Noshir Contractor

Area of Interest

Noshir Contractor

Co-Principal Investigator

Behavioral Sciences
Roger Guimerà Manrique

Area of Interest


The primary goal of this Center is to bring the rigor of scientific approach to sport from physics as well as data analytic perspectives. The specific objectives of the Center are:

  • to be an intellectual hub for sports analytics and science that is first of its kind.
  • to use the insights gained for improving athlete performance as well as fan engagement.
  • to use experimental resources for primary ground-truth validated data generation.
  • to work with the sporting clubs, media and sports encouragement community to create an ecosystem encouraging sports-tech research and start-ups.
This CoE proposal is on the development of a Center for Sports Science and Analytics at IIT Madras. Sports as a field has undergone significant changes with increasing adoption of technology cross-cutting all aspects of sports such as:
  • Player performance analysis and improvement.
  • Team performance analysis and improvement.
  • Rule enforcement.
  • Sports administration.
  • Fan engagement.
  • Human endurance and limit.
  • Safety.
  • Sales, marketing and advertising.
  • Betting and its influence on sports.

A list of project areas:

1. First principles modelling:
  • Develop a fluid mechanics model to calculate spinning ball trajectory
  • Develop a model for bounce of a ball on a general surface to characterize pitch performance.
  • Develop an experimental apparatus in IIT Madras’ sports facilities to accurately measure the spatiotemporal ball flight in football, tennis and cricket. Both visual and IoT based measurements of ball flight shall be made for establishing ground truth.
  • Validate computer vision and image processing models against ground truth data.
  • Validate the fluid mechanics model against the experimental measurements.
2. Data Science:
  • Develop interpretable models for sports data. This is important for both fan engagement as well as player performance improvement.
  • Develop Monte Carlo models of sports performance to understand the minimal parameter set that has a strong bearing on the end result.
  • Develop network-based models of sports performance.
  • Develop hybrid models, combining data science and first principles models. This class of models are important to developing explainable models.
  • Develop a model to propagate uncertainty through both physics based, Monte Carlo as well as data based models.
  • What can sport betting markets teach us about factors determining team performance?
  • Prediction of extreme events in a game
  • Player, State and Action evaluation through Reinforcement Learning
3. Internet of Things (IoT):
  • Develop a set of smart sports equipment using implantable sensors and IoT devices, which are capable of generating data streams during a game.
  • Player position data using beacons coupled with visual imaging to map out a rich data stream of a football or tennis match.
  • Shot mechanics data from tennis and cricket shall be analyzed from textile implant sensors
  • Computer Vision in Sports
4. Data Repository:

Another under-served need in sports analytics is the collection and curation of datasets for multiple sports that are relevant and reproducible. For sure, many organizations are likely to have data that is collected on-field and/or during training. However, this data hardly ever finds its way into the public domain due to many reasons such as competitive pressures, sensitive nature of the data and so on. As a result, while there are algorithms that are published and papers presented in conferences, the research can never be reproduced and objectively evaluated as the underlying data is not available.

The proposed center will generate a large repository of highly curated data in multiple sports that can then form the benchmark for comparing algorithms in an “apples-to-apples” fashion and also in further development of the core technologies that are pursued.

Expected deliverables of the research

  • Publications and Visible output:
    • High impact publications and top notch conference presentations
    • Prototypes, technologies and start-ups
  • Manpower development:
    • Minor course and IDDD programs:
    • Associate Faculty from other institutes
    • Outreach and capacity building
    • Industrial collaboration

      Current status


International Collaborations

  • The Center is being jointly in partnership with Northwestern University which is one of the strongest sports science groups in the world.
  • Two Co-PIs of the proposal are faculty at Universitat Rovira I Virgili, Tarragona, Spain
  • A collaborative project on experimentation in sports is currently underway with faculty at Massachusetts Institute of Technology.

International Education Programs

  • The Centre envisages joint degree programs between IITM and NU in this field leveraging academic programs that are already in place in NU in the field of sports analytics.
  • Two international workshops and one Showcase Colloquium is planned to be conducted with quality speakers.

Industrial Collaborators

  • Industrial Collaborators who have already expressed support:
    • IPL Team-Royal Challengers Bangalore
    • Tamil Nadu Olympic Association
    • Aspire Tennis Academy- Aspire boasts of most of the top professional players in India as users of its services.
    • ESPN

      Societal impact

Sports, especially Cricket in India carries the aspirations of 1.3 billion people. The social impact of this center is natural to the very purpose of the center - to bring a scientific paradigm to coaching and analysing sport, thereby improving outcomes. While we are initially focused on four sports, it is our desire to impact the outcomes in the Olympics. We have initiated a partnership with Olympic Gold Quest, an organization in the space of impacting Olympic outcomes in India.

The heady mix of sports and technology areas that are in the public radar (AI, IOT) can inspire K-12 students to get exposed to the STEM areas. The Center will catalyze this through regular outreach programs.

Activities related to “training to promote rural sports, nationally recognised sports, paralympic sports and olympic sports” is permissible under the Corporate Social Responsibility mandate of the Companies Act. Several start-ups that are likely to emerge from the Center could be funded initially through CSR grants. It is envisaged that CSR will form a significant source of support to sustain the Center’s activities, once it has established its credibility as a serious player in this space.

The center, through its AI/ML driven gamified activities will weave itself into the fabric of sporting growth in India. There is no entity that is ready to do this currently in India. We feel that the center will spin out a whole ecosystem of start-ups that will leverage technology developed in the Center for translating into products and games that various sports can use and benefit the country. A primary social objective of the center is to therefore sow the seeds of creating such an ecosystem in India.

Sustenance Statement

IIT Madras, with the RBC-DSAI, has a culture of translating high quality analytics research in India. Some of the Center faculty members have had funded research projects with ESPN, which has agreed to explore future opportunities as well. In addition, we have already had interest expressed from Royal Challengers Bangalore (RCB) to work with the Center.

The Center will develop a consortium model to onboard industry interest. This will allow all sports corporate entities to gain visibility of the research in the Center at a non-compete level. Subsequently, it is conceivable that the corporate partners would develop IP-guarded relationships with the Center faculty through sponsored consultancy projects.

The Center will position itself to attract CSR funds from a wide variety of corporate organizations, which has already been enabled legally. Therefore, sustainability plan will involve some funds secured from CSR which will continue to fund the translational aspects. In addition, the prospect of converting this Center into a named CoE with donor funds shall be explored. The Center will own equipment for gathering data from sports videos and other data. This equipment will be used by various sporting organizations, but operated by Center personnel for gathering high resolution spatiotemporal data. This data will be of value to the sporting clubs and therefore, they will pay for gathering the data. This will form one source of revenue for supporting Center equipment. Besides, the Center equipment will also be used for research.

Technical/ Scientific Progress

New works done in the project

Sl NoTitle of the projectProfessorForeign CollaborationIndustrial CollaborationName of the student AffiliationProgress
1 Studying correlations between individual and team performance in cricket (Kano Model)Prof Nandan SudarsanamProf.Noshir Contractor, Professor, Kellog's School of Management,NW UniversityIshan Sunil NaryaniDual degree1. Explored ball by ball data for IPL matches from all seasons.
2. Built a model using ‘weighted runs’ for player performance vs. net run rate for team performance and made reasonable observations
3. Built a ball by ball and over by over win probability predictor - way forward for a more sophisticated model.
4. Incorporated ball by ball probability based credit assignment into the current model.
5. Devised a new probability based team measure. Incorporated this measure into our model.
6. Propose to work on prescriptive analysis
2Evaluation of Team centric Performance measure of an Individual in Cricket- Quantifying Shane Battier EffectProf Nandan SudarsanamProf.Noshir Contractor, Professor, Kellog's School of Management,NW UniversitySriram RMS Dataset has been procured. Normalization methodology has been set and Sample credits were assigned for a few sets of matches. The resulting credits were also analyzed for each player. The credits for the players are being computed for subsequent matches. Further scope of Work has been discussed with Prof.Noshir and Prof. Nandan and currently, a regression model with the credits assigned to each player is being built up
3Framework to predict ball by ball match information from scorecardProf Raghunathan RengaswamyRCBArunprakash,Aziz Murtuza Kanchanwala Dual degree1) Forecaster - I have implemented two variants of the forecaster. The first one predicts the end of powerplay scores for both innings of a T20 match whereas the second one is a combined resource allocation and machine learning approach to predicting cricket scores. Need to refactor the codebase as well as the paper before I can publish it.
2) Smart Stats - Implementation of statistical metrics which are corrected for the match context to provide an unbiased estimate of a player's (team's) performance. I have started gathering scholarly articles for this one. I Will start the implementation once the other ones are published.
4Game theory centric auction model for IPLProf Raghunathan RengaswamyArneshkumar,UjjalDual degree1. Identified the ideal batting and bowling role of a player.
2. Contribution of every player when the team wins
3. Finding players who can build partnerships, while batting
5FSR Pressure Mat for vertical jumpDr Ranganathan Srinivasan Dr Bala Natarajan, KSU IIS Bellary KarthikeyanProject associatePrototype under construction
6Wearables in shoe sole for x,y,z force measurementDr Ranganathan SrinivasanDr Bala Natarajan, KSUIIS BellaryKarthikeyanProject associate Under study
7IoT applications in combat sports (Boxing, Wrestling and Judo).Prof Babji Srinivasan/ Dr Ranganathan SrinivasanDr Bala Natarajan, KSUIIS BellarySaravananPhDProblems definition with the help of IIS
8Advanced analytics for boxing using deep learningProf Babji Srinivasan/Dr.Ranganathan SrinivasanProf Ravi Hedge, IIT GandhinagarIIS BellaryTBDTBDProposal acceptance with IIS Bellary
9Video based characterising the bounce of a spinning ballProf.Rajagopalan Prof Mahesh Panchagnula AakanshaPhDWe have been able to estimate rpms for a spinning ball undergoing 1D translation and rotation. Presently, we're working on moving into an outdoors setting and estimating rpms for a ball undergoing simultaneous 2D translation and rotation.
103D geometry of a sport from VideoProf Rajagopalan Prof Mahesh Panchagnula Asishkumar PhDI am working on the camera triangulation part with the idea to get the 3D location of a cricket ball in the 3D plane (Our focus is cricket at the moment). We are performing our experiments in indoor as well as outdoor environments (Sanmar cricket ground)
11 Experimental Investigation of the Bounce of a Spinning BallProf Mahesh PanchagnulaAvinash Gupta Navaneeth KrishnanMS
I am at the data generation stage where we record and study the different kinds of motions a ball can have with the help of Computer Vision group at Electrical Engineering at IITM. I take care of the experimental setup and the data generation process.
12Spinning and Bouncing of Sports BallsProf Mahesh PanchagnulaNavaneeth KrishnanPhDCurrently working on the CFD simulation of rotating (Spinning) tennis ball using incompressible single phase solver of OpenFOAM. Geometry is created using SALOME and meshes are done using snappyHexMesh utility of OpenFOAM. Simulations are going on by varying three parametres (Reynolds numbers, angles and non-dimensional spin factors). The results will be compared with the flow around a sphere which has the same size of the tennis ball and analyse the effect of seam on the aerodynamic forces.
13 Aerodynamics of sports ballsProf Mahesh Panchagnula Pasunuru Sai VineethMSWorking on quantifying the swing of a cricket ball
14Sports Analytics CourseProf Mahesh Panchagnula, Prof Raghunathan R, Prof Rajagopalan A N, Prof Nandan Sudarsanam, Prof Babji Srinivasan, Dr Ranganathan SrinivasanRCSYet to be identifiedProject AssociateMoU stage
Infrastructure Development
  1. Purchase of Clusters, High speed cameras and Servers are in progress
  2. Sports Science Club has been started and regular meetings have been conducted. This initiative as inter-club will be managed by the CFI. Nearly 50 students are actively participating in this club. Problem statements will be shared to the students of the club.
Workshops, Papers, Webinars, Media coverage etc

IRIS Webinar was conducted on 22 July 2021. Prof Mahesh Panchgnula, Prof Raghunathan Rengaswamy, Prof A N Rajagopalan and Prof Nandan Sudarsanam gave away lectures. Title was Sports Science Analytics – AI and Data Science.


International Collaboration, Visits planned for PIs and Co PIs
  1. MoU is in progress with Kansa University, KS with Dr. Bala Natarajan Clair N. Palmer and Sara M. Palmer Professor, Steve Hsu Keystone Research Faculty Scholar Director, CPSWin group Dept. of Electrical and Computer Engineering Kansas State University, Manhattan, KS

  2. International faculty visit and collaboration with Prof Noshir Contractor, He visited IITM on Dec 7-8, 2021. Dr. Noshir S Contractor, Jane S. & William J. White Professor of Behavioral Sciences, Northwestern University President-Elect, International Communication Association


Industrial Engagement

  • IIS – Prof. Babji Srinivasan & Dr Ranganathan Srinivasan along with post graduate students visited IIS, Bellary on 8-9 Dec 2021. Prof Ravi Hegde, Professor of IIT Gandhinagar, also joined the IIS Visit. IIS Shared their problem statements with our team. Now our sports science team have been working on it. We will be having a long term future collaboration with them and benefit mutually.
  • Royal Challengers Bangalore – We have initiated MoU with RCB, Bangalore. The following criteria will be.
Carried out in the collaboration.
  1. Development of course material to go on the RCB Innovation Labs platform. These courses will vary in size from 2 hours to 20 hours and be on topics that are relevant to sports in general - sports analytics etc.
  2. R&D to develop a data analytics tool to provide insights from the sensor data streams on the athlete management system. This tool will be developed by IITM using data provided by RCB.
  3. New sensor development: New sensor technologies developed by IITM will be piloted by RCB on their platforms. Rajesh V Menon, VP & Head RCB, Royal Challengers Sports Pvt Ltd has promptly agreed to have MOU with IITM.

University Engagement

  1. MoU is in progress with Kansa University, KS with Dr. Bala Natarajan Clair N. Palmer and Sara M. Palmer Professor, Steve Hsu Keystone Research Faculty Scholar Director, CPSWin group Dept. of Electrical and Computer Engineering Kansas State University, Manhattan, KS
  2. Prof Ravi Hegde, Electrical Engineering, IIT Gandhinagar


Relevant Updates: