We are glad to announce that the 2018 Applied Bayesian Statistics Summer School (15th

edition) will be held in the magnificent Villa del Grumello, Como (Italy) along the Lake

Como shore.

       BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT

                        4-8 June, 2018

Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics,
Queensland University of Technology, Brisbane, Australia.

Further details are provided below.

Guido Consonni and Fabrizio Ruggeri
ABS18 Directors
Raffaele Argiento
ABS18 Executive Director

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          *            ABS18            *
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        Applied Bayesian Statistics School

BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT

         Villa del Grumello, Como, Italy

         4-8 June, 2018

Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics,
Queensland University of Technology, Brisbane, Australia.

The conference webpage is

>>>>   web.mi.imati.cnr.it/conferences/abs18.html   <<<<

Registration is now open. Please note that the conference
room allows only for a limited number of participants.

The ABS18 Secretariat can be contacted at

        fabrizio@mi.imati.cnr.it

COURSE OUTLINE

The aim of this course is to increase students' ability to develop Bayesian models and

computational solutions for real problems in the world of sport. A case study based teaching

approach will be taken for the course. Each day, students will be presented with one or two

problems posed by Sports Institutes regarding aspects of athlete training for world games.

Through participatory problem solving, the students will be challenged to learn about

theory, methods and applications of a range of Bayesian models including mixtures, spatio-

temporal models, hidden Markov models and experimental design, and computational approaches

including Markov chain Monte Carlo and Approximate Bayesian Computation. This hands-on

course pays equivalent attention to theory and application, foundation and frontiers in

Bayesian modelling and analysis. While the focus of the case studies is on sport, both

sporting novices and lovers of sports are welcome, noting that the learning obtained in the

course will be widely applicable to many other areas.

COURSE SCHEDULE

Day 1: Lectures on introduction to Bayesian modelling and computation. Presentation of

Problem 1: ranking and benchmarking athletes. Discussion and implementation of potential

Bayesian hierarchical models and computational solutions. Communication of results.

Day 2: Lectures on foundational Bayesian theory. Presentation of Problem 3: modelling

swimmers' effective work per stroke. Discussion and implementation of potential Bayesian

high dimensional regression models and computational solutions. Communication of results.

Presentation of Problem 4: modelling cyclists' wearable data. Discussion and implementation

of potential (marked) time series models and computational solutions. Communication of

results.

Day 3: Lectures on foundational Bayesian computation. Presentation of Problem 5: optimising

athletes' resilience. Discussion and implementation of potential Bayesian mixture models to

relate performance, fatigue and recovery. Communication of results.

Day 4: Lectures on foundational Bayesian computation and frontier Bayesian theory.

Presentation of Problem 6: optimal sampling strategies. Discussion and implementation of

potential Bayesian experimental design methods for acquiring data from athletes.

Presentation of Problem 7: using video data to compare planned and set play in team sports.

Discussion and implementation of potential Bayesian spatio-temporal models. Communication of

results.

Day 5: Lectures on frontier Bayesian computation. Finalisation of problems 1-7. Extensions.

Concluding remarks.

PRACTICAL INFORMATION

The school will replicate the successful format of the previous years, and will feature

lectures and practical sessions (run by a junior researcher), as well as participants'

talks. It will start on Monday after lunch and end on Friday before lunch; Wednesday

afternoon is free. Accommodation is available either at the Villa guesthouse or in downtown

hotels (info will appear soon on the website). Como can be easily reached by train from

Milan and its airports. More details are available on the website.