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SAW2024 Program ​
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Thursday 23/5/2024
SAW2024 Day 1
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14:00-14:10 SAW2024 Opening by Ioannis Ntzoufras
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Session 1:
14:10-15:00 Alex Krumer, Molde University College, Norway
Ask not what economics can do for sports - ask what sports can do for economics
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15:00-15:25 Florian Felice, University of Luxembourg
Score More with Data: Unveiling the Coach's Analytics Advantage - an illustration with handball
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15:25-15:50 Dimitris Karlis, AUEB, Greece
Statistical Models for handball
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15:50-16:15 Tim Swartz, Simon Fraser University, Canada
Tactical Problems in Football using Tracking Data and Causal Methods
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16:15-16:40 BREAK 1
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Session 2:
16:40-17:05 Nina Deliu, MEMOTEF, Sapienza University, Italy
A Multivariate Copula-based Conformal Bayesian Framework for Doping Detection
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17:05-17:30 Dimitra Eleftheriou, Leiden University, The Netherlands
Doping control analysis in athletes’ steroid profile: a multivariate Bayesian learning approach
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17:30-17:55 Laurentiu Hinoveanu, University of Kent, UK
Athletic Performance Trajectories for middle-distance running Inferred via a Bayesian Hierarchical Model
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17:55-18:20 Jethro Ronald Lee, Northeastern University, US
Analysis of Success Probabilities in Field Hockey with Bivariate Binomial Regression in Machine Learning
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18:20-18:45 BREAK 2
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Session 3:
18:45-19:10 Keisuke Fujii, Nagoya University, Japan
Estimation of counterfactual outcomes in basketball games with trajectory prediction
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19:10-19:35 Gerçek Budak, Ankara Yıldırım Beyazıt University, Turkey
A Game Theoretical Mathematical Modelling for the Best Team Formation During the Basketball Match
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19:35-20:00 Rouven Michels , Bielefeld University, Germany
Exploring team-level momentum effects: a study of offensive and defensive performances in the NBA
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20:00-20:25 Ambra Macis, University of Brescia, Italy
Injuries in NBA and player’s vulnerability
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20:25-20:50 Ioannis Ntzoufras, Argyro Damoulaki, AUEB, Greece
Lasso Multinomial Indicators for in-play Basketball Data
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Friday 24/5/2024
SAW2024 Day 2
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Session 1:
12:00-12:25 Mirko Carlesso, University of Brescia, Italy
Measuring shooting performance in the basketball court with spatial statistics methods. A structured case study with data of the Italian Basketball First League.
12:25-12:50 Gabriele Giudici, University of Brescia, Italy
Computer Vision in Basketball
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12:50-13:15 Michail Tsagris, University of Crete, Greece
Predicting full retirement attainment of NBA players
13:15-13:40 Tianxiao Guo, Beijing Sport University, China
Exploring the relationship between basketball substitution and collective performance using complex network
13:40-14:30 LUNCH BREAK
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Session 2:
14:30-14:55 Dimitris Dallas, AUEB, Greece
A basketball description of (almost) everything
14:55-15:20 Kazuhiro Yamada, Nagoya University, Japan
Impact of player combinations on scoring efficiency: using shooting style clustering based on Wasserstein distance of dynamic features
15:20-15:45 Michalis Nikolouzos, AUEB, Greece
Exploring New Frontiers: Greek Research in Real-Time Performance Monitoring for Athletes
15:45-16:10 BREAK 2
Session 3:
16:10-16:35 Robert Bajons, Vienna University of Economics and Business, Austria
PEP: Evaluating tackles in American football
16:35-17:00 Roberto Macrì Demartino, University of Padova, Italy
The use of Bradley-Terry comparisons in statistical and machine learning models to predict football results
17:00-17:25 Steffen Lang, Technical University of Munich, Germany
In-play event prediction using machine learning and spatiotemporal data in association football
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*All times refer to the Greek time-zone (GMT+3)
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Organized by
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Ioannis Ntzoufras
Dimitris Karlis
Sotiris Drikos
Administrative Assistant
Argyro Damoulaki
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