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Annals of Operations Research, Volume 325
Volume 325, Number 1, June 2023
- Pierpaolo D'Urso, Livia De Giovanni, Tim B. Swartz:
Editorial: Big data and data science in sport. 1-7 - Pierpaolo D'Urso, Livia De Giovanni, Vincenzina Vitale:
A robust method for clustering football players with mixed attributes. 9-36 - Maurizio Carpita, Paola Pasca, Serena Arima, Enrico Ciavolino:
Clustering of variables methods and measurement models for soccer players' performances. 37-56 - Gian Paolo Clemente, Alessandra Cornaro:
Community detection in attributed networks for global transfer market. 57-83 - Valerio Ficcadenti, Roy Cerqueti, Ciro Hosseini Varde'i:
A rank-size approach to analyse soccer competitions and teams: the case of the Italian football league "Serie A". 85-113 - Raffaele Mattera:
Forecasting binary outcomes in soccer. 115-134 - Ruud H. Koning, Renske Zijm:
Betting market efficiency and prediction in binary choice models. 135-148 - Llorenç Badiella, Pedro Puig, Carlos Lago-Peñas, Martí Casals:
Influence of Red and Yellow cards on team performance in elite soccer. 149-165 - Marius Ötting, Dimitris Karlis:
Football tracking data: a copula-based hidden Markov model for classification of tactics in football. 167-183 - Adjei Peter Darko, Decui Liang, Yinrunjie Zhang, Agbodah Kobina:
Service quality in football tourism: an evaluation model based on online reviews and data envelopment analysis with linguistic distribution assessments. 185-218 - Antonello D'Ambra, Pietro Amenta:
An extension of correspondence analysis based on the multiple Taguchi's index to evaluate the relationships between three categorical variables graphically: an application to the Italian football championship. 219-244 - Sumit Sarkar, Sooraj Kamath:
Does luck play a role in the determination of the rank positions in football leagues? A study of Europe's 'big five'. 245-260 - Praveen Puram, Soumya Roy, Deepak Srivastav, Anand Gurumurthy:
Understanding the effect of contextual factors and decision making on team performance in Twenty20 cricket: an interpretable machine learning approach. 261-288 - Apurva Jha, Arpan Kumar Kar, Agam Gupta:
Optimization of team selection in fantasy cricket: a hybrid approach using recursive feature elimination and genetic algorithm. 289-317 - Praveen Ranjan Srivastava, Prajwal Eachempati, Ajay Kumar, Ashish Kumar Jha, Lalitha Dhamotharan:
Best strategy to win a match: an analytical approach using hybrid machine learning-clustering-association rule framework. 319-361 - Alessandro Chessa, Pierpaolo D'Urso, Livia De Giovanni, Vincenzina Vitale, Alfonso Gebbia:
Complex networks for community detection of basketball players. 363-389 - Luca De Angelis, J. James Reade:
Home advantage and mispricing in indoor sports' ghost games: the case of European basketball. 391-418 - Pierpaolo D'Urso, Livia De Giovanni, Vincenzina Vitale:
A Bayesian network to analyse basketball players' performances: a multivariate copula-based approach. 419-440 - Rodolfo Metulini, Giorgio Gnecco:
Measuring players' importance in basketball using the generalized Shapley value. 441-465 - Jiangang Wang, Fanghong Liu:
Will more skills become a burden? The effect of positional ambiguity on player and team performance. 467-493 - Paola Zuccolotto, Marco Sandri, Marica Manisera:
Spatial performance analysis in basketball with CART, random forest and extremely randomized trees. 495-519 - Tullio Facchinetti, Rodolfo Metulini, Paola Zuccolotto:
Filtering active moments in basketball games using data from players tracking systems. 521-538 - David Van Bulck, Arthur Vande Weghe, Dries R. Goossens:
Result-based talent identification in road cycling: discovering the next Eddy Merckx. 539-556 - Bram Janssens, Matthias Bogaert, Mathijs Maton:
Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents. 557-588 - Fabian Clemens Weigend, David C. Clarke, Oliver Obst, Jason Siegler:
A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise. 589-613 - Alberto Arcagni, Vincenzo Candila, Rosanna Grassi:
A new model for predicting the winner in tennis based on the eigenvector centrality. 615-632 - Peter Tea, Tim B. Swartz:
The analysis of serve decisions in tennis using Bayesian hierarchical models. 633-648 - Daniel Goller:
Analysing a built-in advantage in asymmetric darts contests using causal machine learning. 649-679 - Michael Schuckers, Michael Lopez, Brian Macdonald:
Estimation of player aging curves using regression and imputation. 681-699 - Maria Iannario, Rosaria Romano, Domenico Vistocco:
Dyadic analysis for multi-block data in sport surveys analytics. 701-714 - Yazan F. Roumani:
Sports analytics in the NFL: classifying the winner of the superbowl. 715-730 - Benjamin Williams, Will Palmquist, Ryan Elmore:
Simulation-based decision making in the NFL using NFLSimulatoR. 731-742 - Haoyu Liu, Kim Hua Tan, Xianfeng Wu:
Who's watching? Classifying sports viewers on social live streaming services. 743-765
Volume 325, Number 2, June 2023
- Salvatore Corrente, Yves De Smet, Michalis Doumpos, Salvatore Greco, Constantin Zopounidis:
Classification, sorting and clustering methods based on multiple criteria: recent trends. 767-770 - Sarah Ben Amor, Fateh Belaid, Ramzi Benkraiem, Boumediene Ramdani, Khaled Guesmi:
Multi-criteria classification, sorting, and clustering: a bibliometric review and research agenda. 771-793 - Pegdwende Minoungou, Vincent Mousseau, Wassila Ouerdane, Paolo Scotton:
A MIP-based approach to learn MR-Sort models with single-peaked preferences. 795-817 - Eduardo Fernández, José Rui Figueira, Jorge Navarro:
A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes. 819-843 - Oussama Raboun, Eric Chojnacki, Alexis Tsoukiàs:
Dynamic-R: a "challenge-free" method for rating problem statements. 845-873 - Jindong Qin, Yingying Liang, Luis Martínez-López, Alessio Ishizaka, Witold Pedrycz:
ORESTE-SORT: a novel multiple criteria sorting method for sorting port group competitiveness. 875-909 - Zhen Zhang, Zhuolin Li:
Consensus-based TOPSIS-Sort-B for multi-criteria sorting in the context of group decision-making. 911-938 - Saeideh Babashahi, Paul Hansen, Ronald J. A. P. Peeters:
External validity of multi-criteria preference data obtained from non-random sampling: measuring cohesiveness within and between groups. 939-949 - Bice Cavallo, Alessio Ishizaka:
Evaluating scales for pairwise comparisons. 951-965 - Francesco Ciardiello, Andrea Genovese:
A comparison between TOPSIS and SAW methods. 967-994 - Che Xu, Wenjun Chang, Weiyong Liu:
Data-driven decision model based on local two-stage weighted ensemble learning. 995-1028 - Paritosh Jha, Marco Cucculelli:
Enhancing the predictive performance of ensemble models through novel multi-objective strategies: evidence from credit risk and business model innovation survey data. 1029-1047 - Maria Franca Norese, Diana Rolando, Rocco Curto:
DIKEDOC: a multicriteria methodology to organise and communicate knowledge. 1049-1082 - Bruno M. B. Pinto, Fernando A. F. Ferreira, Ronald W. Spahr, Mark A. Sunderman, Leandro Ferreira Pereira:
Analyzing causes of urban blight using cognitive mapping and DEMATEL. 1083-1110 - Hongtao Ren, Wenji Zhou, Marek Makowski, Shaohui Zhang, Yadong Yu, Tieju Ma:
A multi-criteria decision support model for adopting energy efficiency technologies in the iron and steel industry. 1111-1132 - Esther Jose, Puneet Agarwal, Jun Zhuang, Jose Swaminathan:
A multi-criteria decision making approach to evaluating the performance of Indian railway zones. 1133-1168 - Ali Tlili, Oumaima Khaled, Vincent Mousseau, Wassila Ouerdane:
Interactive portfolio selection involving multicriteria sorting models. 1169-1195 - Pranith Kumar Roy, Krishnendu Shaw, Alessio Ishizaka:
Developing an integrated fuzzy credit rating system for SMEs using fuzzy-BWM and fuzzy-TOPSIS-Sort-C. 1197-1229 - Chrysovalantis Gaganis, Panagiota Papadimitri, Fotios Pasiouras, Menelaos Tasiou:
Social traits and credit card default: a two-stage prediction framework. 1231-1253 - Yoontae Hwang, Yongjae Lee, Frank J. Fabozzi:
Identifying household finance heterogeneity via deep clustering. 1255-1289 - Philippe du Jardin:
Designing topological data to forecast bankruptcy using convolutional neural networks. 1291-1332
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