{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T08:28:59Z","timestamp":1766305739782,"version":"3.48.0"},"reference-count":29,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T00:00:00Z","timestamp":1758585600000},"content-version":"vor","delay-in-days":265,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Procedia Computer Science"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1016\/j.procs.2025.09.309","type":"journal-article","created":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T22:13:48Z","timestamp":1762467228000},"page":"1886-1895","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Dynamic Descriptive Analytics in Football: A Case Study with Retrieval-Augmented Generation for Structured Data"],"prefix":"10.1016","volume":"270","author":[{"given":"Ioannis","family":"Tzikas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samuel","family":"Didovic","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Felix","family":"Gerschner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manfred","family":"R\u00f6ssle","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Theissler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Klaiber","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.procs.2025.09.309_bib1","unstructured":"Akram Sawiras, K., 2024. Evaluation and development of innovative nlp techniques for query-focused summarization using retrieval augmented generation (rag) and a small language model (slm) in educational settings. ICT 66."},{"key":"10.1016\/j.procs.2025.09.309_bib2","doi-asserted-by":"crossref","first-page":"62160","DOI":"10.52202\/079017-1986","article-title":"Make your llm fully utilize the context","volume":"37","author":"An","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.procs.2025.09.309_bib3","unstructured":"Caron, M., M\u00fcller, O., 2023. Tacticalgpt: uncovering the potential of llms for predicting tactical decisions in professional football, in: Stats-Bomb Conference, pp. 1\u201311."},{"key":"10.1016\/j.procs.2025.09.309_bib4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2071389.2071390","article-title":"A survey of automatic query expansion in information retrieval","volume":"44","author":"Carpineto","year":"2012","journal-title":"Acm Computing Surveys (CSUR)"},{"key":"10.1016\/j.procs.2025.09.309_bib5","unstructured":"Celikyilmaz, A., Clark, E., Gao, J., 2020. Evaluation of text generation: A survey. arXiv preprint arXiv:2006.14799."},{"key":"10.1016\/j.procs.2025.09.309_bib6","doi-asserted-by":"crossref","unstructured":"Douze, M., Guzhva, A., Deng, C., Johnson, J., Szilvasy, G., Mazar\u00e9, P.E., Lomeli, M., Hosseini, L., J\u00e9gou, H., 2024. The faiss library. arXiv preprint arXiv:2401.08281.","DOI":"10.1109\/TBDATA.2025.3618474"},{"key":"10.1016\/j.procs.2025.09.309_bib7","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1007\/s10479-022-04558-x","article-title":"A robust method for clustering football players with mixed attributes","volume":"325","author":"D\u2019Urso","year":"2023","journal-title":"Annals of Operations Research"},{"key":"10.1016\/j.procs.2025.09.309_bib8","first-page":"121","article-title":"Query expansion","volume":"31","author":"Efthimiadis","year":"1996","journal-title":"Annual review of information science and technology (ARIST)"},{"year":"2024","series-title":"SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset","author":"Gautam","key":"10.1016\/j.procs.2025.09.309_bib9"},{"key":"10.1016\/j.procs.2025.09.309_bib10","doi-asserted-by":"crossref","unstructured":"Giancola, S., Amine, M., Dghaily, T., Ghanem, B., 2018. Soccernet: A scalable dataset for action spotting in soccer videos, in: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp. 1711\u20131721.","DOI":"10.1109\/CVPRW.2018.00223"},{"key":"10.1016\/j.procs.2025.09.309_bib11","doi-asserted-by":"crossref","unstructured":"Haroutunian, L., Li, Z., Galescu, L., Cohen, P., Tumuluri, R., Hafari, G., 2023. Reranking for natural language generation from logical forms: A study based on large language models. arXiv preprint arXiv:2309.12294.","DOI":"10.18653\/v1\/2023.ijcnlp-main.69"},{"key":"10.1016\/j.procs.2025.09.309_bib12","doi-asserted-by":"crossref","unstructured":"Hu, Y., Song, K., Cho, S., Wang, X., Foroosh, H., Yu, D., Liu, F., 2024. Sportsmetrics: Blending text and numerical data to understand information fusion in llms. arXiv preprint arXiv:2402.10979.","DOI":"10.18653\/v1\/2024.acl-long.17"},{"key":"10.1016\/j.procs.2025.09.309_bib13","unstructured":"Jagerman, R., Zhuang, H., Qin, Z., Wang, X., Bendersky, M., 2023. Query expansion by prompting large language models. arXiv preprint arXiv:2305.03653."},{"key":"10.1016\/j.procs.2025.09.309_bib14","doi-asserted-by":"crossref","unstructured":"Kim, Y., Bui, K.H.N., Jung, J.J., 2021. Data-driven exploratory approach on player valuation in football transfer market. Concurrency and Computation: Practice and Experience 33, e5353.","DOI":"10.1002\/cpe.5353"},{"key":"10.1016\/j.procs.2025.09.309_bib15","unstructured":"Leng, Q., Portes, J., Havens, S., Zaharia, M., Carbin, M., 2024. Long context rag performance of large language models. arXiv preprint arXiv:2411.03538."},{"key":"10.1016\/j.procs.2025.09.309_bib16","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1162\/tacl_a_00638","article-title":"Lost in the middle: How language models use long contexts","volume":"12","author":"Liu","year":"2024","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"10.1016\/j.procs.2025.09.309_bib17","doi-asserted-by":"crossref","unstructured":"Muennighoff, N., Tazi, N., Magne, L., Reimers, N., 2022. Mteb: Massive text embedding benchmark. arXiv preprint arXiv:2210.07316.","DOI":"10.18653\/v1\/2023.eacl-main.148"},{"key":"10.1016\/j.procs.2025.09.309_bib18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10586-023-04203-7","article-title":"Foundation and large language models: fundamentals, challenges, opportunities, and social impacts","volume":"27","author":"Myers","year":"2024","journal-title":"Cluster Computing"},{"key":"10.1016\/j.procs.2025.09.309_bib19","series-title":"A review of evaluation metrics in machine learning algorithms, in: Silhavy, R., Silhavy, P. (Eds.), Artificial Intelligence Application in Networks and Systems, Springer International Publishing","first-page":"15","author":"Naidu","year":"2023"},{"key":"10.1016\/j.procs.2025.09.309_bib20","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1038\/s41597-019-0247-7","article-title":"A public data set of spatio-temporal match events in soccer competitions","volume":"6","author":"Pappalardo","year":"2019","journal-title":"Scientific data"},{"key":"10.1016\/j.procs.2025.09.309_bib21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40064-016-3108-2","article-title":"Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science","volume":"5","author":"Rein","year":"2016","journal-title":"SpringerPlus"},{"key":"10.1016\/j.procs.2025.09.309_bib22","series-title":"Querying football matches for event data: Towards using large language models, in: International Sports Analytics Conference and Exhibition","first-page":"216","author":"Schilling","year":"2024"},{"key":"10.1016\/j.procs.2025.09.309_bib23","doi-asserted-by":"crossref","unstructured":"Sepasdar, Z., Gautam, S., Midoglu, C., Riegler, M.A., Halvorsen, P., 2025. Soccer-GraphRAG: Applications of GraphRAG in Soccer, in: Boratto, L., Malitesta, D., Marras, M., Medda, G., Musto, C., Purificato, E. (Eds.), Advances on Graph-Based Approaches in Information Retrieval. volume 2197, pp. 1\u201310.","DOI":"10.1007\/978-3-031-71382-8_1"},{"key":"10.1016\/j.procs.2025.09.309_bib24","doi-asserted-by":"crossref","unstructured":"Strand, A.T., Gautam, S., Midoglu, C., Halvorsen, P., 2024. Soccerrag: Multimodal soccer information retrieval via natural queries. arXiv preprint arXiv:2406.01273.","DOI":"10.1109\/CBMI62980.2024.10859209"},{"key":"10.1016\/j.procs.2025.09.309_bib25","unstructured":"Wang, X., Salmani, M., Omidi, P., Ren, X., Rezagholizadeh, M., Eshaghi, A., 2024a. Beyond the limits: A survey of techniques to extend the context length in large language models. arXiv preprint arXiv:2402.02244."},{"key":"10.1016\/j.procs.2025.09.309_bib26","unstructured":"Wang, Z., Zhang, H., Li, C.L., Eisenschlos, J.M., Perot, V., Wang, Z., Miculicich, L., Fujii, Y., Shang, J., Lee, C.Y., et al., 2024b. Chain-of-table: Evolving tables in the reasoning chain for table understanding. arXiv preprint arXiv:2401.04398."},{"key":"10.1016\/j.procs.2025.09.309_bib27","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume":"35","author":"Wei","year":"2022","journal-title":"Advances in neural information processing systems"},{"key":"10.1016\/j.procs.2025.09.309_bib28","first-page":"1","article-title":"Harnessing the power of llms in practice: A survey on chatgpt and beyond","volume":"18","author":"Yang","year":"2024","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"key":"10.1016\/j.procs.2025.09.309_bib29","unstructured":"Yu, T., Zhang, S., Feng, Y., 2024. Auto-rag: Autonomous retrieval-augmented generation for large language models. arXiv preprint arXiv:2411.19443."}],"container-title":["Procedia Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050925029825?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050925029825?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T08:26:26Z","timestamp":1766305586000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1877050925029825"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":29,"alternative-id":["S1877050925029825"],"URL":"https:\/\/doi.org\/10.1016\/j.procs.2025.09.309","relation":{},"ISSN":["1877-0509"],"issn-type":[{"type":"print","value":"1877-0509"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dynamic Descriptive Analytics in Football: A Case Study with Retrieval-Augmented Generation for Structured Data","name":"articletitle","label":"Article Title"},{"value":"Procedia Computer Science","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.procs.2025.09.309","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}