{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,11]],"date-time":"2026-10-11T00:48:35Z","timestamp":1791679715089,"version":"4.3.4"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T00:00:00Z","timestamp":1791590400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T00:00:00Z","timestamp":1791590400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Gambl Stud"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Previous research on gambling loss patterns has mainly relied on self-reported data, which has some inherent biases (e.g., low accuracy). While some studies are based on large samples of horse bettors, few have examined how losses are distributed among them. The aim of this exploratory study was to examine the concentration of losses among gamblers playing horse betting games. Norsk Rikstoto, the Norwegian horse betting monopoly, provided account-based gambling data for all customers who bet with them between 2021 and 2023, covering 13 horse betting formats. To describe the shape of the loss distribution for each format, we calculated the mean-to-median loss ratio, the Gini coefficient, and the shares of total losses attributable to the top 1%, 5%, 10%, and 20% of bettors. Across all 13 betting formats combined, the mean-to-median loss ratio was 7.06 (min: 4.88, max: 11.53) and the Gini coefficient was 0.81 (min: 0.77, max: 0.87). Overall, the top 1% of bettors accounted for almost one-quarter of total losses (24.7%), while the top 20% accounted for 86.0%. This imbalance was most pronounced for single-race games (top 1%: 26.2\u201339.5%; top 20%: 87.3\u201391.5%) compared with the multi-race V-games (top 1%: 19.9\u201323.9%; top 20%: 81.0\u201387.5%). In summary, losses in horse betting are heavily concentrated among a relatively small share of bettors. The degree of inequality differs across game types, suggesting that product characteristics may play a role in shaping who loses and by how much.<\/jats:p>","DOI":"10.1007\/s10899-026-10568-2","type":"journal-article","created":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T21:32:30Z","timestamp":1791667950000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Distribution of Losses Among Horse Race Bettors: An Analysis of Account-Based Player Tracking Data"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5766-8995","authenticated-orcid":false,"given":"Kerem","family":"Buzcular","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8652-9367","authenticated-orcid":false,"given":"Ingeborg","family":"Rossow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5831-0840","authenticated-orcid":false,"given":"St\u00e5le","family":"Pallesen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1781-4153","authenticated-orcid":false,"given":"Tony","family":"Leino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,10]]},"reference":[{"issue":"3","key":"10568_CR1","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1007\/s10899-016-9648-0","volume":"33","author":"M Auer","year":"2017","unstructured":"Auer, M., & Griffiths, M. D. (2017). Self-reported losses versus actual losses in online gambling: An empirical study. Journal of Gambling Studies, 33(3), 795\u2013806. https:\/\/doi.org\/10.1007\/s10899-016-9648-0","journal-title":"Journal of Gambling Studies"},{"issue":"2","key":"10568_CR2","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/s11469-020-00442-6","volume":"21","author":"M Auer","year":"2023","unstructured":"Auer, M., & Griffiths, M. D. (2023). Reasons for gambling and problem gambling among Norwegian horse bettors: A real-world study utilizing combining survey data and behavioral player data. International Journal of Mental Health and Addiction, 21(2), 740\u2013755. https:\/\/doi.org\/10.1007\/s11469-020-00442-6","journal-title":"International Journal of Mental Health and Addiction"},{"key":"10568_CR3","doi-asserted-by":"publisher","first-page":"106864","DOI":"10.1016\/j.actpsy.2026.106864","volume":"266","author":"M Auer","year":"2026","unstructured":"Auer, M., & Griffiths, M. D. (2026). Differences in online gambling expenditure between players from Germany, Spain, Netherlands, Great Britain, US and Canada: A largescale online player tracking study. Acta Psychologica, 266, 106864. https:\/\/doi.org\/10.1016\/j.actpsy.2026.106864","journal-title":"Acta Psychologica"},{"issue":"3","key":"10568_CR4","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1037\/a0036428","volume":"26","author":"J Braverman","year":"2014","unstructured":"Braverman, J., Tom, M. A., & Shaffer, H. J. (2014). Accuracy of self-reported versus actual online gambling wins and losses. Psychological Assessment, 26(3), 865\u2013877. https:\/\/doi.org\/10.1037\/a0036428","journal-title":"Psychological Assessment"},{"key":"10568_CR5","doi-asserted-by":"publisher","unstructured":"Catalano, M. T., Leise, T. L., & Pfaff, T. J. (2009). Measuring resource inequality: The Gini coefficient. 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Informed consent was not provided as all analyses were based on player account data that the provider, Rikstoto, can make available for research purposes.","order":1,"name":"Ethics","label":"Ethical Approval","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Informed consent was not required as the analyses utilized de-identified player account data.","order":2,"name":"Ethics","label":"Informed Consent","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":3,"name":"Ethics","label":"Competing Interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}