Skip to main content

What makes Brazilians gamble in bets? Empirical evidence from ANBIMA's investor X-Ray for 2024 and 2025

Published: Feb 9, 2026
Volume: 24
Keywords: Bets Sports betting Financial behavior ANBIMA Investor X-Ray

Authors

Aureliano Angel Bressan
Universidade Federal de Minas Gerais
Daniel Pereira Alves de Abreu
Universidade Federal de Minas Gerais

Abstract

The rise of sports betting platforms in Brazil has raised concerns about their impact on socially and economically vulnerable groups. This study investigates the main factors associated with the propensity and frequency of betting, based on data from ANBIMA's Raio-X do Investidor 2024 and 2025. Using logistic and Random Forest models, we sought to identify how the variables of age, income, financial stress, and digital access influence this behavior. The results reveal that younger individuals with lower incomes and under greater financial stress are more likely to bet and to do so frequently. The economic motivation to gamble was the most relevant predictor in distinguishing between levels of gambling frequency, revealing a distorted perception of betting as a supplement to income. The findings highlight the need for public policies on protection, financial education, and advertising regulation to prevent the worsening of inequalities and the risks associated with this practice.


How to cite

Aureliano Angel Bressan, Daniel Pereira Alves de Abreu. What makes Brazilians gamble in bets? Empirical evidence from ANBIMA's investor X-Ray for 2024 and 2025. Brazilian Review of Finance, v. 24, n. 1, 2026. p. e202602. DOI: 10.12660/rbfin.v24n1.2026.97144.


References

ANBIMA (2024) Raio-X do investidor brasileiro -- ANBIMA. https://www.anbima.com.br/pt_br/especial/raio-x-do-investidor-brasileiro.htm
ANBIMA (2025) Raio-X do investidor brasileiro -- ANBIMA. https://www.anbima.com.br/pt_br/especial/raio-x-do-investidor-brasileiro.htm
Auer, M., Reiestad, S.H. and Griffiths, M.D. (2020) Global limit setting as a responsible gambling tool: What do players think? International Journal of Mental Health and Addiction, 18, 14–26. https://doi.org/10.1007/s11469-018-9892-x
BACEN (2024) Análise técnica sobre o mercado de apostas online no Brasil e o perfil dos apostadores, Estudo especial no. 119, Banco Central do Brasil. https://www.bcb.gov.br/conteudo/relatorioinflacao/EstudosEspeciais/EE119_Analise_tecnica_sobre_o_mercado_de_apostas_online_no_Brasil_e_o_perfil_dos_apostadores.pdf
Baláž, V. (2021) Attitudes towards financial risks and portfolio allocations: Evidence from large-scale surveys. Ekonomický časopis, 69(02), 113–134. https://doi.org/10.31577/ekoncas.2021.02.01
Brasil (1969) Decreto-lei nº 594, de 27 de maio de 1969: Institui a Lotérica Esportiva Federal, Diário Oficial da União.
Brasil (2018) Lei nº 13.756, de 12 de dezembro de 2018: Dispõe sobre o Fundo Nacional de Segurança Pública (FNSP), sobre a destinação do produto da arrecadação das loterias e sobre a promoção comercial e a modalidade lotérica denominadas apostas de quota fixa, Diário Oficial da União.
Brasil (2023) Lei nº 14.790, de 29 de dezembro de 2023: Dispõe sobre a modalidade lotérica denominada apostas de quota fixa; altera as leis nºs 5.768, de 20 de dezembro de 1971, e 13.756, de 12 de dezembro de 2018, e a Medida Provisória nº 2.158-35, de 24 de agosto de 2001; revoga dispositivos do Decreto-Lei nº 204, de 27 de fevereiro de 1967; e dá outras providências, Diário Oficial da União.
Breiman, L. (2001) Random forests. Machine Learning, 45(1), 5–32. https://doi.org/10.1023/A:1010933404324
Cameron, A.C. and Trivedi, P.K. (2005) Microeconometrics: Methods and Applications. Cambridge University Press.
Columb, D. and O'Gara, C. (2018) A national survey of online gambling behaviours. Irish Journal of Psychological Medicine, 35(4), 311–319. https://doi.org/10.1017/ipm.2017.64
Cutler, A., Cutler, D.R. and Stevens, J.R. (2012) Random forests. In Ensemble Machine Learning, Springer, New York, NY, pp. 157–175. https://doi.org/10.1007/978-1-4419-9326-7_5
da Silva, E.C. and da Silva Rezende, P.I. (2024) A regulamentação das apostas esportivas no Brasil: A lei nº. 14.790 de 29 de dezembro de 2023. Revista Ibero-Americana de Humanidades, Ciências e Educação, 10(10), 5552–5565. https://doi.org/10.51891/rease.v10i10.16433
de Oliveira, M.P.M.T., de Castro, J.S., Braga, E.D.O. and Raszeja, B.C. (2022) Gambling disorder: Contributions of the psychodynamic approach to treatment. Psicologia USP, 33. https://doi.org/10.1590/0103-6564e210007
Dellosa, G. and Browne, M. (2024) The influence of age on gambling problems worldwide: A systematic review and meta-analysis of risk among younger, middle-aged, and older adults. Journal of Behavioral Addictions, 13(3), 702–715. https://doi.org/10.1556/2006.2024.00051
Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J. and Wagner, G.G. (2011) Individual risk attitudes: Measurement, determinants, and behavioral consequences. Journal of the European Economic Association, 9(3), 522–550. https://doi.org/10.1111/j.1542-4774.2011.01015.x
Díaz, A., García, J. and Pérez, L. (2023) Gender differences in the propensity to start gambling. Journal of Gambling Studies, 39(4), 1799–1814. https://doi.org/10.1007/s10899-023-10232-z
García-Pérez, A., Krotter, A. and Aonso-Diego, G. (2024) The impact of gambling advertising and marketing on online gambling behavior: An analysis based on Spanish data. Public Health, 234, 170–177. https://doi.org/10.1016/j.puhe.2024.06.025
Greene, W. (2018) Econometric Analysis, 8th ed., Macmillan; Pearson Education Limited.
Instituto Locomotiva (2024) Bets: 86% das pessoas que apostam têm dívida e 64% estão negativadas na Serasa, diz pesquisa. https://ilocomotiva.com.br/clipping/bets-86-das-pessoas-que-apostam-tem-divida-e-64-estao-negativadas-na-serasa-diz-pesquisa/
James, G., Witten, D., Hastie, T. and Tibshirani, R. (2013) An Introduction to Statistical Learning: With Applications in R. Vol. 103, Springer, New York. https://doi.org/10.1007/978-1-4614-7138-7
Kuhn, M. and Johnson, K. (2013) Applied Predictive Modeling. Vol. 26, Springer, New York. https://doi.org/10.1007/978-1-4614-6849-3
Kuhn, M. and Johnson, K. (2019) Feature engineering and selection: A practical approach for predictive models. Chapman and Hall/CRC Press, Boca Raton, FL. https://doi.org/10.1201/9781315108230
Lakew, N., Jonsson, J. and Lindner, P. (2024) Towards an active role of financial institutions in preventing problem gambling: A proposed conceptual framework and taxonomy of financial wellbeing indicators. Journal of Gambling Studies, pp. 1–30. https://doi.org/10.1007/s10899-024-10312-8
Landreat, M.G., Boudet, I.C., Perrot, B., Romo, L., Codina, I., Magalon, D. and Grall-Bronnec, M. (2020) Problem and non-problem gamblers: A cross-sectional clustering study by gambling characteristics. BMJ Open, 10(2), e030424. https://doi.org/10.1136/bmjopen-2019-030424
Lelonek-Kuleta, B., Bartczuk, R.P., Wiechetek, M., Chwaszcz, J. and Niewiadomska, I. (2020) The prevalence of E-gambling and of problem E-gambling in Poland. International Journal of Environmental Research and Public Health, 17(2), 404. https://doi.org/10.3390/ijerph17020404
Liaw, A. and Wiener, M. (2002) Classification and regression by randomForest. R News, 2(3), 18–22.
Lindstrom, M. (2013) Brand Sense: Os segredos sensoriais que nos levam a comprar. Gestão Plus Edições, Lisboa, Portugal.
Macey, J., Abarbanel, B. and Hamari, J. (2021) What predicts esports betting? A study on consumption of video games, esports, gambling and demographic factors. New Media & Society, 23(6), 1481–1505. https://doi.org/10.1177/1461444820908510
Mendieta, F.H.P. and Queiroz, A.F. (2024) Bets e apostas online: O jogo do Tigrinho e seu efeito tangerina. Contribuciones a las Ciencias Sociales, 17(10), e11358. https://doi.org/10.55905/revconv.17n.10-099
Ministério da Fazenda (2024) Ministério da Fazenda solicita à Anatel o bloqueio de mais de 1.800 sites de apostas ilegais. https://www.gov.br/fazenda/pt-br/assuntos/noticias/2024/novembro/ministerio-da-fazenda-solicita-a-anatel-o-bloqueio-de-mais-de-1-800-sites-de-apostas-ilegais
Muggleton, N., Parpart, P., Newall, P., Leake, D., Gathergood, J. and Stewart, N. (2021) The association between gambling and financial, social and health outcomes in big financial data. Nature Human Behaviour, 5(3), 319–326. https://doi.org/10.1038/s41562-020-01045-w
Tabri, N., Xuereb, S., Cringle, N. and Clark, L. (2022) Associations between financial gambling motives, gambling frequency and level of problem gambling: A meta-analytic review. Addiction, 117(3), 559–569. https://doi.org/10.1111/add.15642
Vasconcelos, F.A. (2013) Contratos de jogo e aposta: Permissão ou proibição. Revista Direito e Liberdade, 15(2), 79–95.