NodeCrafter: Tool for stochastic modeling board games and RPG
Resumo
Introduction: Good game balancing provides fair and engaging gameplay experiences, ensuring equal conditions for players and memorable progression. However, many game creators lack the mathematical knowledge to analyze models based on stochastic mechanics, often relying on intuition and, at best, a large number of practical tests. Objective: This work presents NodeCrafter, a visual tool for modeling game subsystems, focusing on Monte Carlo simulations of stochastic processes for balancing design and evaluation. Materials and Methods: The proposed solution offers an online graphical modeling environment based on node flow that allows for the practical modeling, simulation, and sharing of rules. In addition to comparison with other available tools, the power of representing existing game systems is presented. Results: The results indicate that NodeCrafter can represent various mechanics common in tabletop and RPG games and presents itself as a promising tool for enthusiasts and studios.
Palavras-chave:
Game design, game balancing, stochastic systems, Monte Carlo simulations
Referências
dos Santos Rosa, R. (2023). Ambiente online para modelagem de jogos. Bachelor’s thesis, Universidade Federal de Juiz de Fora.
Engelstein, G. (2021). A visual probability analysis tool for board game designers. Patterns, 2(5).
Engelstein, G. e Shalev, I. (2022). Building Blocks of tabletop game design: An encyclopedia of mechanisms. Crc Press.
Filho, F. F., Gomes, G., Júnior, A. L., Junior, N. C., e Carmo, R. (2021). Balanceamento em jogos para dispositivos móveis: estudo de caso do jogo clash royale. In Anais Estendidos do XX Simpósio Brasileiro de Jogos e Entretenimento Digital, pages 48–57, Porto Alegre, RS, Brasil. SBC.
Metropolis, N. e Ulam, S. (1949). The monte carlo method. Journal of the American Statistical Association, 44(247):335–341.
Mocanu, D. (2023). Modeling and analyzing board games through markov decision processes.
Ourique, L., Silva, F., Parreiras, M., Magalhães, M., e Xexéo, G. (2024). Balancing and analyzing player interaction in the esg+p game with machinations. Journal on Interactive Systems, 15(1):461–477.
Paparistodemou, E., Noss, R., e Pratt, D. (2008). The interplay between fairness and randomness in a spatial computer game. International Journal of Computers for Mathematical Learning, 13(2):89–110.
Policarpo, L. S. (2025). Uma ferramenta visual para modelagem e simulação de regras de jogos de mesa. Bachelor’s thesis, Universidade Federal de Juiz de Fora.
Schreiber, I. e Romero, B. (2021). Game balance. CRC Press.
Silva, F., Ouriques, L., Parreiras, M., Magalhães, M., e Xexéo, G. (2023). Balanceamento do jogo esg+p utilizando o machinations: um estudo de caso. In Anais Estendidos do XXII Simpósio Brasileiro de Jogos e Entretenimento Digital, pages 157–168, Porto Alegre, RS, Brasil. SBC.
Zamith, M., da Silva Junior, J. R., Clua, E. W., e Joselli, M. (2020). Applying hidden markov model for dynamic game balancing. In 2020 19th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), pages 38–46. IEEE.
Engelstein, G. (2021). A visual probability analysis tool for board game designers. Patterns, 2(5).
Engelstein, G. e Shalev, I. (2022). Building Blocks of tabletop game design: An encyclopedia of mechanisms. Crc Press.
Filho, F. F., Gomes, G., Júnior, A. L., Junior, N. C., e Carmo, R. (2021). Balanceamento em jogos para dispositivos móveis: estudo de caso do jogo clash royale. In Anais Estendidos do XX Simpósio Brasileiro de Jogos e Entretenimento Digital, pages 48–57, Porto Alegre, RS, Brasil. SBC.
Metropolis, N. e Ulam, S. (1949). The monte carlo method. Journal of the American Statistical Association, 44(247):335–341.
Mocanu, D. (2023). Modeling and analyzing board games through markov decision processes.
Ourique, L., Silva, F., Parreiras, M., Magalhães, M., e Xexéo, G. (2024). Balancing and analyzing player interaction in the esg+p game with machinations. Journal on Interactive Systems, 15(1):461–477.
Paparistodemou, E., Noss, R., e Pratt, D. (2008). The interplay between fairness and randomness in a spatial computer game. International Journal of Computers for Mathematical Learning, 13(2):89–110.
Policarpo, L. S. (2025). Uma ferramenta visual para modelagem e simulação de regras de jogos de mesa. Bachelor’s thesis, Universidade Federal de Juiz de Fora.
Schreiber, I. e Romero, B. (2021). Game balance. CRC Press.
Silva, F., Ouriques, L., Parreiras, M., Magalhães, M., e Xexéo, G. (2023). Balanceamento do jogo esg+p utilizando o machinations: um estudo de caso. In Anais Estendidos do XXII Simpósio Brasileiro de Jogos e Entretenimento Digital, pages 157–168, Porto Alegre, RS, Brasil. SBC.
Zamith, M., da Silva Junior, J. R., Clua, E. W., e Joselli, M. (2020). Applying hidden markov model for dynamic game balancing. In 2020 19th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), pages 38–46. IEEE.
Publicado
29/09/2026
Como Citar
MELO, Alexandre Altair de; BET, Luis Eduardo; TRINDADE, André Bonetto; HOUNSELL, Marcelo da Silva.
NodeCrafter: Tool for stochastic modeling board games and RPG. In: SIMPÓSIO BRASILEIRO DE JOGOS E ENTRETENIMENTO DIGITAL (SBGAMES), 25. , 2026, Goiânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 907-915.
DOI: https://doi.org/10.5753/sbgames.2026.25914.
