Neural network data analysis and mathematical modelling for Wordle games

Wordle is a popular daily puzzle in the New York Times. The 'Predicting Wordle Results' problem in the 2023 Mathematical Contest in Modelling (MCM) focused on developing a model to estimate the reported headcount in the difficult mode. The model considered three attributes: word frequency, letter repetition and letter frequency. The analysis showed that these attributes influenced the reported headcount. Correlation analysis revealed a strong relationship between the number of participants and word frequency and letter repetition. A neural network time series model was developed, using word frequency and letter frequency as inputs to predict the reported results. The model achieved a high accuracy with an R²-value of 0.95. The study found that the number of participants had a linear relationship with the number of participants in the difficult mode. Most word frequencies in the questions were below 0.0002.