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This project provides a fully reproducible analysis of Google Trends data for "Cricket Australia" from 2014–2024. It demonstrates how to: Import and clean monthly Google Trends data. Explore time series patterns, including trends, seasonality, anomalies, and autocorrelation. Fit multiple forecasting models (ARIMA, ETS, TSLM) on historical data and evaluate their predictive performance. Forecast search interest for 2025 using all models and visualize combined historical + forecast data. Interpret results and discuss limitations, including the absence of match- or team-specific context—spikes in search interest are often driven by visits from countries like India or England. The document is designed for complete novices, with clear step-by-step instructions, commented code, and reproducible analysis. It serves as a portfolio-quality example of combining sports data, R programming, and statistical modelling for time series forecasting.