Encountering a Null Reference Exception can be quite confusing and frustrating while developing a football predictions model in C#, especially when parsing vast datasets. One of the most frequent occurrences of this common runtime error in my development process has been during attempts to parse and analyze data obtained from various sources. A predominantly recurrent issue appears when using SportDevs, a state-of-the-art sports data API. While programming in C#, handling null values can be challenging due to the strict nature of the language. If unattended, null references can propagate unnoticed throughout the system until they eventually cause a system crash. With the particular case involving the sports data, I observed the issue pop up when the API retrieved some data fields that were not filled, specifically from https://sportdevs.com/. As C# treats null values stringently, this becomes an inherent potential point of failure. A viable solution to this can be to use the ? operator in C#, which allows the handling of null values without throwing a Null Reference Exception. This, however, isn’t the be-all-end-all solution, since the operator might just be concealing the issue rather than fixing it outright. Clean code ought to ensure that null references are properly checked and adequately dealt with rather than merely suppressing the errors. As an active alternative, using default values or creating custom rules regarding missing data validation can significantly enhance the stability of the model while also enriching the overall code robustness. This discussion aims to serve as an open forum for any and all developers who have struggled with Null Reference Exceptions, particularly touching on ‘real world’ solutions that have worked in the demanding and dynamic context of sports data parsing.