Third Blog

Third Blog (2/14):

• METHOD

– What type of method have you selected? Why?

– Explain and justify 3-5 steps of your method.

– Identify and explain at least TWO limitations/challenges of your method.

My method consists of Descriptive Statistics Calculation, Comparative Analysis, and Discriminant Analysis. First, I will compute means and standard deviations for key game-related statistics to summarize performance trends. Then, I will use independent t-tests (or one-way ANOVA if necessary) to identify significant differences in game-related statistics between different groups, such as winning vs. losing teams or top vs. bottom performers. Additionally, I will likely incorporate Discriminant Analysis to determine which statistical variables best differentiate performance groups, potentially using the leave-one-out cross-validation method (which validates the model by training it on all but one data point, repeating this for each point, and averaging the results to assess accuracy). I chose this method not only because several similar sources used these three types of analysis but also because it made the most sense when comparing statistics between groups. Additionally, a few sources conducted their method on SPSS(some statistics software) which I plan on using as well. A key limitation of this approach is potential multicollinearity, where some game-related statistics may be highly correlated, potentially distorting results. To mitigate this, I will exclude variables with high correlation coefficients (r>0.60r > 0.60r>0.60) from the discriminant analysis. Another limitation is the sensitivity to small sample sizes, such as in leave-one-out cross-validation, which may lead to unreliable classification accuracy. 

Which criteria did you use to discriminate among the perspectives in order to reach a conclusion?

Since each source is using similar methods to analyze different leagues/levels of play, I chose the three tests that were most common among them. Additionally most of them used 2-3 tests so my method is pretty similar to existing research. Some sources focused on preseason vs post season and some about starts, vs non starters so I am taking a similar spin to the research by focusing on D1 vs D2 vs D3 levels since Region 10(my gap) consists of teams from each of these divisions. I also think this is a good approach since this method will have implications for all levels of college basketball.