TRAIN Scholar Steven Gonzalez's Blog

  This week I worked on a model to apply to last season's playoffs in order to see how its predictions compared to the actual outcomes of the first round of playoff play. The model that I was assigned used different parameters to determine expected goals (xG) for teams depending on whether they were hosting the match or were the visiting team. For the 6 home teams in the first round of the playoffs, the model only considered goals scored while playing at home throughout the regular season for its xG calculations. For the 6 visiting teams, the model only considered the goals scored in away games that season to calculate xG. This model accurately predicted the result for four of the six matches in the first round of the playoffs. It should be interesting to see how the models from the rest of the group performed. This week, Dr. Posta tasked me with an additional model that only takes the results of the last two games of the regular season for each of the 12 playoff teams in the f

  This week was exciting because we got to meet as a team. We were missing one member of our team as they are currently out of town for the week, but we should have the full team next week. Even then, meeting with part of the team was great because it helped clarify the picture of the scope of the research we are working on.   For this week, we are each working on a different model that we will apply to last year's playoff picture. The plan is to then use the best-performing model to predict this year's playoffs. Additionally, we are still plugging away at the data collection.   I am looking forward to working on my assigned model and seeing how it performs when we apply it to last season's playoffs. Should be exciting to see how each of the models performs and find out what model we will go with for our research.    

      This past week, Dr. Posta tasked me with again building a simple model to predict an upcoming match between the Phoenix Rising and Detroit City FC. For this week, there was a focus on using Excel formulas while building this model. Once again, using stats from the past 10 games, I calculated expected goals for both teams heading into this match. Using that xG stat, I calculated the probabilities of several different possible outcomes of the game. Ultimately, the model expected the Phoenix Rising to win 29% of the time, lose 26% of the time, and draw the remaining 46 percent of the time, with the single most probable outcome being a 1-1 draw 12% of the time. The actual outcome of the match was a 5-0 blowout by the Phoenix Rising. The model only expects a 5-0 outcome 0.00006 percent of the time, so the result of this match was very much a statistical anomaly. This is what brings us to the next stage of our research project, data collection. For this project, we are going to