Primary Offensive Statistics
The table below shows the primary statistics and the accumulation of each.
2019 was an exciting season for fantasy baseball. Pitching was not the strength of the league overall (#juiced_balls), but offense made for tight matchups. Not to mention a tight Postseason. Below is a breakdown of data collected throughout the season, by hand (typed into excel from ESPN), and broken down with the statistical program, R. You’ll see many different aspects covered in the breakdown and I will try to provide as much detail about the statistics shown as I can. If there are any stats that you’d be interested in seeing, feel free to contact me and I’ll update the summary with suggested edits!
Below is the data that was used to put together the analysis. CAUTION: There are a lot of columns, so it may not appear well on modile devices.
The following is just a quick breakdown on how people scored points throughout the season.
Below is a summary of the total points scored by each franchise this season. The red line represents the mean number of points on the season. Including the playoffs, McCartney led handily over the rest of the league.
The following represents how teams scored points during the regular season. It shows how close the race for most points was for the top teams. The top 5 in the league in points were separated by only 400 points during the regular season.
Like the regular season analysis, this is an analysis of points scored by teams in the postseason. Our champion, McCartney, dominated the the playoff point totals. Connelly made a case that he will be relevant for next season’s playoffs.
The following are ratios created based on different values of points collected throughout the season. LUE stands for lineup efficiency and is based off of total roster points and points left on the bench.
| Stat | Definition | Formula |
|---|---|---|
| Off to Pit | Ratio of Offense to Pitching | (Sum of Offensive Points)/(Sum of Pitching Points) |
| Pos to Neg | Ratio of Positive to Negative | (Sum of Positive Points)/(Absolute value of Negative Points) |
| LUE (Lineup Efficiency) | Efficiency of roster usage | (Sum of Total Points)/(Sum of Total Points and Bench Points) |
| OP/TB | Ratio of Offense to total bases | (Sum of Offensive Points)/(Sum of Total Bases) |
The sections below contain data on how each franchise performed on offense. Tables have been created to make them easily sortable.
The table below shows the primary statistics and the accumulation of each.
The following summary shows the statistics that had less of an impact than the primary statistics with regards to overall scoring.
The following table shows a representation of how points were earned as percentages. Positive earning categories will be divided by the total positive offensive point total. The same can be said for the negative point categories.
The graph below shows how many offensive points each franchise earned each month per day. We have used a per day basis in order to make it a standard number. The last month of the season consisted of one day. As a result, the daily average only reflects one day worth of data.
The sections below contain data on how each franchise’s pitching performed. Tables have been created to make them easily sortable.
The table below shows the primary statistics and the accumulation of each.
The following summary shows the statistics that had less of an impact than the primary statistics with regards to overall scoring.
The following table shows a representation of how points were earned as percentages. Positive earning categories will be divided by the total positive pitching point total. The same can be said for the negative point categories.
The graph below shows how many pitching points each franchise earned each month per day. We have used a per day basis in order to make it a standard number. The last month of the season consisted of one day. As a result, the daily average only reflects one day worth of data.