YFOG = yards from own goal, for instance, the red zone would be 80 YFOG to 99 YFOG
Columns are named to refer to the query # that the stats are coming from, along with N1 appended to the end of the column name for the player's year N+1 stats. So reYDS.Q1.N1 means receiving yards subject to the Query 1 filter parameters, in the player's N+1 season. reYDS.Q1 would just be the player's stats in season n.
**If a player was on multiple teams in a single season, the "TEAM" column refers to the team for which they had the most attempts/targets
***Wide data tables can be scrolled horizontally using the scroll bar below the table.
Requires a valid data table showing in the first tab, before the comparison table will be rendered below.
This tab requires a table to be displayed in Screen Results tab before the linear model function will work. Use this tab to perform multiple linear regression and test the relationship between variables. While not to be thought of as a replacement for thorough analysis, this tab can help you quickly determine whether variables have any relationship to each other. Note that the training dataset is subject to the sliders in the Screen tab. Some variables will not have linear relationships and thus linear regression is not a good solution for exploring those relationships. If you're unfamiliar with multiple linear regression then some reading on the topic will probably be required.
Columns are named to refer to the query # that the stats are coming from.
If no table is showing below click 'Search the Database' above.
This tab finds the most similar players based on the variables selected, as well as the number of seasons selected.
Columns are named to refer to the query # that the stats are coming from, along with N1 appended to the end of the column name for the year N+1 stats. So reYDS.Q1.N1 means receiving yards subject to the Query 1 filter parameters, in the N+1 season. reYDS.Q1 would just be the stats in season n.
***Wide data tables can be scrolled horizontally using the scroll bar below the table.
Requires a valid data table showing in the first tab, before the comparison table will be rendered below.
This tab requires a table to be displayed in Screen Results tab before the linear model function will work. Use this tab to perform multiple linear regression and test the relationship between variables. While not to be thought of as a replacement for thorough analysis, this tab can help you quickly determine whether variables have any relationship to each other. Note that the training dataset is subject to the sliders in the Screen tab. Some variables will not have linear relationships and thus linear regression is not a good solution for exploring those relationships. If you're unfamiliar with multiple linear regression then some reading on the topic will probably be required.
Columns are named to refer to the query # that the stats are coming from.
Requires a valid data table showing in the first tab, before the comparison table will be rendered below.