Introducing the CFB Stat-Finder App

Primer on my newest app creation

I dropped another new app today, and it is one I will be utilizing plenty for content this year: the CFB Stat-Finder.

The Stat-Finder is great because it is loaded with information on anyone who has played Division 1-A football since 2000 (with 2020 stats coming at the conclusion of the college season). The app comes complete with 38 different data-points, and allows you to view them on either a single-season or career level. Here’s a look at Tee Higgins’ career prior to coming out of Clemson last year:

You can see that the app gives the optionality to look at a player’s career year-by-year, or in the aggregate. This should make comparing players quite easy. Here’s Higgins along with two other alphas from the 2020 class: Justin Jefferson and CeeDee Lamb:

The heatmaps are localized, so you can quickly see the best and worst of any stat comparison. Lamb makes any prospect look pedestrian, but if we swap him out with Jalen Reagor, the colors change:

Career stats are computed in three main ways:

Per-Game: total statistic/total games played

Market Share/Opportunity: average of each season

Efficiency: total statistic/total attempts

Most of this is intuitive, though you may not expect the calculation of market share statistics to come as a career average. This is the “old RotoViz” method, and one that I prefer. I have used, for example, total receiving yards/total team receiving yards in the past, but found it skewed the numbers towards the seasons with higher team volume. This seemed counter-productive to me, since that is out of the player’s control.

The CFB Stat-Finder should be a go-to tool for prospect evaluation. Once I have added the 2020 data, I may play around with a similarity feature that allows you to find the most comparable prospects — much like my NBA Similarity App.

Glossary of Statistics

In case they are not immediately obvious, these are the 38 statistics currently used in the app. Career stats will simply have a prefix of “c_”.

pass_pct: Completion percentage

rush_avg: Yards per carry

rec_avg: Yards per reception

kr_avg: Kick return average

pr_avg: Punt return average

game: Games played

ms_rush_att: Market share of rush attempts

ms_rush_yd: Market share of rushing yards

ms_rush_td: Market share of rushing touchdowns

ms_rec_rect: Market share of receptions

ms_rec_yd: Market share of receiving yards

ms_rec_td: Market share of receiving touchdowns

ms_scrim_yd: Market share of scrimmage yards

ms_scrim_td: Market share of scrimmage touchdowns

ms_touches: Market share of team touches

dom: Dominator rating, average of ms_rec_yd and ms_rec_td

rec_yd_pta: Receiving yards per team pass attempt

rec_td_pta: Receiving touchdowns per team pass attempt

adj_ypp: Adjusted yards per play, (2*receiving yards + rush yards)/plays

pass_comp_g: Completions per game

pass_att_g: Pass attempts per game

pass_yd_g: Pass yards per game

pass_td_g: Pass touchdowns per game

pass_int_g: Pass interceptions per game

rush_att_g: Rush attempts per game

rush_yd_g: Rushing yards per game

rush_td_g: Rushing touchdowns per game

rec_rect_g: Receptions per game

rec_yd_g: Receiving yards per game

rec_td_g: Receiving touchdowns per game

kr_ret_g: Kick returns per game

kr_yd_g: Kick return yards per game

kr_td_g: Kick return touchdowns per game

pr_ret_g: Punt returns per game

pr_yd_g: Punt return yards per game

pr_td_g: Punt return touchdowns per game

pass_ypa: Pass yards per attempt

pass_aya: Adjusted yards per pass attempt (PFR definition)