While this article can be applied to other sports, the calculations and examples applied will be for the NFL.
For decades people have compared athletes. A lot of people say it is impossible to compare players of different eras. Someone from the 1920s did not have the gear, coaching, supplements, health regimens, or access to gyms that players today have. Players today have those opportunities but they also play with a different set of rules which promote safety. Either way, football has evolved from different eras over the course of its history.
What I like to do most with football is look at the general statistics of players as a part of comparing players. The big issue for me is comparing these players of different eras. So I have come up with my own way of doing this from a statistical standpoint. Thank you to a video made by Brandon Perna of That’s Good Sports, which looks at the averages of different groups of seasons in Elway’s career(Link: What Would John Elway’s Stats Look Like in Today’s NFL?), I was inspired to take a deeper dive into how to compare a game, a season, or a career of a player to what it would look like in the most recent season of the NFL. Or looking at it from a different point of view by seeing how a player right now could have performed if dropped into a random season.
The formula I have used is shown below:
{y/[(w/x)*32]}*z=The player’s projected total for the statistic of the analyzed season had he played in 2022.
w=The league total of a given statistic for a season the player played
x=The number of teams for the league in the season the player played
y=The player’s total of the given statistic for the season
z=The 2022 total of the given statistic
In order to explain why this specific equation, let’s break it into three parts.
First, we will look at (w/x)*32. The “w/x” is to find the average for each team, for the given statistic, and for the given year. Multiplying this by 32 will determine what the league would have totaled had there been 32 teams. This will apply to every season in the NFL before 2002.
Next is “y/[(w/x)*32].” The “y” is divided by this total in order to find what percentage of the league’s total of a given statistic was for that season.
Finally, the reason for multiplying everything by “z” is to find the equivalent of that percentage for 2022.
Example(for the sake of this I will round some of the statistics but my spreadsheet is more exact):
- In 1990 there were 87,249 passing yards thrown in the entire league with 28 teams.
- (87,249 / 28)*32= 99,713.14 projected passing yards had there been 32 teams.
- Joe Montana threw for 3,944 passing yards in 1990.
- 3,944 / 99,713.14=0.395%.
- 118,438 passing yards were thrown in 2022.
- 118,438*0.395%≈4,685
So, Joe Montana’s 1990 season would be equivalent to him throwing for around 4,685 passing yards in 2022.
This formula takes into account any increase/decrease in production due to the era, impact on statistics due to rule changes, the number of games played, and just how good they were for the given year.
Even though a touchdown has always been six points, that does not always mean six points have been as important in different eras. The average score has increased over time and the number of plays has increased over time, so the importance of just one touchdown is not the same as it was 10, 20, 50, or 100 years ago. The same goes for any statistic. This is just like how the value of a dollar has changed over time.
Another way to look at this is that you could find out what a player right now would look like from a statistical standpoint in a given year. What would Patrick Mahomes look like in 2000? Jalen Hurts in 1980? or Justin Jefferson in 1960?
Now I understand there are certain aspects that cannot be quantifiable such as injuries, stamina, schemes, etc. but this is just looking at what the players would do if you took the entire league from a time and placed it at another point in time.
I have many posts I will be working on that look at players careers, records, single-season statistics, and many other categories inflated to today’s numbers. In the meantime, here is what Jerry Rice’s season-by-season and career numbers would look like if inflated to today’s numbers: https://www.facebook.com/100046329654150/posts/pfbid02QcXL3jr1d7YCKBfz4ixzKDJ1SXeerDerNM1X8BJTrGqGe74npZsFh5i3vm2JDUBBl/?mibextid=DcJ9fc
-Jordan Burden