The quarterback rating was something that always intrigued me. To have a formula to compare players based on a combination of stats is great. But, I’ve always had problems with what the NFL uses to rate quarterbacks. I first wanted to simplify the QB Rating equation, but I could never get it right, (This guy did) so I had to move on from that. Then I thought what does the QB rating actually mean? Philip Rivers lead the league with a QB rating of 105.5 this year, how good is that? How much better is that than the 10th QB on the list, Matt Cassel at 89.4? And more importantly, what does that 16.1 point difference in rating actually mean. Most sports statistics mean something. In baseball, ERA is the amount of earned runs a pitcher gives up in 9 innings, hockey has points for goals and assists, and in basketball they keep track of points per game. All are great ways to compare players and all have meaning behind the stats.
First, I did some searching online and discovered that the QB rating was created in 1973 by an executive at the Pro Football Hall of fame, Don Smith. Smith’s formula compares a quarterback’s performance based on the total of all quarterback performances in the past 10 years. In the formula that Smith created, he separates completion percentage, passing yardage, TDs and interceptions and awards 1 point for an average game and 2 points for a record breaking game and zero for a terrible game. Smith weighted each category and averaged out the numbers and bam you get the QB Rating. With the top QB rating being 158.3 and the lowest of course is 0, average was supposed to be 66.7. The average for the past 10 years was 80.1.
What if you could compare the quarterback’s stats to their team’s chances to winning the game? This makes the most sense, they touch the ball more than any other player on the team. And why not, they get all the credit when the team wins and all the blame when they lose? So I took every quarterback’s stats from every game the last ten years and put a winning percentage to each category. For example if a quarterback doesn’t throw an interception in the game his team's chances of winning is 66.11%. If a QB throws 2 TDs, he wins 58% of the time. A completion percentage of 40% only wins 18.8% of the time. I graphed each number found the best line to fit the graph.
I did this for each category and kept the stats that had the strongest correlation to winning. I found that completion %, total TDs, total turnovers, yards/play and sacks all had extremely strong graphs. Surprisingly total passing yards didn’t, the graph was all over the place.
The only stat that I was keeping the same from the old equation was completion percentage. All the others were tweaked a bit. It makes more sense especially with today’s football to include things like rushing yards, rushing TDs and fumbles. Even true pocket passers, QB sneak it into the endzone every once in a while. To prove my point, Peyton Manning has 17 career rushing TDs. And when all is said and done Peyton running the ball in for a score gets the same result as him throwing it in, so shouldn’t his rating benefit the same?
For each category I have a linear equation with an R2 of over .97. For all people that aren’t math nerds, the simplest way I can explain it is, R2 is, when using linear lines, a number that shows how strong a line fits with to a set of data points. The number 1.00 means the line fits perfect and 0 the not fitting at all. TDs and turnovers have the strongest correlation with a .999 and the other categories not too far behind, yards/play .97, sacks .98 and completion percent at .98.
After I got the equation for each category I did a weighted average and got your Kosmo Winning Percentage (Why wouldn’t I name my formula after myself?). Now this equation is uglier than the old version, but it uses stats that have a connection to what you play for, winning the game. Another way to say it is, this number shows which QB put their team in best position to win games.
Using the KWP this year’s top passer was not Phillip Rivers, it was Drew Brees with a number of .640. Now one may look at this number and think that it seems odd or small for a rating the top QB of the year. But the QB is just one of several pieces of the puzzle to win the game. There are other factors like the Saints 23rd ranked defense or 28th ranked rush offense, both decreasing their chances of winning games. And the reason why they won 8 games instead of the 10 predicted.
Just because the KWP is higher than the opposing QB doesn’t always mean you will win the game. Just take this year’s Super Bowl for example. Kurt Warner’s numbers put the Cardinals in a better position to win with a KWP of .647 compared to Big Ben’s .567, but The Steelers defense made big plays, specifically James Harrison 100 yard TD.
With this new rating there is no cap or floor, it goes slightly outside of the 1.000-.000 scale of winning percentage. The best game ever played by a QB, Johnny Unitas 11/12/67, got a KWP of 1.062 and the worst game ever played Ryan Leaf 9/20/98, got a KWP of -0.010. It didn’t like that there were 47 “perfect” games for QBs, with some games way more impressive than others.
Football is evolving; the game isn’t close to what it was back in 1973. I think it’s time for a new way to rate quarterbacks and this is the way to do it.
I listed my formula and some new rankings below. This season’s KWP, Top Careers, Stand-Out Seasons, “Perfect” Games and “Zero” games.
I am up for ideas on how to improve the formula or other suggestions.
