Current Statistics for NFL Cornerbacks Inadequate

Charles Woodson

Al Harris

After reading about Al Harris of the Packers possibly being done for the season due to a likely ruptured spleen, I went and checked his and his teammate, Charles Woodson’s career stats. The article said that they form one of the most formidable cornerback (CB) tandems in the NFL. If you don’t watch the Packers regularly, it’s hard to verify except to compare stats with other CBs.  However, when you look at the stat categories for a defensive back, it doesn’t show the effectiveness of the player. Deion Sanders, arguably the best cornerback ever in NFL history, has a statbox similar to many CBs and  thus makes it difficult to conclude his greatness. Let’s look at ESPN and NFL.com’s stats of Charles Woodson’s career:

ESPN – Charles Woodson Career Defense Stats
YEAR	TEAM	G	TOT	SOLO	AST	PD	SACK	FF	REC	INT	YDS	TD
1998	OAK	16	62	59	3	20	0.0	2	0	5	118	1
1999	OAK	16	61	51	10	15	0.0	0	0	1	15	1
2000	OAK	16	76	63	13	13	0.0	3	0	4	36	0
2001	OAK	16	52	39	13	10	2.0	1	0	1	64	0
2002	OAK	8	33	31	2	4	0.0	4	0	1	3	0
2003	OAK	15	69	56	13	8	1.0	1	0	3	67	0
2004	OAK	13	73	58	15	9	2.5	2	0	1	25	0
2005	OAK	6	30	26	4	4	0.0	1	0	1	0	0
2006	GNB	16	62	51	11	20	1.0	3	0	8	61	1
2007	GNB	14	63	52	11	9	0.0	0	0	4	48	1
2008	GNB	3	7	7	0	6	0.0	0	0	2	41	1
Career		139	588	493	95	118	6.5	17	0	31	478	5

NFL.com – Charles Woodson Career Defensive Stats
			Tackles					Interceptions
Year	Team	G	Total	Solo	Ast	Sck	SFTY	PDef	Int	TDs	Yds	Avg	Lng
2008	Green Bay Packers	3	7	7	0	0.0	0	6	2	1	41	20.5	41T
2007	Green Bay Packers	14	63	52	11	0.0	0	9	4	1	48	12.0	46T
2006	Green Bay Packers	16	59	48	11	1.0	0	12	8	1	61	7.6	23T
2005	Oakland Raiders	6	30	26	4	0.0	—	3	1	0	0	0.0	0
2004	Oakland Raiders	13	73	58	15	2.5	—	8	1	0	25	25.0	25
2003	Oakland Raiders	15	69	56	13	1.0	—	5	3	0	67	22.3	51
2002	Oakland Raiders	8	33	31	2	0.0	—	3	1	0	3	3.0	3
2001	Oakland Raiders	16	52	39	13	2.0	—	9	1	0	64	64.0	34
2000	Oakland Raiders	16	—	—	—	0.0	—	0	4	0	36	9.0	23
1999	Oakland Raiders	16	—	—	—	0.0	0	0	1	1	15	15.0	15T
1998	Oakland Raiders	16	—	—	—	0.0	0	0	5	1	118	23.6	46T
TOTAL		139	386	317	69	6.5	0	55	31	5	478	—	51

The two sets of stats are essentially the same. We can rule out several of the categories as obviously  being bad indicators of how well a secondary player plays – touchdowns (TDs), sacks (SCK) safeties (SFTY), forced fumbles and recoveries (FF, REC). As a matter of fact, most of those are in either ESPN’s or NFL’s and not both, which confirms them as bad indicators. So, let’s focus on the three stat groups that have traditionally been used to assess the efficiency of CBs (and even safeties) – tackles, interceptions,  and passes defended (PD, PDef).

TACKLES

Charles Woodson attempts to tackle Plaxico Burress of the NY Giants

Tackles are a tricky statistic because they can mean two things. It might mean the receiver he was covering just made a big catch against him and he had to tackle him. It might mean a running back ran into the secondary and he made a great open field tackle. If he had a large number of tackles it could mean he is very active and covers a huge swath of the field, or… it could mean that he is a bad pass coverage guy and the opponents keep targeting him. Thus, it is difficult to really put any emphasis on any of the tackle categories; total, solo, and assisted.

INTERCEPTIONS

Interceptions have a similar problem. A CB having no interceptions in a game gives no clues in whether he played a good or bad game. Interceptions also have a lot to do with luck and situation. It really doesn’t show the skill of a secondary back. Additionally, interceptions are rare and normalizing the statistic to per game would not solve the problem. Interceptions are a worse stat than sacks for a defensive back  (DB) because interceptions can only occur if a pass is directed at his coverage area, whereas a DB or a defensive tackle rushes the quarterback a majority of the game.

PASSES DEFENDED

Passes defended is a potentially good statistic. It shows that when a pass is directed at the CB, was he successful at preventing the pass from being completed by the offense. It shows a skill that he is legally (with no penalty) in the area and provided excellent coverage to defend the pass. So what is the problem? The problem is that it is not normalized. What does it mean when a cornerback defended two passes in a game? There is nothing to compare it to. It could mean two passes were directed at him and he knocked both down, for a 100% efficiency, or it could mean 10 passes came at him and he knocked only two down, for a 20% efficiency. Two completely different results. But what do you normalize it to?

NEW STATISTIC – PASSES DEFENDED EFFICIENCY

CB Aaron Ross intercepts a pass

Just like an average and ERA in baseball, or a yards after catch (YAC) and rushing average in football, we need something that normalizes the stat against all other games and players. One way would be to divide the passes defended in a game by the number of passes directed at him in that same game. This would give us a pass defended efficiency average per game (PDE). Another option would be to divide the number of total passes defended in the season by the number of total passes directed at him in the season (PDE). The latter one is a better statistic because it would remove anomalies such as games in which only a few passes are directed at him and his PDE in that game is either 0% or 100%. However, what makes this stat difficult to record is determining the number of passes directed at a specific CB. In times when a CB plays zone or steps up to tackle or defend another player, it’s hard to say is the pass directed at him. Or if there are multiple defenders in the area, what do you do? Also, some passes are difficult to determine its intended target. Maybe this can be a statistic recorded for the secondary.

NEW STATISTIC – AVERAGE PASSES DIRECTED TOWARDS

Another statistic is to determine the percentage of passes in a game directed at a CB. In many cases a quarterback will target the CB that is most vulnerable. This would show up in this statistic. However, a quarterback will also target his best receiver regardless of who the CB is. That means a less than stellar CB on a less than stellar receiver will have a low percentage of passes directed at him. That does not mean he is a good CB.

Deion Sanders

NEW STATISTIC – AVERAGE CATCH YARDS AGAINST

Just like the running back has the average yards per rush, the wide receiver has the average yards per catch, and the quarterback has the average yards per pass attempt, we need a statistic for the defense.  They already have average yards per rush against and possibly an average yards per catch, but it is for the whole defense and accounts for tight ends, running backs, and wide receivers. There needs to be a statistic for  average yards per catch against each specific CB or at least for the whole secondary. As a fan, it’s sometimes very difficult to watch when a timid CB plays at least 10 yards off his receiver and gives up an easy catch and run.

CONCLUSION

The biggest problem is trying to normalize a statistic. With the way defensive schemes are used, many times it’s not just one person responsible for a catch but multiple players. However, that happens on offense also, such as determining whether a pass is the fault of the quarterback or its intended target. Quarterback stats drop even when they make perfect passes but the receiver drops the ball. What we realize though is that these stats usually evens out, and the best quarterbacks, running backs, and receivers have high numbers  compared to worse QBs. A similar reliable statistic must be created and tracked in order to determine how well a cornerback plays.