eINT%, or DB Interceptions Per Passes Targeted for his or her Coverage Assignment

The first gal I crushed on as a youth was a brunette named Kelly. Aside from chasing each other to a clearing in the woods, basketball was the first sport I loved. The Michael Jordan concept was my favorite. I watched Come Fly with Me on repeat. I probably watched NBA Jam Session more frequently, though, and religiously read the compendium text still nestled on my bookshelf today.

However, Jordan departed from the game in 1993. Likewise, the fam’ and I were relocated southward by my father’s acquisition of stable employment. Aside from teenage pregnancy, obesity, substandard education, joblessness, voting against self-interests, poverty, and libidinous religiosity, the biggest thing in the South is college football. In New England the professional gridiron game received greater coverage than the collegiate game that ruled in my new stomping ground.

At 8, I was oblivious to the nuances of the two and probably watched pro-games because it was more familiar. Today I prefer the myriad offensive stratagems seen in the college game to the “retreaded” schemes of the pros.  But really, it is college football and nothing is comparable.

1996 Deion Sanders Air Max Diamond Turf.

To the 8-year old Justin, the New England Patriots were unappealing. The 49ers had won 4 titles in the 1980s and my grandparents lived in the greater San Fran area. So I cheered for the 49ers. Deion Sanders joined the San Francisco 49ers for the 1994 season and Prime Time became my favorite player, easy. He shut down opposing receivers. He scored touch downs on defense as he high-stepped into the endzone. Two years later, when I entered middle school and appearances suddenly mattered, I begged and begged my parents for Air Max DTs seen at right. 

Importantly, all the kids I knew from school and from the after school program I attended, all those kids’ favorite players were quarterbacks, running backs, and wide receivers. Being the new kid, I found some comfort because my intentions to play cornerback were rarely contended when we played a slightly more bellicose variety of two-hand touch. 

I played baseball, basketball, and soccer through my early adolescence. However, my mother prohibited playing football until I was a teenager. Ultimately, much of my adolescence was devoted to strumming guitars and staring into the sun but needless to say, she probably would have forbidden my donning shoulder pads then too. Had I tried out though, it would have been for spot in the defensive backfield.

Salient for aspiring defensive backs is the number 14. Coincidentally, 14 interceptions is the single season record in both the professional and collegiate ranks, achieved long-ago by ‘Night Train’ Lane (1952, LA Rams) and Al Worley (1968, UWash), respectively.

Night Train hawks the ball.

Ella Lane recovered the 3-month old Lane from a dumpster, adopted him into her family, and reared the future game-changer.  Night Train later served 4 years as a Lt Col in the US Armed Services during the Second World and Korean Wars. After discharge, Lane walked on as a third string receiver and was repurposed as a defensive back prior to his rookie season. That was the same season in which he snagged the 14 INTs. Some speculate that Lane originated the cornerback blitz as QBs increasingly avoided targeting the receivers he covered. 

Lane was married to the renowned Dinah Washington before her death. After football, Night Train was inducted into the Hall of Fame and coached for various small college programs.  Dick Lane, as he was known to friends and family, was survived by three sons and several grandchildren when he passed in 2002 from ailments indicative of a football life.

Elven 'Al' Worley

Less is available about Elven ‘Al’ Worley. He was a consensus All-American in his final season as a Washington Husky in 1968, the season in which he nabbed 14 passes thrown by opposing QBs. During his time at UW Al was a member of the ROTC. Worley was touted among the top DBs in the 1969 draft yet he is missing from the 71 defensive backs selected in the 1969 NFL draft.¹ At 5’11” 175lbs, Worley was admittedly slow and slightly underweight compared to 223 defensive backs whose rookie seasons fell in the seasons 1965-70.  Perhaps these factors limited his potential in the eyes of NFL scouts. Worley did play in 1969 a year of pro football for the since-defunct Continental Football League, however. As an All-Pro All-Star defensive back for the Seattle Rangers he intercepted 4 passes.
 
Ostensibly, Worley later completed his bachelor’s degree at UW in 1970 while serving as an assistant coach to the football team. Worley was appointed defensive backs coach at Northern Arizona in 1971 and held the position through at least 1974.  By 2003 Al Worley resided in Hawaii.²  Maybe he still does. He might live in Huntington VA, though, or perhaps he holds a membership to a Texas RV club. Who knows, I'm no private investigator nor is this an expose of one man's private life. In June 2015 Al Worley was included on the 2016 College Football Hall of Fame ballot. 

Lester Hayes' unique pre-snap stance.

One of Holliman's interceptions of Jameis Winston in 2014.

No pro pigskin player has approached Lane’s mark since Lester Hayes did in 1980 with 13.  Prior to 2014, two had flirted with Worley’s record, David Amerson (2011, NC State) and Terrell Buckley (1992, FSU), who each snagged 13. Enter Gerod Holliman, former free safety of the Cardinals who represent Louisville, capital of Louisville. By early November 2014, I noticed Holliman’s total was 10 and then, a game later, 13. Ultimately, Holliman tied Worley’s record.  

Having known Worley’s fate of undrafted peril, I wondered how Holliman would fare in the 2015 draft. That led to my curiosity about an objective valuation of a DB’s ability to intercept passess. Specifically, the consistency and reliability with which a DB generates interceptions when the pass is targeted to his assignment(s). For instance, in 2003 Josh Bullocks snared 10 INTs for Nebraska, getting at least 1 INT in 9 of 11 games.  Compare that to 2009 UCLA's Rahim Moore who totaled 10 INT in 2009 but only 1 INT in 6 of 13 games. Moore intercepted multiple passes in multiple games but Bullocks appears more likely to have intercepted a pass in any given game. Notably, although Moore played in a greater quantity of games, Bullocks’ opponents attempted 430 passes where as Moore’s opponents attempted only 367.

I advise the reader, my acumen for mathematics is comparable to neither Brian Burke nor Gerald Tamayo. Uncertain how to begin I referred to a familiar statistic, the shot-block percentage (BLK%) used in basketball. BLK% is intended to provide an estimation of the percentage of opponents' 2-point shots a player blocked while he or she was playing. I contemplated several configurations for INT% formulas. However, BLK% translates inexactly to INT% because a constituent of BLK% is a players' minutes played. Minutes played is a readily accessible basketball statistic but in football statistics, the quantity of plays in which a player plays is generally inaccessible. 

Ok, so with that stated I based the final formula on several premises. First, there are a maximum of five eligible receivers on any given play. Second, thorough analysis by others indicates that ~68% of passes are targeted to eligible receivers lined up out wide or at the slot. To obtain that percentage, I included WRs out-wide or at slot, RBs out-wide or at slot, and TEs out-wide. TEs lining up at the slot were excluded because, due to their physical statures, my thinking is that they were generally covered by an LB. 

Thus, there are two probabilities to consider. The first is the probability that an eligible receiver will be targeted (i.e., 1/5). The second is the probability that a pass is targeted for an eligible receiver that would be covered by a DB (i.e., .68). I like this notion of probability because, if the DB of interest is a second-stringer, we could perhaps adjust the first probably to 1/10. Likewise, the second probability could be adjusted for LBs or DLineman (perhaps, .32). 

So in the numerator is the quantity of interceptions by a DB. In the denominator is the quantity of pass attempts defended by that DB's team multiplied by the first probability, .20 or 1/5. The product thereof is multiplied by .68, the second probability. Although the probabilities used in the INT% formula are the most rudimentary of estimates, the results are interesting. 

Table 1. Estimated-INT% for Selection of NCAA DBs with >= 10 INTs in a Season

Player	Year	Program	G	INT	Pass	%Pass Int	eINT%
Al Worley	1968	Washington	10	14	203	6.9	50.7
Gerod Holliman	2014	Louisville	13	14	410	3.4	25.1
Dre Bly	1996	UNC	11	11	326	3.4	24.8
Terrel Buckley	1992	FSU	13	13	402	3.2	23.8
David Amerson	2011	NC State	13	13	407	3.2	23.5
Sean Taylor	2003	Miami	13	10	328	3.0	22.4
Dwight Smith	2000	Akron	11	10	337	3.0	21.8
Rahim Moore	2009	UCLA	13	10	367	2.7	20.0
Anthony Floyd	2000	Louisville	11	10	389	2.6	18.9
Jim Leonard	2002	Wisconsin	14	11	432	2.5	18.7
Senquez Golson	2014	Ole Miss	13	10	402	2.5	18.3
Aaron Beasley	1994	WVU	12	10	402	2.5	18.3
Josh Bullocks	2003	Nebraska	13	10	430	2.3	17.1

Table 1 provides INT% and the necessary data for Worley and players who tallied 10 or more INTs in the past quarter century, sorted descendingly by INT%.³ Worely's feat is given some perspective. The second-to-rightmost column of Table 1 displays the basic percentage of opponent passes intercepted. Unfortunately for my inchoate INT%, the table demonstrates that INT% provides little additional nuance beyond the basic percentage. That is, the rankings of INT% essentially mirror that of basic percentage. However, we gain insight into my earlier discussion of Rahim Moore and Josh Bullocks. INT% suggests that Moore was somewhat more adept at intercepting passes than Bullocks, a result probably attributable, at least mathematically, to Moore's team defensing fewer passes. But again, Moore's basic percentage was slightly greater than that of Bullocks.

The lack of nuance aside, ideally, INT% provides us an estimation of the rate at which a defensive back intercepts passes thrown to the receiver he was defending. But is the INT% ecologically valid? That is, if we knew the actual quantity of passes available for a player to intercept, would INT% provide an accurate estimate?

Table 2. Actual- and Estimated-INT% for a Selection of 2014 NFL DBs

Player	Team	Targeted	INT	PASS	INT%actual	INT%estimate	Act - Est
Richard Sherman	SEA	65	4	507	6.15	5.80	-0.35
Darrelle Revis	NE	79	2	574	2.53	2.56	0.03
Casey Hayward	GB	26	3	564	11.53	7.82	-3.72
Rashean Mathis	DET	89	1	592	1.12	1.24	0.12
Antonio Cromartie	ARZ	81	3	579	3.72	3.81	0.11
Chris Harris	DEN	89	3	641	3.37	3.44	0.07
Josh Wilson	ATL	37	1	566	2.70	2.60	-0.10
Brice McCain	PIT	51	3	543	5.88	4.06	-1.82
William Gay	PIT	104	3	543	2.88	4.06	1.18
A.J. Bouye	HST	85	3	619	3.53	3.56	0.03
Bradley Fletcher	PHI	115	1	591	0.87	1.25	0.37
Blidi Wreh-Wilson	TEN	76	1	545	1.32	1.35	0.03
Joe Haden	CLV	113	3	587	2.65	3.76	1.10
Kyle Fuller	CHI	101	4	548	3.96	5.37	1.41
Buster Skrine	CLV	123	4	587	3.25	5.01	1.76
Jason McCourty	TEN	125	3	545	2.40	4.05	1.65
Johnathan Joseph	HST	117	2	619	1.71	2.38	0.67
				Mean:	3.50	3.65	0.15
				SD:	2.53	1.74	1.32
Note, italicized eINT%s were computed with .1 in denominator instead of .2 because those players were considered second-string following cursory comparison of their quantity of games started and games played.

Let us consider 17 professional defensive backs for whom we the have numbers. Table 2 contains the actual INT%, our estimated INT%, and the difference of the two. For these 17 players, the eINT% formula overestimates the actual INT% by an average of .15 and, if we exclude an outlier of -3.72, an overestimation of .39. (Actual and estimated INT% correlated positively, Rho = .85, p < .001, 2-tailed.)⁴

There are shortcomings to predicted INT%, of course. The pro-sample used to validate the accuracy of the eINT% is small. The accuracy of eINT% may be less evident with a larger data set. But given my fixed income as a grad student, I am unwilling to spend the money to obtain targeted-data for the League. 

For the college and professional samples, estimated INT% increases as opponents' pass attempts decrease; the college sample considerably more so than the pro sample (act. Rho = -.35, est. r = -.35, ps > .15), skewed by the Worley data point (Rho = -.46 with Worley, Rho = -.32 without, ps > .10). Also, each team in the college sample defended more run than pass plays whereas more pass than run plays were defended in the pro sample. 

Probabilistically allocating opponents' pass attempts equally among defensive backs led, at least in part, to disparities that emerged between actual- and estimated-INT% in the pro sample. Inclusion of another readily accessible statistic of individual players might provide a more accurate and personalized estimate of INT%. This is evident in the pro-sample as Brice McCain and William Gay each tallied three interceptions for the Pittsburgh Steelers and thus have identical estimated INT% despite Gay being targeted more than twice as often as McCain.

I am fond of the relative simplicity of the statistic, however. The formula could be easily enhanced by summing interceptions and pass deflections to provide a statistic more representative of a DB's ability to prevent successful passing.

Before concluding, let us return to Al Worley and 1968. Football strategies have shifted and that is evident in the statistics. The ratio of pass to run plays has increased. Rules have changed. Fewer passes were attempted in '68 and Worley's 50.7 estimated INT% is gaudy, indeed. Recall, the highest actual-INT% in the pro-sample was Casey Heyward's 11.43 and, in estimated-INT%, Howard's 7.82; his basic INT percentage was 0.5% (excluded from Table 2 due to minuteness). Consider then, Night Train Lane's basic percentage of 3.9% in his record breaking 1952 season and an estimated 28.6 INT%. Staggering. Lester Hayes picked off 2.5% of opponents' passes in 1980 with an estimated 18.2 INT%. My favorite, Prime Time, well, in his best season, he picked 1.4% on 7 interceptions in 1993 with an eINT% of 10.2 and in the '94 season with the 49ers, he had 6 picks at 1% with an eINT% of 7.6.

So I leave the reader with INT%, for now. To follow in the near future are my thoughts on statistically evaluating a defensive back's ability to counteract his opponents' successes scoring and moving the ball. 



Notes:

¹ As an aside, Roger Wehrli played was a 7-time All-Star in his 14-year NFL career.  

² Admittedly, I'm wagering that the obituary is of a woman who is Worley's sister. The 1968 Walla Walla Union-Bulletin snippet indicates Worley is one of 10 children and the 2003 obituary states the woman was survived by 5 brothers and 4 sisters. The WWUB snippet mentions Al's brother Larry and the obituary mentions a brother named Lawrence which is often short for Larry. However, the WWUB snippet states the mother's name is Blanche whereas the obituary states the mother's name is Bertha. Regardless, I am writing this text to discuss estimated INT% absent any intentions of unearthing a man's private life. However, the reader curious about Worley's later life may find this worth noting.

³ Unless noted, all statistics sourced from Sports-Reference.com. Less accessible sources are provided for the reader's convenience.

⁴ Here and elsewhere in the text, Rho, or Spearman's rank correlation, is presented when data have high skewness and/or kurtosis.