The position of 2nd Row is one of the most important in Rugby League for a variety of different reasons. For a long time, coaches have positioned their most damaging forwards in the #11 or #12 to run courageous lines at the defence by bursting through holes or attracting defensive attention as a decoy. Currently, the majority of attacking plays in the NRL are built upon this premise – move the ball to the edge and have players running through the defensive line. These plays are mostly effective because it forces the defence to make quick decisions, and with so many players in motion around the ball it’s easy to make a mistake. This is how the position of 2nd Row has become so important, with so much action on the edge they have evolved into the primary decision makers on defence. If they make the wrong defensive read, they concede an immediate overlap on the outside, if they make the correct read, they can snuff-out any chance of a potential line-break. Edge defence has never been more crucial.

While its importance has long been recognised, how can we accurately quantify edge defence?

Unfortunately, there are no statistics that recognise how often a player makes the ‘correct’ or ‘incorrect’ defensive read, however there are some defensive statistics that have surprising application. Raw counting-statistics like tackles and missed tackles have limited use in isolation, however there are ways to boil-down these numbers into a more useful metric. How many missed tackles a player contributes is less important than how often a player misses a tackle per attempt – missing 10 tackles from 50 attempts has more value than missing 6 tackles from 14 attempts. Breaking-down these raw numbers into per-attempt efficiency is an important step towards quantifying defence. Context is also important, missed tackles even in a per-attempt format do not consider situation – a defender might be consistently positioned in poor situations that result in an increase in misses while other defenders are given support from their teammates resulting in more completed tackles. Luckily, One-on-One tackles is a statistic available which can help shed light on how often a defender is positioned in a One-on-One situation which is more likely to result in a miss. Combining these considerations, a metric called Defensive Efficiency can be created.

Defensive Efficiency (DE%) is a combination of a players; Tackle attempts per minute, Misses per attempt, Ineffective tackles per attempt, One-on-One tackles per attempt and Penalties per attempt. Each individual metric is given as a percentage of the average for the position – players who have a positive % perform higher than average, and those with a negative % perform lower than average. The full-breakdown for the DE% of all qualified edge defenders (min 5 games at Second Row) can be seen here, however this is the isolated DE% of all edges ranked from best to worst:

Rank Name DE% 1 S. Sorensen(CRO) 108.75% 2 M. Aubusson(SYD) 93.99% 3 M. Niukore(PAR) 91.16% 4 F. Kaufusi(MEL) 85.86% 5 M. Gillett(BRI) 83.47% 6 R. Matterson(SYD) 79.96% 7 I. Yeo(PEN) 78.14% 8 M. Ma’u(PAR) 74.42% 9 G. Cooper(NQL) 65.71% 10 J. Jackson(CBY) 61.46% 11 J. Stimson(MEL) 56.23% 12 T. Moeroa(PAR) 46.46% 13 A. Guerra(NEW) 43.68% 14 T. Harris(WAR) 42.11% 15 C. Lawrence(WST) 36.48% 16 R. Faitala-Mariner(CBY) 36.34% 17 J. Thompson(MAN) 33.14% 18 V. Kikau(PEN) 32.85% 19 T. Frizell(STI) 26.74% 20 S. Lane(MAN) 16.79% 21 T. Sims(STI) 11.23% 22 B. Cordner(SYD) 1.56% 23 I. Papali’i(WAR) -1.17% 24 L. Fitzgibbon(NEW) -7.02% 25 K. Capewell(CRO) -13.89% 26 W. Graham(CRO) -18.57% 27 A. Crichton(SOU) -23.49% 28 R. Martin(CBY) -24.55% 29 K. Proctor(GLD) -26.48% 30 J. Su’a(BRI) -26.59% 31 J. Sutton(SOU) -26.88% 32 C. Hess(NQL) -27.98% 33 C. Harawira-Naera(PEN) -28.87% 34 R. Rochow(WST) -33.64% 35 A. Glenn(BRI) -43.50% 36 R. Hoffman(MEL) -55.84% 37 E. Whitehead(CBR) -66.65% 38 W. Matthews(GLD) -70.06% 39 J. Tapine(CBR) -71.15% 40 M. Barnett(NEW) -79.11% 41 M. Chee Kam(WST) -88.47% 42 T. Pangai Junior(BRI) -109.39% 43 L. Lewis(CRO) -136.73% 44 K. Hipgrave(GLD) -217.28%

Subjectively, DE% seems to have accurately separated defenders who have a reputation. Defensive stalwarts like; Mitchell Aubusson, Felise Kaufusi, Matt Gillett, Isaah Yeo, Gavin Cooper, Josh Jackson, Aidan Guerra, Tyson Frizell, Tariq Sims and Boyd Cordner all rank as above average edge defenders by DE%. Players with largely questionable defensive reputations like; Tevita Pangai Jnr, Coen Hess, Will Matthews, Keagan Hipgrave and Angus Crichton all rank as below average defenders by DE%.

But how can we accurately identify if these players are better or worse defenders compared to average?

One method is by looking at the average points a player’s team concedes when they are playing 2nd Row. Here is the teams PPG conceded for defensive edges when listed at 2nd Row per Rugby League Project, ranked by DE%:

Rank Name PPGC (2nd Row) 1 S. Sorensen(CRO) 14.67 2 M. Aubusson(SYD) 9.67 3 M. Niukore(PAR) 21.00 4 F. Kaufusi(MEL) 15.67 5 M. Gillett(BRI) 20.40 6 R. Matterson(SYD) 15.69 7 I. Yeo(PEN) 19.00 8 M. Ma’u(PAR) 24.30 9 G. Cooper(NQL) 22.23 10 J. Jackson(CBY) 19.65 11 J. Stimson(MEL) 13.81 12 T. Moeroa(PAR) 20.50 13 A. Guerra(NEW) 24.66 14 T. Harris(WAR) 17.12 15 C. Lawrence(WST) 20.00 16 R. Faitala-Mariner(CBY) 20.46 17 J. Thompson(MAN) 25.92 18 V. Kikau(PEN) 18.48 19 T. Frizell(STI) 16.75 20 S. Lane(MAN) 25.92 21 T. Sims(STI) 18.04 22 B. Cordner(SYD) 14.64 23 I. Papali’i(WAR) 19.31 24 L. Fitzgibbon(NEW) 25.35 25 K. Capewell(CRO) 17.78 26 W. Graham(CRO) 18.78 27 A. Crichton(SOU) 18.40 28 R. Martin(CBY) 18.91 29 K. Proctor(GLD) 24.17 30 J. Su’a(BRI) 19.50 31 J. Sutton(SOU) 18.15 32 C. Hess(NQL) 21.74 33 C. Harawira-Naera(PEN) 17.11 34 R. Rochow(WST) 17.92 35 A. Glenn(BRI) 23.39 36 R. Hoffman(MEL) 16.82 37 E. Whitehead(CBR) 22.20 38 W. Matthews(GLD) 24.38 39 J. Tapine(CBR) 23.44 40 M. Barnett(NEW) 25.07 41 M. Chee Kam(WST) 19.45 42 T. Pangai Junior(BRI) 18.36 43 L. Lewis(CRO) 19.41 44 K. Hipgrave(GLD) 21.18

Players listed as above average defenders by DE% have a combined PPG conceded of 19.03 when playing 2nd Row. Players listed as below average by DE% have a combined PPG conceded of 20.49 when listed at 2nd Row. Interestingly, the average PPG conceded of the Top-10 in DE% when playing 2nd Row is 18.23, and the average PPG conceded of the bottom 10 in DE% when playing 2nd Row is 21.37. Defensive Efficiency accurately identified the edge defenders who contributed to an above-average defence – this is certainly significant and provides some clout to DE% as a metric for quantifying defenders. While identifying defenders who contribute towards a better defence is useful, it doesn’t confirm that these players were responsible for an improved defence. It’s possible that DE% has randomly assigned players from better defences at the top.

One of the easiest ways to confirm whether DE% has identified defenders responsible for defensive improvement is to look at how each team has performed while that player is not playing at 2nd Row. Unfortunately, on/off split data in Rugby League is not comprehensive and for some players we do not have an appropriate sample of games when they are off the field. There is also some noise in the data, even though a player is not listed at 2nd Row they are often playing some role within the team either off the bench or in a different position. Regardless, the data is still a valuable indicator of the impact each player has:

Rank Name Team PPGC (2nd Row) Team PPGC (Non-2nd R) Diff 1 S. Sorensen(CRO) 14.67 18.95 4.28 2 M. Aubusson(SYD) 9.67 15.57 5.90 3 M. Niukore(PAR) 21.00 24.26 3.26 4 F. Kaufusi(MEL) 15.67 14.84 -0.83 5 M. Gillett(BRI) 20.40 22.30 1.90 6 R. Matterson(SYD) 15.69 12.79 -2.90 7 I. Yeo(PEN) 19.00 8 M. Ma’u(PAR) 24.30 21.27 -3.03 9 G. Cooper(NQL) 22.23 10 J. Jackson(CBY) 19.65 11 J. Stimson(MEL) 13.81 17.91 4.10 12 T. Moeroa(PAR) 20.50 25.33 4.83 13 A. Guerra(NEW) 24.66 25.92 1.26 14 T. Harris(WAR) 17.12 22.88 5.76 15 C. Lawrence(WST) 20.00 20.00 0.00 16 R. Faitala-Mariner(CBY) 20.46 18.91 -1.55 17 J. Thompson(MAN) 25.92 18 V. Kikau(PEN) 18.48 20.43 1.95 19 T. Frizell(STI) 16.75 28.00 11.25 20 S. Lane(MAN) 25.92 25.90 -0.02 21 T. Sims(STI) 18.04 22 B. Cordner(SYD) 14.64 23 I. Papali’i(WAR) 19.31 18.34 -0.97 24 L. Fitzgibbon(NEW) 25.35 25 K. Capewell(CRO) 17.78 18.11 0.33 26 W. Graham(CRO) 18.78 16.44 -2.34 27 A. Crichton(SOU) 18.40 28 R. Martin(CBY) 18.91 20.46 1.55 29 K. Proctor(GLD) 24.17 30 J. Su’a(BRI) 19.50 23.54 4.04 31 J. Sutton(SOU) 18.15 32 C. Hess(NQL) 21.74 21.60 -0.14 33 C. Harawira-Naera(PEN) 17.11 16.67 -0.44 34 R. Rochow(WST) 17.92 20.41 2.49 35 A. Glenn(BRI) 23.39 18.14 -5.25 36 R. Hoffman(MEL) 16.82 13.20 -3.62 37 E. Whitehead(CBR) 22.20 38 W. Matthews(GLD) 24.38 24.19 -0.19 39 J. Tapine(CBR) 23.44 20.63 -2.82 40 M. Barnett(NEW) 25.07 25.60 0.53 41 M. Chee Kam(WST) 19.45 19.00 -0.45 42 T. Pangai Junior(BRI) 18.36 24.71 6.35 43 L. Lewis(CRO) 19.41 15.60 -3.81 44 K. Hipgrave(GLD) 21.18 26.85 5.67

The average difference for an above average DE% edge forward is 2.26 points per game, which is to say the teams overall defence is 2.26 points per game better when they are listed at 2nd Row. The average difference for a below average DE% edge forward when listed at 2nd Row is 0.06 points per game, essentially the same.

There is missing data in this sample – some edge forwards do not have an appropriate sample size without them at 2nd Row (5 games or more), while there are several edges without enough games to qualify for DE% initially.

Like any capture-all statistic, Defensive Efficiency does not accurately quantify every player – there are some players listed as below average who impact the defence positively, and some players listed as above average who impact the defence negatively, yet as a whole it accurately identified above and below average defenders for a position.

Having a defensive metric with real application to the game is important, however this should not overshadow the overwhelming impact defence, specifically on the edge can have on winning. One quality edge defender can contribute on average more than two points per game to a team’s defence, which in 2018 was the difference between the 3rd and 10th best in the NRL and often the difference between winning and losing. Only 1 below-average defensive team made the Top-8 in 2018 (Broncos). Looking further, the clear two best defences in the NRL this season (Sydney and Melbourne) had only 1 of 6 qualified edges ranked as below average by DE%, the retiring Ryan Hoffman.

On a macro-level, it’s also interesting to wonder how often a team’s struggles can be attributed to poor edge defence. There are 3 teams with 2 bottom 10 edge defenders by DE% in 2018. The Canberra Raiders who did not make the finals despite leading the league in PPG last season. The Gold Coast Titans who finished 14th in both defence and ladder position. The Brisbane Broncos who lost their best edge defender Matt Gillett 5 games into the season, finished 11th in defence and had the doors blown off in a home final by conceding 48 points. In many ways defence is more important than offence, and just like we credit halves for any offensive achievements, the same should be given to the edges on defence.

Teams and fans have often organically recognised the importance of determined defensive-minded players like Gavin Cooper, Josh Jackson and Manu Ma’u – and yet it’s possible they provide even more value than the most devout Rugby League experts realise. Their contribution goes largely unnoticed, and yet the impact they have on winning is supreme. Edge defenders are one of the most undervalued assets in the league, the important players that nobody talks about. If you’re a Sydney Roosters fan, the next time you see Mitchell Aubusson – thank him for the premiership.