A statistical look at some of the NRL’s most improved players of 2020

The 2020 regular season is winding down and there has been some talk about the most improved player in the NRL. It’s a great talking point for these later rounds as most games are dead rubbers. Are you really interested to watch the Queensland Toilet Bowl this Thursday evening?

The problem with examining players who have improved in the traditional way of looking at who scored more tries or who’s averaging more running metres this year is that it falls into the counting statistics trap. You have a number of statistical buckets. Every time you do something, a bucket fills up. If your bucket is filled with more “stuff”. If you have more “stuff” than last year, then you’re more improved!

But is that the case? The above approach only rewards players who play more games, or spend more time on the field, or have a change in role. What about players who are doing more with less, there by being more efficient?

One way we can do this is by looking at a players output on a per possession basis rather than just their raw volume. This way we can if they’re doing more or less with the ball every time they touch it, rather than just looking at the end result which may have come from twice as many handles of the ball.

Regular readers may remember that earlier this season I’d made a comparison between Shaun Johnson and Nathan Cleary, based on the fact that Johnson only touches the ball about 50 times per game, whilst Cleary averages about 75 possessions per game. By taking their per possession statistics and then normalising them by the same number of possessions, their per game output was remarkably similar.

Speaking of Cleary, he’s been bandied about as one of the more improved players this season. But if you look at his possession stats year on year, he’s doing more but not more efficiently. This year he’s averaged 75 touches, up nearly one third from 2019 (57 per game). As a result, other than line break and try assists, and kicking stats, almost every other statistic is down on a per possession basis for Cleary.

That’s not a knock either, as it’s obviously working for the minor premiers and only a fool would suggest Cleary isn’t anything other than the NRL’s best halfback for 2020. But if we’re talking per possession, then becoming “less efficient” isn’t an improvement. Is he doing more? Undoubtedly, just look at where the Panthers sit on the ladder. But more isn’t always more efficient and can falsely be equated with improvement.

So, for this exercise, we’re going to expand on the previous analysis and look at normalised (by position) per possession statistics for some players that I’ve identified who have had a marked increase in their output in 2020. By doing so we can see just how much their performance has changed by giving them the same level of possession as a baseline.

To use this method to look at who has improved, I’ve narrowed down a pool of NRL players who played in both 2019 and 2020 (sorry Jamal Fogarty), which ends up around 370 players. I’ve left out another 90 players who played fewer than 200 minutes in 2019 (sorry Tino Fa’asuamaleaui and Harry Grant), as their previous sample size was likely too small to draw any conclusions from. For clarity, I’m using publicly available data from Fox Sports.

Below is a table of just how many times per game certain positions touch the ball, broken down for 2019 and 2020 with a % change. This helps to show just how many times different positions get their hands on the ball, but also to highlights the increase in possession due to the set restart rule change.

Average possession per game by position, 2019 v 2020 seasons

One thing that needs to be considered is the increase in time in play due to the set restart change. Time in play is up by at least 5%, possessions are up 6%, runs are up 5% and run metres are up 4%. Interestingly average metres per run are down 1.6%. Everyone is running more but overall, not as far.

Given this, most players will likely see an increase in runs and run metres thanks to the ball being in play more often. If you’re seeing anyone with a “career high” average in runs or metres or the like, that isn’t higher than the percentages above it is most likely not an increased output.

There are also some players who’ve put up ridiculous increases in some statistics this year due to a change in role. Cameron McInnes is a great example. He played almost exclusively at hooker in 2019, but for 2020 has adapted to more of a running forward role in conjunction with time at dummy half. As a result, his runs per possession are up 330%, and his run metres are up 248%. Not improved, just a change in role.

This is more an indictment of how little hookers are running the ball than necessarily any improvement in McInnes’ game.  As a result, players like McInnes who have moved between positions that dramatically alter their statistical output have so been excluded. Jarome Luai would be another, who spent most of 2019 as an interchange player before graduating to a full time five eight in 2020, with his minutes and possessions each increasing by over 100%. It’s not like for like so he’s unfortunately excluded from this list.

The one downside is that normalising players output on a per possession basis takes any defensive performance out of the equation. That’s not necessarily a bad thing, as there’s fewer defensive As a statistics available and it’s not an aspect of the game that can easily be quantified by treating player individually. After all, you can’t miss a tackle if you’re so far out of position that you can’t attempt one. So, for this exercise I’ve used the Eye Testtm to rule out a few players from the most improved list since I can’t quantify it easily (sorry Matt Dufty and Kotoni Staggs).

With that out of the way, let’s look at a a number of players that have made significant statistical improvements on a per possession basis, normalised by the average possessions at the position they play.

Dylan Brown, Parramatta

It’s not much of a coincidence that the Eels struggles this season traced back to when Brown suffered his season ending injury. He was an integral part of the Eels attack this season, touching the ball 25% more than he did in 2019 as Parramatta favoured his left side of the field. The increase in possessions weren’t used to increase his playmaking role (both passes and offloads were down per possession on 2019), but to showcase his damaging running game.

Even with the increase in possession, Brown sported double figure increases in runs and run metres, with a breathtaking 170% increase in tackle busts per possession. Unsurprisingly this led to significant jumps in tries per possession (+30%) and line breaks per possession (+95%). He also took on more of a kicking role as well, increasing by 55% through both long kicks (+114%) and attacking kicks (+37%). All this shows just how vital he was to the Eels game plan this season and his presence has been sorely missed. And that’s not even taking into account one of his overlooked abilities, usually underdeveloped in young half – his defense. But as stated we’re not able to quantify that as easily so we only have the Eye Testtm to use there, and he’s definitely above a passing grade.

Taniela Paseka, Manly

With both Manly starting front rowers missing time this season and the Sea Eagles sporting a thin interchange bench, Paseka has been required to increase his time on field in 2020 (28 minutes per game to over 34). He’s also getting more involved, with a 32% increase in touches per game, from 8.3 to 10.9. This increase in role has seen his numbers explode across the board as you can see from the above table.

Runs (+6%), run metres (12.1%) metres per run (5.7%) and tackle busts (+35%) are the bread and butter of a middle forward and Paseka has seen steady increases in those statistics. But it’s the improvement of other aspects of his game that have made him stand out. He’s become more of a passer and creator for the Sea Eagles, with a 360% increase in offloads per possession and triple digit increase in general passing. The most pleasing part of this is that it hasn’t come at the expense of his ball security, with Paseka’s per possession error rate down 75%. As the club prepares for current starting prop Addin Fonua-Blake to depart, Paseka has shown he can more than handle the load.

AJ Brimson, Gold Coast

After a nasty back injury, Brimson has made a full time move to the #1 jersey in 2020 and he’s been an integral part of their late season improvement. He’s played the full eighty minutes in every game this season after averaging 68 per game last year, and his involvement has increased slightly as well from 26.1 touches to 30.4 per game. With less time spent in the halves, he’s distributing the ball less but running more, with runs (+3%), metres (+30%) and metres per run (+26%) all showing dramatic improvement over 2019.

His ability to break the line and set up for others has been another marked expansion of his game with an 182% increase in tries per possession, and triple figure increases in try and line break assists. He’s also taking on some of the hard work this season, as his one pass runs have increased by 26%, and he’s busting tackles at a significantly higher rate as well (+35%). With two new star signings and having Brimson and Fogarty at the start of the season the Titans look to be one of the darlings of the 2021 season.

Sione Katoa, Cronulla

The Sharks are headed to the finals this season, and Katoa has been one of the few constants in a backline ravaged by injuries. With wingers usually playing the full 80 minutes his time on field hasn’t changed a lot, and his possessions per game are only up 10% on 2019, from 15.2 to 17. It’s what he’s doing with them though that is making a difference for Cronulla.

Katoa is running the ball 10% more per possession and producing almost 4% more run metres on the back of runs  with a distance of 8 metres or more increasing by 13%. He’s also taking a lot more basic hitups, with one pass runs up 30% per possession, and also offloading the ball slightly more (+5%) even though his general passing is marginally down. It seems like Katoa is picking his spots better as well, with errors declining by 26% despite offloading more, which usually leads to an increase in errors.

The biggest change in his game this year though is the ability to get over the line. Sure, it helps when you have Shaun Johnson playing inside of you whilst having one of his best seasons as well, but Katoa has emerged as one of the best finishers in the NRL. He’s scored 15 tries in his 17 games this season, which is an increase of 39% on a per possession basis. Line breaks are up by 33% too as they tend to go hand in hand with tries. How he’ll fare in 2021 will be interesting to watch as Johnson will likely out the entire season (or at best the majority of it) due to a devastating Achilles injury.  

Moses Leota, Penrith

Leota has been an important factor in Penrith’s ability to push through the middle this season. His minutes are up only slightly (an extra 2 minutes per game), and his possessions are actually down this season (-3.2%). His impact off the bench has been notable, with 15% fewer runs that were shorted than 7 metres, and 30% more that were longer than 8 metres.

He has seen double digit increases in runs per possession (+11%), run metres (+24%) and metres per run (+12%). His passes and offloads are down, as he’s playing a more basic game through the middle now. This has resulted in offloads and passes declining (-73% and -55% respectively), but it’s also meant the errors have come out of his game (-53%).

Jordan Pereira, St George Illawarra

Whilst he hasn’t had the same highlight season as the Dragons other winger, Pereira has been one of the most consistent Dragons all season. And he’s done all of this without being able to cross the line, with just one try this season and none since Round 6. He’s still been an excellent contributor, only seeing a 1% increase in touches this season and pumping out an additional 18% more metres per possession than last year.

And it’s not just short runs either – his metres per run are up 16% and runs longer than 8 metres have increased by more than 24%. He’s one of the hardest working wingers in the NRL, sitting 6th among all backs (including fullbacks) for total one pass hit ups, constantly helping the Dragons return the ball out of their own area. If he’d only been able to cross the line a few times this season he’d be snaring more headlines.

Sitili Tupouniua, Sydney Roosters

He’s reaped the benefits of playing on the best side in the NRL (ladder position notwithstanding), and whilst you could use that to refute his improvement, you’re not going to post increases like Tupouniua has without effort. With the injury toll the Roosters have suffered, he’s had to play an increased role, jumping up from nearly 30 minutes per game up to over 57, with a related 55% increase in touches (6.4 per game up to 9.7)

It has affected his running stats, with runs (-15.5%), run metres (-23.9% and metres per run (–9.9%) all suffering on a per possession basis but in doing so he’s become a much more damaging situational ball carrier. When you consider how many metres the Roosters get from their backs, James Tedesco especially, it’s less of a reflection on Tupouniua than how the Roosters play.

His offloads are up nearly 24%, and tackle busts have improved a similar increase (+29%), showing he’s moved from a one-dimensional meter gaining runner of the ball. Tupouniua has had a knack for finding the line this season (+209% per possession) but only has a 3% increase in line breaks, indicating that the Roosters may have found that the best situation to use him in is close to the line where he can crash over and not further out.

Luciano Leilua, Wests Tigers

The younger Leilua joined the Tigers this season from the Dragons and has developed into a damaging 80-minute edge forward. His minutes have shot up from 41 per game to 78, but hasn’t seen a corresponding increase in touches, going from 11.7 to 13.8 per game. Yet on a per possession basis, he has expanded his running game.

Runs per possession are up 20%, with run metres up 11%. His metres per run have declined slightly, down to 8.2% form 9.2%, which is also shown by a sizable 64% increase in his runs of less than 7 metres. It’s a Tigers wide problem as I’ve noted twice previously. He’s also been one of the few Wests players that has shown the ability to break through the line, as he’s nearly doubled his try scoring output per possession. With some additions to their middle forward rotation in 2021, the Tigers might have the go forward required to create more space for Leilua to cause more havoc down the left edge.   

Sam Stone, Gold Coast

Another player who hasn’t been playing the full season for the Titans but given his improvements over 2019 he could be playing a larger role in 2021. Stone hasn’t seen a substantial increase in minutes (68 to 71) and his per game possessions have dropped 20%. Yet almost all of his per possession statistics have seen growth on last season. He’s running the ball 7% more, resulting in 29 % more metres and an increase of 20% on his run per metre average (7.3 metres per carry to 8.8).

Stone is also busting tackles at an incredible rate compared to last season (+106%) which is leading to longer runs, with those greater than 8 metres up 9%. He’s not a stimulating choice from a marketing point of view, but the Titans and their fans should be very happy with his progress after joining the club from Newcastle.

Honourable mentions – Peta Hiku, Brian To’o, Dylan Edwards, Brett Morris, Regan Campbell-Gillard, Thomas Burgess, Daniel Saifiti, Jahrome Hughes, Blake Lawrie, Jack Wighton.

NRL Round 19 advanced stats – Involvement Rate

Involvement Rate is an advanced statistic for rugby league that I created to identify players who have a high workload but don’t play a lot of minutes. If you’re new to the site and want to understand how it works, I would recommend reading this post on Involvement Rate.

With that out of the way, here’s the all minutes leaders for Round 19

After leading the Tackle % chart, it’s no surprise to see North Queensland’s Emry Pere first for Involvement Rate as well, at 30.33% for the round. This indicates he made a run or completed a tackle on 30.33% of all plays during the Cowboys loss to Penrith.

Second place was Warriors debutant Tom Ale who had an Involvement Rate of nearly 28% in his 12 minutes, whilst Andrew Fifita

Next, we’ll look at those players who spent 40 minutes or more on field in Round 19.

As with Tackle % the leader takes the cake again here. New Zealand’s Lachlan Burr is in first with an Involvement Rate of 26.41%. The Sharks Toby Rudolf nabbed second spot with a rate of 23.32% while the Roosters Lindsay Collins rounds out the top three at 23.17%.

Patrick Carrigan is the only 80 minute player in the leader board this week with an Involvement Rate of 20.12% as the Broncos lost again to the Eels.

Finally, we have the leaders for Involvement Rate for 2020 with one game remaining.

With Jaimin Jolliffe not playing for the Gold Coast this round he still sits first at 21.93%, with New Zealand’s Jazz Tevaga not far behind at 21.69%. The Titans Jarrod Wallace preserves his third spot at 21.39% but has Blake Lawrie from the Dragons breathing down neck, just 0.03% behind at 21.36%.

There’s another five players sitting just behind Lawrie between 21.24% and 21.13%, and any one of them could move into the podium with a high workload game in Round 20.

NRL Round 19 advanced stats – Tackle %

Let’s skip the intro – if you’re new to the site, I’d recommend reading this post on Tackle %, which explains how it works and why I think it’s an important statistic for identifying high motor middle and interchange forwards.

Here’s how the Tackle % chart looked for Round 19 without a minute restriction

No single digit minute shenanigans this week. The Cowboys Emry Pere takes top spot with a Tackle % of 46.58%, indicating he completed a tackle on nearly half of the possession his team defended whilst Pere was on the field.

Second and third place goes to a pair of Warriors, and sadly one wasn’t Daniel Alvaro. Lachlan Burr took second place with a tackle rate of 43.94% and debutant Tom Ale at 41.67%. Ale completed 9 tackles in his 12 minutes.

Sam McIntyre (40.55%) from the Wests Tigers was the only other player above 40% this round.

Next, we’ll look at those players who spent at least half a game on the field this round

Burr takes top spot for those who played at least 40 minutes, with his tackle rate of 43.93%. One of the NRL’s most improved players Moses Leota from Penrith grabbed second spot with a Tackle % of 35.63%. Jacob Saifiti takes third place as the Knights prop posted a tackle rate of 33.93% in his 41 minutes on field during their win over the Dragons.

There was a number of 80 minute hookers making this list this week – Penrith’s Mitch Kenny (31.61%), North Queensland’s Reuben Cotter (30.98%) and South’s Damien Cook (28.50%).

Finally, here is the 2020 season leader board for Tackle % with one round to go.

No movement in the top three, with Nathan Peats (34.08%), Mitch Rein (33.22%) and Elijah Taylor (32.28%) sitting in the same spots as last week and unlikely to change with one game remaining.

Want to also wish fourth placed Tim Glasby (31.75%) the best in his post NRL career.

NRL Round 19 advanced stats – Run %

For those new to the site, I’d recommend reading this post on Run % which details how it is calculated and how to use it.

Here’s the leading players in the NRL after Round 19 without a minute restriction

Zane Musgrove led the way this round with a Tackle % of 25.81%, meaning he completed a run on over a quarter of all plays the Tigers had whilst he was on the field. The remainder of the top three comprised of Souths’ Mark Nicholls (21.64%) and season leader Cronulla’s Andrew Fifita (20.88%).

Abbas Miski takes the spot for top back this round, playing 18 minutes and making six runs for a Run % of 18.65% after coming on to the field as an interchange player. Charnze Nicoll-Klokstad of the Raiders was the only other back in the top 20 with a run rate of 13.19% in his 80 minutes.

Moving on, let’s look at the 40 minute plus players for this round.

Musgrove’s teammate Josh Aloiai placed first among high minute players with a run rate of 19.05% and will be sorely missed by the Tigers next season as he recovers from injury. The Gold Coast’s Jarrod Wallace placed second with a Run % of 18.23% whilst Daniel Saifiti showed no lingering affects of injury with a Run % of 17.28% in 43 minutes.

The Sea Eagles’ Curtis Sironen was the only 80-minute player inside the top 20 this round, with a run rate of 14.69%, coming from 21 runs.

To finish up we’ll take a look at the 2020 season leaders for Run % with one round to go.

As mentioned above, Fifita is the season leader and looks like going unchallenged for the remainder of the season as he sits with a 2020 Run % of 18.12%. Melbourne’s Nelson Asofa-Solomona still occupies second place at 16.50% and is too far behind to close the gap with one game remaining. The Eels Kane Evans maintains third spot with a run rate for the season of 16.24%.

There’s a huge gap of nearly 1.5% then to fourth place, which is Jason Taumalolo (14.87%) of the Cowboys who returned on the weekend in limited minutes.

Does regular season performance dictate finals success? – NRL Round 18 2021 stats and trends

Last week Rugby League Analytics posted a fantastic visualisation of points for versus points against for every Super League team since 1996, which showed that the majority of teams that either topped the table or won the grand final sit in the bottom right quadrant. This quadrant contains high scoring teams with great defense, which makes perfect sense. Below is the tweet, please give them a follow if you’re into Super League or analytics for the sport.

This led me to wonder if the same trend was evident in the NRL era (1998-2020). Did each Grand Final contain only the best attacking teams who could also defend, or were there some outliers who made to the grand final (or even won it) despite having obvious weaknesses in defense or attack?

First lets define what we’re looking at. The below scatter plot shows every team in the NRL era, and their average points scored plotted against their average points conceded. All data Is taken from The Rugby League Project, the best rugby league resource on the internet.

I’ve changed the legend up a little bit from Rugby League Anlaytics colour coding, adding a few extra segments. It’s a little bit busier but it allows a greater level of analysis. How they finished the season is still colour coded – pink for winning the grand final and minor premiership, purple for winning the minor premiership but losing the grand final, orange for grand final winners only, red for grand loser, blue for winning the minor premiership only, yellow for a top 8 finish and green for no finals played.

For simplicity sake I’m going to include the discarded grand final wins by Melbourne, which as an Eels fan is pretty painful. Additionally, the “Top 8” moniker is a proxy for finals, I am aware there was a 10 team final series in 1998.

Now we know what data we’re looking at, lets have a look at the overall picture before breaking it down into segments.

Just like the above chart from Rugby League Analytics, this one has four quadrants. Moving clockwise from the top left have: bad defense/bad attack, bad defense/good attack, good attack/good defense, and good defense and bad attack. Most of the teams sit in the bad defense/bad attack and good defense/good attack quadrants with a few outliers sitting in the other quadrants.

It’s quite clear from that the successful teams look to be sitting in the bottom right quadrant which is the good defense/good attack area. But from an initial glance there are some grand finalists and top 8 teams sitting outside that quadrant. Let’s take a deeper look and see who the were and if it might give some indication of what could happen this season.

Firstly let’s look at those those teams who achieved the minor premiership and grand final win double, the pink data points below.

No team that has achieved this double had a bad attack or bad defense, except for the mythical 2003 Penrith team that defeated the Roosters with that Scott Sattler tackle.

Next up those minor premiers who didn’t win the grand final, the purple data points in the below chart.

There’s been seven instances of the minor premier making the grand final and losing, and not one of them had anythong other than a combination of good defense/good attack.

What about teams who just won the minor premiership but didn’t make the grand final (the blue data points)?

Again relatively straight forward here – no team that was minor premier but didn’t make the grand final in the last 22 years has had bad defense or bad attack. Again, this is logical, since taking the minor premiership requires a season of consistently good results. I’ve also assumed Penrith wins the minor premiership here with a three point lead with two rounds remaining.

Lets look at grand final winners next, shown in orange.

Of the 22 grand final winners over the past 22 seasons just five of them have come from outside the bottom right good attack/good defense quadrant. The exceptions fall into two groups – historically elite teams like the 2006 Broncos and the 2009 Storm (*cough*), or high scoring teams with a transcend star half. There’s something else those latter two who could score easily have in common and we’ll get to that in shortly.

Now we’ll have a look at grand finalists only, coloured red.

It’s a similar tale, with the majority of losing grand final teams also sitting in the good defense/good attack quadrant. The lone side that lost a grand final despite bad defense was North Queensland in 2005, which also included another team with “bad defense”, the Wests Tigers. Otherwise every grand final team at least had good defense, indicating that at least having a strong defense gives you a chance of making the grand final.

The other thing to note is that those grand finalists within the bad defense/good attack quadrant all occurred before 2006, which is an eternity ago. In the current NRL era, if you don’t have an elite defense you’re not making the grand finals. Pre 2006 NRL seems to be the wild west where you could simply try to outscore a team before the banality of modern NRL where coaches refuse to take any risks and would rather lose a low scoring game than try to win a high scoring one. How good are endless block plays.

Moving on, next we’ll look at teams who played finals football, shown as yellow in the chart below.

This one has a wider spread, although again the majority of teams playing in September had a quality defense, or at least were able to put points on the board. There were a few outliers, with the “worst” team to make the finals being the Canberra Raiders of 2002 who made it in with 10 wins, 13 losses and one draw, and a points differential of -170, sitting well inside the bad defense/bad attack segment.

Let’s flip things now and look at teams who didn’t make the finals, represented by the green data points.

This provides a slightly clearer picture, as teams who have both good attack and defense usually make the postseason. The two “best” teams who didn’t make the finals were the 2002 Bulldogs who were stripped of 37 points, and the 1999 Canberra Raiders. Coincidentally the 1999 Raiders were almost an exact mirror of the 2002 Raiders – 13 wins, 10 losses, 1 draw and a +173 points differential.

After looking at all of this, now we know that you’re unlikely to make the top eight without a good defense, and you’re even more unlikely to make the grand final unless you have a good attack and good defense, where do teams sit for the 2020 season? Here’s the last 22 years with 1998-2019 in blue, with the 2020 season in orange.

The three raging favourites for the 2020 title – Melbourne, Sydney and Penrith –understandably sit in the important bottom right quadrant. The other top four team, Parramatta have sit in the good defense/bad attack quadrant, which was epitomised in the Eels inability to cross the line against Penrith on Friday despite being able to withstand a torrent of pressure in the first half. Both Canberra and Newcastle also sit in this quadrant, signifying that they are also unlikely to feature on the final weekend of the season.

The Knights are nearly inside the quadrant but given their wildly inconsistent results you wouldn’t give them much of a chance even if they were. Of those three Canberra would be the most likely th crash the party and make it to the grand final.

The team I haven’t mentioned yet is one that could be a smokey a grand final win this season – South Sydney. Despite sitting currently in sixth place, they are the only other team besides the top three that sits in the favourable good defense/good attack quadrant. The loss of Latrell Mitchell definitely hurts, but the Rabbitohs have the foundation of a side that could challenge for the title. They aren’t as deep into that quadrant as the other three, but they had started to gain momentum at the right end of the season.

It’s a bit of stating the obvious that there’s only a handful of teams who look like serious contenders this season, but as I’ve stated before analytics is the art of being less wrong . By looking at teams in this lense, we’ve been able to practically eliminate Newcastle, Parramatta and Canberra as legitimate contenders, although the Eye Testtm would have eliminated the Eels a few rounds back and Newcastle would have never been in the conversation.

It’s also shown that you need an elite defense to be even in the hunt for a title, and the most likely grand final winners are coming from Melbourne, Sydney, and Penrith. The final key point is that Souths are a potential dark horse for the title but will face a battle without Mitchell as their defence and attack are good but not on the same level as the other three contenders.

Are the top four running the ball more consistently?

Over the past few weeks, I’ve been delving into the total metres and pre/post contact metres splits of teams in the NRL with a focus on the Wests Tigers, since they’re having issues promoting the ball lately. To get you up to speed here’s the update after Round 18 for pre/post contact run metres for starting forwards and interchange players.

Wests still have the fewest average pre contact and average total run metres by forwards and interchange player and have the third least average post contact metres. On the other end Penrith have the most post contact and are second in total and pre contact metres. This led me to wonder, are the top sides this season consistently gaining metres?

The below chart shows the total run metres per round for 2020 by all sixteen NRL clubs, with a reference line across the middle showing their average run metres, and a 95% confidence interval (95% certain of the true mean sitting in this range) either side.

At first glance you can see that there is more consistency in run metres from some of the top teams. Melbourne, Sydney, Penrith, Souths and Parramatta are either above the line or very close to their average most weeks. Souths notably started the season poorly but have had a strong run of late, while Parramatta were running the ball more effectively earlier in the season but have dropped off considerably of late, which is concerning considering their injuries are to positions that don’t usually run the ball often (Dylan Brown and Reed Mahoney).

Teams who are struggling this season tend to have wilder fluctuations in their total running metres. Brisbane tend to swing wildly above and below their season average, as do North Queensland and the Warriors. The Gold Coast had some very low points early in the season, but their turn around in form has seen them only dip below their season average once since Round 12. And you also have the Tigers, who finally had a game close to their season average after back to back games where they couldn’t move the ball.

One thing to consider here is that we’re looking at total metres gained during a game. What if we looked at just pre or post contact metres? Would that show anything different? Historically pre contact metres correlate better with scoring points, whilst pre-contact metres correlate more with a higher margin.

Above is the same chart but just for pre contact metres. Turns out there’s not a lot of difference, just some of the peaks and valleys are smoothed out a little bit. That makes sense as around two thirds of total run metres come from pre contact metres, with the other third coming from post contact metres.

So, what do you see when you look at post contact metres only?

It’s quite different! Even a team like Brisbane that was struggling has some massive spikes for pre contact metres. The issue, like other bad teams, is that they lose big when they’re not able to generate metres after contact. The erratic season Newcastle is having can be seen here, alternating from high to low post contact metres on a weekly basis over the past two months.

Penrith has seen a huge uptick in post contact metres in the last month when they’ve been lapping teams. Souths have only had one game below their season average in post contact metres since Round 8, which came against Melbourne. Parramatta had been excellent at pushing through contact earlier in the season but that has waned of late.

There is one notable exception to this rule and that seems to be the Roosters, whose run consistency profile shares more with the bottom eight than the top eight. One theory behind this could be that they’re incredibly good at creating space for their outside backs and putting players into huge gaps in the defense doesn’t actually generate post contact metres because they’re not getting touched in the first place.

#BIGMANSZN kicking stats

Round 18 was a bonanza for middle forwards moving out of their wheelhouse and trying their chances with a kick. First up was Tom Burgess on Thursday night against the Tigers forcing a line drop out with this deft touch that you can see in the below video:

Second was Martin Taupau kicking and regathering (eventually) for himself against the Bulldogs on Friday Night.

Based on this, I wanted to look and see which forwards had been kicking the ball this season. Most other positions generally have a licence to kick the ball when needed, with middle forwards generally on a tight leash. I’ve also removed second rowers as well, since Wade Graham has kicked over 20 times this season. Below is the table of kicks by middle forwards this season.

This season Adam Elliot from Canterbury leads the way among middle forwards with four kicks and one forced drop out. Des Hasler seems to have the longest leash on his middles, with both Taupau and Jake Trbojevic kicking three times each this season, but without any forced dropouts. The only other forced dropout this season by a middle forward was by the Panthers James Tamou.

So we really did see something of a unicorn on the weekend. Let’s hope we see more of it #bigmanszn.

Net Points Responsible For Round 18 update

Net Points Responsible For (NPRF) is a statistic I put together to track the contributions by playmakers for their team that isn’t always shown in raw numbers for try assists. By including the try contribution statistic that Fox Sports uses it brings in players who don’t necessarily throw the deciding pass for a try. I’d first brought it up earlier in the season in this post, highlighting how well Jahrome Hughes was playing.

Players like Nathan Cleary, Brett Morris, James Tedesco, and Luke Keary show up on the the leaderboards for try scoring or try assists, but that doesn’t always provide a true measure of their worth. And given that defense is just as important in rugby league, I’ve deducted four points for every try cause allocated to a player to use as weighting of their defense.

Here is the calculation for NPRF – tries *4 + try assists *4 + try contributions *4 + field goals but adds in a negative four points for every try caused.

Now that we’ve explained it, let’s look at the top 20 players for NPRF after Round 18:

Nathan Cleary still leads the way but has dropped under 10 points added per game for Penrith. His halves partner, Jarome Luai has been exceptional of late and is adding another 5.6 points per game himself and is one of just eight players have a NPRF of more than 5 points per game.

Let’s not forget that Shaun Johnson has been exception despite allegedly “not doing enough” a month or two ago, and Hughes is still having a very good season.

Here’s the bottom 20:

As you’d expect, the majority of this bottom portion of the NPRF table is littered with Broncos, Cowboys and Titans. Jesse Arthars was the worst this season, giving away 10 try causes in just five games for a NPRF of -6.4 per game. Ouch.

The Eels struggles of late down their right edge is seen here too with Blake Ferguson sitting inside the bottom 10, giving away 3.06 points per game. He’s one of the few players in this list to be playing for a top four side, the other notable one being Ryan Hall at -2.4 per game.

If you scan both lists, the one thing that jumps out (especially in the top 20) is the lack of forwards. Other than Cameron Smith, every player in the top 20 is a back or half.

Regular readers will know one of my key tenets is that you (usually) can’t compare players across positions in rugby league as players perform very different roles. With that in mind, lets look at the top 20 players for NPRF filtered purely for forwards, and by forwards, I mean their regular or default position and not named position, as utility interchanges would dominate this list otherwise.

The one thing I like about looking at Net Points Responsible For this way is that it isn’t just hookers leading the way, there’s a smattering of edge and middle forwards as well. A few key takeaways from this list:

– Cameron Smith is in a class of his own as a hooker even at 37, but it’s clear he’s more halfback than hooker with the ball contributing nearly 6 net points per game.

– Tom Startling is having an incredible season for the Raiders, and it’s a crime he wasn’t starting sooner. The return of John Bateman also has played a huge part in their strong recent form, with both players part of the six forwards who have a NPRF average higher than 2.

– Warriors rookie Eliesa Katoa was an incredibly damaging runner for the Warriors, at least when he was fully fit and not carrying injuries into games, adding 2.33 points per game.

And finally, we’ll take a look at the bottom 20 for NPRF segmented for forwards only this season.

Here we have the Eye Testtm confirmed, Bryce Cartwright is quantifiably the worst defensive forward in the NRL, with he only player in the league averaging over 2 per game conceded. A number of Broncos also make up the top five, along with another reported turnstile in Coen Hess.

It’s also worth nothing is that volumes of tackles don’t equate to quality defense, as Cameron McInnes’ appearance on this list would show. And I wonder how long Josh Jackson will continue to live of his good defensive reputation that was acquired in 2015?