NRL Round 15 advanced statistics – Inolvement 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. Traditional rugby league statistics are counting stats and volume based, and the important work of middle and interchange forwards in the NRL goes largely unrecognised.

If you’re new to the site and want to understand how it works, I would recommend reading this post on Involvement Rate. To put it simply, it is a combination of Run % and Tackle % which shows the estimated percentage of plays that someone completed a run or tackle during their time on field.

Adjusting for minutes played and times helps identify those middle and interchange forwards who play with a high motor but don’t play huge minutes. Think Daniel Alvaro, Christian Welch, Blake Lawrie, Moeaki Fotuaika, Toby Rudolf and Francis Molo.

With that out of the way, here’s the all minutes leaders for Round 15:

Jai Whitbread from the Titans takes first place for Involvement Rate this week, and at 29.03% means he either completed a run or tackle on nearly three in every ten plays whilst he was on the field against the Raiders.

Eye Testtm Hall of Famer Daniel Alvaro was second for the second straight week with an Involvement Rate of 25.90%. His loan at the Warriors has been extended for another week, so hopefully we see him feature once more before he heads back to the Eels. Alvaro’s Warrior’s teammate Lachlan Burr rounded out the top three for Involvement Rate of 25.43%

Next we’ll look at those players who spent 40 minutes or more on field

The Titans do it again, with Jarrod Wallace nailing down first spot with an Involvement Rate of 24.02%, meaning he completed a run or tackle on nearly a quarter of all plays whilst he was on the field.

To show just how little running with the ball modern hookers do, Danny Levi placed second this week with an Involvement Rate of 22.83%, after smashing the field with a Tackle % of 48%. His 42 Involvements included 40 tackles and two runs. This lack of running usually makes it hard for dummy halves to feature in the Involvement Rate leaders without a mammoth effort in defense, which Levi had this round.

Third place was another New Zealand Warrior, with rookie Jamayne Tanoua-Brown sporting an Involvement Rate of 22.28%.

Finally, we have the leaders for Involvement Rate the 2020 NRL season.

Thanks to playing a huge game at lock in place of Jai Arrow, Jarrod Wallace has reclaimed spot for Involvement Rate at 22.65% after Jazz Tevaga surged into first place last round. Tevaga is still in second and not far behind at 22.45%. Titans rookie Jaimin Jolliffe completes the top three with an Involvement Rate of 22.26%.

Lachlan Burr has made a late run into third place with an Involvement Rate of 21.07%, but it’s unlikely that Burr or any of the next half dozen players hovering around 21% can make a run at the top three. Moses Leota from the Panthers would be the most likely, with an Involvement Rate of 21.68% sitting just the closest to Jolliffe.

NRL Round 15 advanced statistics – Tackle %

Tackle % is one of three advanced statistics that I’ve created to look at player performance throughout the NRL season. 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.

The idea behind it is that most tackle statistics you see are just based on volume, and mainly highlight players like Jake Friend who make a massive amount of tackles or play large minutes. Most middle forwards and interchange players play limited minutes and wouldn’t ever show up on a top tackle chart.

Adjusting for minutes played and times helps identify those middle and interchange forwards who play with a high motor but don’t play huge minutes. Daniel Alvaro has been the king of this statistic previously, owning two of the three highest Tackle % rates over the past six NRL seasons, both at around 38%.

Here’s how the Tackle % chart looked for Round 15 without a minute restriction

A Manly player topped the list for Tackle %, as you’d expect if you watched the game and saw how much defense the Sea Eagles had to do. Danny Levi had a tackle rate of 48.31%, meaning he completed a tackle on nearly half of the defensive plays Manly faced whilst on the field, which is an insane amount of work. Looking back this season and it’s rare for a player playing more than 30 minutes to have a Tackle % over 40% let alone close to 50%, and let alone in more than 45 minutes.  His team mate Sean Keppie also featured in the top 10 with a Tackle % of 39%.

The other Sione Katoa from the Bulldogs (45.13%) and Jai Whitbread (44.83%) from the Titans were the only other players to pass 40% this round.

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

Again, no surprises that Levi topped this list too with the volume of tackles he had to make. You can see the difference in workrate needed between Levi and his teammate Jake Trbojevic, who made just 6 more tackles despite playing another 34 minutes. Both defended through the middle yet Levi’s Tackle % dwarfs Trbojevic, 48.31% to 31.94%.

North Queenslands Jake Granville takes second spot at 38.65% and Jarrod Wallace of the Gold Coast placed third with 36.83%.

Canterbury had three players in the top ten this week  – Aiden Tolman (35.95%), Sauaso Sue (35.73%) and Jeremy Marshall-King (32.25%), while Phoenix Crossland (27.39%) from the Knights snuck into the top 20 due to a reshuffle after Blake Green’s unfortunately knee injury.

Finally, here is the 2020 season leader board for Tackle %

The Titans continue their stranglehold on the top three for this advanced statistic, despite their improvements of late. They may be putting more points on the board but they’re still doing a lot of defending. Jarrod Wallace maintains first with 35.05%, whilst Nathan Peats (34.08%) and rookie Jaimin Jolliffe (32.40%) places third. Jolliffe’s continued efforts have been rewarded with a new two year deal with the club, and with the work rate numbers he’s putting up it’s not surprising.

Late starters to the season Jazz Tevaga (30.92%), Tom Starling (30.54%) and Lachlan Burr (30.32%) are moving up this list of late but are unlikely to push the top three.

NRL Round 15 advanced statistics – Run %

With Round 15 complete it’s time to look at one of my advanced statistics, 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.

To summarise, it estimtes the percentage of runs that a player made during his time on the field, adjusted for an estimate of how many times thier team had the ball. After all, you can only run the ball if you team possesses it. More possessions usually results in more runs.

The idea behind it is that most statistics about runs are volume based, so you will only ever see high minute players. Adjusting for minutes played and times helps identify those middle and interchange forwards who play with a high motor but don’t play huge minutes. Think Neslon Asofa-Solomona, Christian Welch, Blake Lawrie, Moeaki Fotuaika and Francis Molo.

Here’s the leading players in the NRL after Round 15 without a minute restriction:

It shouldn’t be any surprise to see the list headed by two Souths players after their demolition of Manly on the weekend. Patrick Mago takes top stop with a Run % of 31.8%, meaning he made a run on more than three in ten plays that Souths had the ball on during the game. Tevita Tatola was next, but his Run % was nearly 10% lower than Mago’s, at 22%. The Knights Josh King completes the top three for the round at 21.15%.

There were two other Souths players in the top 10 – Kurt Dillon (20.37%) and Keaon Koloamatangi (18.16%). Again, that is not shocking considering the massive amount of possession that Souths had.

Moving on, lets look at the 40 minute plus players for Round 15:

This makes it two weeks in a row for Tevita Tatola, and increased from the 19% that led last round to 22.2% this week. Canberra’s Ryan Sutton (18.89%) splits Tatola and Koloamatangi in the top three.

Roger Tuviasa-Scheck was the only non-forward in the Run % top 20 this week at 13.25%.

To finish up we’ll take a look at the 2020 season leaders for Run %.

Nelson Asofa-Solomona is still holding on to first place, but his season Run % as dropped from 17.6% to 17.1%. Kane Evans played just 23 minutes last week against Melbourne and now two minutes outside the season limit I’ve set (250), which means Penrith’s James Tamou (15.49%) takes second for now. As long as he takes the field though Evans will move back into second spot last week with his Run % sitting not far behind Asofa-Solomona at 16.97%. It could end up being a close race after all.

North Queensland’s Francis Molo takes third at 15.44% but Cronulla’s Royce Hunt is rocketing up the list into fourth with a Run % of 15.14%. A few more high impact games from Hunt to finish 2020 could see him end up in the Top 3.

Which teams are driving the change in kicking tactics? – NRL Round 15 2020 stats and trends

In last weeks’ post, I proposed a theory that NRL teams this season were changing their tactics from using weighted kicks to look for repeat sets to more attacking kicks aimed outside the try line. The first reason was to take advantage of the new rules protecting attacking players in the air. The second was to reduce the number of seven tackle sets from kicks going dead in goal.

This week, I wanted to see if there were any teams driving this change. Turns out there are, and it’s mostly who you would expect but not necessarily how you’d expect it.

As mentioned last week with the increase in time in play there should be more “stuff” being done – after Round 14, time in play was up over 8%, runs and tries are up nearly 10%, line breaks up 7% and kicks are up over 7%. But weighted kicks were down 20%.

To find out who is causing this change, first let’s look at the percentage change in total kicks and total sets. That way we can see who is kicking more purely from having more possession due to rule changes introduced in Round 3.

Below is the percentage change for total kicks and total sets for all teams from Rounds 1-15, 2019 to 2020 (excluding Round 12, which was a condensed round in 2019 due to representative gams and had just four matches). The colour of each data point ranks each team for the volume of total kicks (dark red = 16th, dark green = 1st with lighter shades in between).

There are a few things that stand out initially from this. Every team in the league, except for the Gold Coast and Brisbane, has seen an increase in total sets this year of at least 4%. Penrith (it’s always Penrith) are leading the way with the most kicks this season, thanks to a 15% increase in possession resulting in 27% more total kicks. Parramatta have seen a similar amount of possession increase but only an 18% increase in kicks, indicating they’re running the ball a little more than the Panthers, who are favouring kicks more to end their sets. Soemthing that confirms the Eye Testtm with the Panthers.

There are a few teams though with a decline in total kicks despite an increase in possession, such as the Melbourne Storm, who have 5% fewer kicks despite an 8% increase in total sets. We’ll get to them in a minute.

One thing to remember is that we’re dealing with percentage change here, so higher percentages do not necessarily equate to high volumes. There are also lower volumes of weighted kicks for individual teams, but given the game sample size I’m not concerned about it as I would be after 6 or 7 games. Also, with the increase in ball in play time of about 8% and 5% increase in runs as noted last week, anything lower than that is technically a decline.

Next, we’ll look at the year on year change in total sets against the change in attacking kicks. It’s similar to the previous chart but the gaps are a little smaller at the top end of the scale.

At the pointy end, the numbers for Penrith are almost identical – an increase of 14% in total sets and 28% in attacking kicks, in case you want to know what is driving their offense this season. Parramatta are much closer to the Panthers in their increase in attacking kicks, up 25% on last season.

And if you wanted another indication of why the Broncos attack is so putrid, they have a decrease in total sets of 7%, but a decrease in attacking kicks of 20%.

Now if we look at the percentage change of weighted kicks against total sets, which as I mentioned before is down 20%.

Here’s where things get interesting. There has only been one team with an increase in weighted kicks this season – New Zealand (+10%) – although the Tigers were in the positives last week. Their bases are low enough however that you could argue they’ve at best stayed steady in weighted kicks but increased other kick types.

For the Warriors, even with an increase in attacking kicks they’re still under indexing on weighted ones as their total kicks are up by 13%. And their weighted kick increase of 12% is actually just two kicks in volume – they’ve gone from 20 to 22 since they don’t kick the ball as often as other clubs. One of the perils of drilling down to lower levels of data.

The far bigger story is the significant decline in weighted kicks by two teams – Melbourne and the Sydney Roosters – who have attempted 50% fewer weighted kicks than last season. If those teams taking half as many weighted kicks isn’t an indication of a massive change in tactics then I don’t know what more proof you’d need. The sharp drop in change for those clubs would lead me to believe someone has been doing some expected points analysis on certain kick types and found that attacking kicks yield a better result than weighted ones.

Melbourne’s 50% decline in weighted kicks is a drop from 58 to 28, which on a per game basis is a drop from over 4 per game to under 2. That is 30 fewer weighted kicks in over half the season. It’s a huge swing even if you consider that their total kicks are down 5%. I initially thought that they may have had small decline that increased whilst Cameron Smith was injured, but the decline was similar before he hurt his shoulder in Round 12.

The Roosters are another interesting case. Their overall increase in kicks is just 2.6%. What makes them more intriguing is that unlike Melbourne, their 56% decline in weighted kicks looks like 25 to just 11 in volume. That 11 is by far the lowest in the NRL, indicating they may have been ahead of the game by not having as many last season. On a per game basis they’ve’ from kicking around 1.5 weighted kicks per game now down to less than 1. It’s barely a part of their attack now, and when you have weapons like James Tedesco, Brett Morris, Angus Crichton and Daniel Tupou that makes sense.             

It’s not just those two teams, even St George Illawarra are kicking 47% fewer weighted kicks. This is a case where execution can’t be captured by statistics, as they’re clearly not travelling as well as the Storm or Roosters even if they have improved of late. It seems everyone is getting in on it as the Titans are down 39% on weighted kicks this season, from 36 to 22.

Now to tie everything together and support my crackpot theory, here is the change in attacking kicks plotted against the change in weighted kicks. Again, colour indicates the ranking of teams by total kicks (dark red = 16th, dark green = 1st and shades in between). I’ve also added a size indicator for the volume of weighted kicks taken to help visualise whether or not the change from last year matters.

Penrith, who had a 28% increase in attacking kicks, are kicking 14% fewer weighted kicks, and Parramatta who had 25% more attacking kicks have 18% fewer weighted kicks. Melbourne and the Roosters both have significant drops in weighted kicks but more muted increases for attacking kicks of 3% and 8% respectively. When you consider that they did not have large increases in total kicks, and the Roosters already take the fewest weighted kicks in the NRL, that makes sense.

Most of the top eight sits in the bottom right quadrant where you have an increase in attacking kicks but a decrease in weighted kicks. South Sydney (Wayne always likes to be different) are the lone outlier sitting firmly in the bottom left quadrant, as Cronulla sits very close to the right side with just a 1% drop in attacking kicks. Again, the Sharks have an increase in kicks of less than 1% so that change isn’t a huge concern.

And there’s your confirmation of a change in kicking tactics not just on an overall basis but led by some of the higher performing teams in the league. This is most likely due to the rule changes this season and coaches trying to reduce the incidence of seven tackle sets as discussed at length last week.

Those teams having very a successful 2020 – such as Penrith and Parramatta – are seeing a huge increase in kicks, both total and attacking, and outpacing their increase in possession. Other top four sides like Melbourne and the Roosters have dramatically changed their kicking profiles this season, eschewing weighted kicks in favour of attacking ones or running the ball more frequently close to the line. But as I mentioned last week, you’ll only hear how one referee and set restarts, not strategic kicking, are changing the game this year.

Why volume statistics aren’t always your friend

This week should have been a fantastic matchup of halves, with Shaun Johnson of the Sharks facing up against the Panthers and Nathan Cleary. Cleary has been one of the standouts this season, whilst Johnson is having a great season, but you wouldn’t necessarily know it from the way he’s often covered by the mainstream media. I’d pointed it out previously with a radar chart comparison in early August:

Johnson ended up missing the game due to some minor injuries and the birth of his child (congratulations Shaun!) and Cleary had another strong showing. Despite this we can still have a look at their statistical output for the season and use it as a test case for counting stats and raw volume statistics not telling the full story.

If you’ve been following for me for any length of time you know that I’ve put together some advanced statistics for rugby league, as using raw numbers mean players who spend the whole 80 minutes on the field usually dominate. If you’ve not read them, I’d recommend checking out my articles on Run %, Tackle % and Involvement Rate on the website, as they’re all incredibly useful in identifying high

But back to the topic at hand. It’s lazy analysis to only use counting stats without context but is more palatable to the wider viewing audience so I’m not going to deride them for dishing up what the consumer wants and easier to digest in small doses.

Source: Fox Sports Stats

Comparison of raw numbers – Cleary seems ahead. More passes, more runs, more kicks, more attacking kicks, more tries, more try contributions, more line breaks and more line engagements. Johnson is only ahead in try assists (20 to 14) and weighted kicks (17 to 10).

Per game stats will give a slightly better comparison, although it paints a better picture for Cleary who has only played 12 games compared to Johnson’s 14.

When players are compared on the usual pregame shows, it’s assumed that all players in a certain position play a similar game or similar role within a team, leading to scorching hot takes like this on social media from mid-June:

And if you look at the raw volume or counting statistics at that time without any context you’d probably agree – Johnson isn’t impacting the game as much as Cleary is.

But there’s one variable that’s not usually discussed (although the wonderful Jason Oliver pointed it out in his Round 15 preview on SportsTechDaily, another must read each week), is possessions. The amount of times a player gets his hands on the ball plays a massive part in his statistical output. The basketball adage of “you can’t rebound the ball out of the basket” can be applied here with a twist, you can’t do more in attack in rugby league without the ball in your hands.

For the season Cleary has 964 possessions, compared to just 733 for Johnson, a difference of 231 possessions. On a per game basis, that’s roughly 73 possessions for Cleary and 52 for Johnson. Cleary has his hands on the ball nearly 30% more than Johnson on a per game basis.

Knowing this, what if we looked at the same statistics again for Cleary and Johnson on a per possession basis. Would it show anything?

Source: Fox Sports Stats

Not initially, as those numbers are essentially meaningless – 0.016 line break assists or 0.187 line breaks per possession isn’t really meaningful. You can’t create 20% of a line break.

Instead we’ll normalise it to take out any bias that having more possesions per game creates. I’m going to pick a set number of possessions in between both players to even things out. The number doesn’t matter so much as long as we use the same number for both, and for this exercise I’m going to use 60 per game, since it’s a nice round number that falls between both Cleary and Johnson’s season average.

Source: Fox Sports Stats

Now we can see that they’re not performing that differently. Cleary has an edge with kicking, especially long kicks, whilst Johnson leads on weighted kicks and try assists. Yet for all the calls that Johnson needs to run the ball more, his runs, passes and line engagements are very similar to Cleary’s. Does he really need to “do more”?

That leads into the other part of player this analysis their positioning and their role. As mentioned above it’s assumed that all #6s and all #7s should play identically but this is rarely the case.

This was shown in a great article by Jack Snape from the ABC showing the locations NRL halves are receiving the ball. If you apply the Eye Testtm during Sharks games you’d know that Johnson sticks primarily to the right side of the field, while Cleary tends to operate on both sides. The above article shows this, with the locations of Cleary’s touches coming evenly across the field whilst Johnson’s are mostly on the right. You could then argue that if Johnson had a similar level of freedom as Cleary, he would probably increase his raw statistics.

The other part of the role is not just what side they’re playing on but how often they’re involved and relied upon for their team. Cleary takes about 16% of the Panthers total possessions, makes 36% of their passes, 75% of their kicks, 66% of attacking kicks and 44% of line engagements. Johnson on the other hand, takes 12.6% of Sharks possessions, 29% of their kicks, only 52% of their kicks and 45% of attacking kicks.

This again ties back to role. Similar to a sport like Formula One, the Panthers play with a clearly defined lead half in Cleary, with Jarome Luai supporting him. The Sharks more often than not play with their halves on a closer to equal footing, a 1a/1b type scenario, with each either sticking to their side of the field or sharing in the playmaking duties.

Asking Johnson to “do more” or run the ball more won’t necessarily help his game. More stuff isn’t always better. Johnson will turn 30 in a few weeks and it could be that he doesn’t have the same explosiveness and has developed more as a player is now picking his spots and interjecting himself at the right time. Just because he’s not shredding teams anymore with one of his explosive runs and making defenders look as if their feet are stuck in cement doesn’t mean he’s not impacting games.

Whatever the reason, the outcome of this specific comparison of Cleary and Johnson is that they’re both having amazing seasons for their team, and the difference in their statistical output is simply down to the role they play for their side, which can be accounted for by looking at a per possession basis.

Claiming one is better based on one number or a group of counting statistics won’t prove anything other than teams and players are different and may play different styles. Hopefully we’ll see some more analysis based on possessions than just counting stats moving forward.

Opponent play the ball location analysis

A few weeks back I had posted a chart showing the percentage of play the balls each team has in their own half, opponents midfield (20-50 metre area) and inside the opponents 20 metre zone. If you didn’t see it, here’s an update after Round 15, sorted by percentage of play the balls in a teams own half.

The Panthers are still dominating here, with nearly a quarter of their play the balls inside their opponents 20 metre zone. The Cowboys are still sitting in the top half of the league for play the balls in an opponents half, a testament to Jason Taumalolo’s ability to make lengthy runs (discussed last week), and also to their inability to do anything with the ball once they get there.

The biggest change would be the Roosters, who now sit in the bottom half of the NRL for play the balls in their opponents half since Round 3, although the Titans have improved with the ball, also sitting mid table now.

I’ve had a few requests to look at it from the other side of the ball, showing where their opponents are playing the ball to see if it was the inverse of their own play the balls. Below is the distribution of play the ball by opponent after Round 15, sorted by the percentage of play the balls spent in their own half.

It’s not an exact mirroring of the above chart, but there’s some similar trends. The Panthers are having a lot of success this season with field position, holding opponents to their own half in nearly 59% of play the balls. Combined with a very low percentage of play the balls inside their own 20 metre area, it shows the Panthers have been succeeding at maintaining excellent field position all season. Souths are the only team ahead of them, with 59% of play the balls in their opponents half on the back of some big wins recently.

The Roosters sitting mid table is a refelction of their struggles of late, and also of their confidence in defending their own line, as they sport a higher percentage of play the balls in their own 20 metre zone than the rest of the top eight.

The middle of the field grind that Canterbury likes to get into is evident as well, having one of the lowest percentages of play the balls inside their own 20 metre zone, but one of the highest in the opponents midfield at 27.3%. The Gold Coast keep opponents in their own half less than 50% of the time, the worst in the league but not far ahead of a faltering Manly.

Error rate Round 15 update

Finally, this week an update on the error rate leaders for the 2020 season. If you’ve not seen a post on error rate before, it can be summed up as how often a player commits an error, as shown by the number of possessions. The average NRL player commits an error approximately every 37 possessions, although that varies wildly by position.

Here’s the leader board (if you can call it that) for the 2020 season after Round 15.

There are eight players who are committing an error before they’ve had 10 possessions. Some of them are low minute interchange players – Max King, Beau Fermor, and Shane Wright. King has been the worst offender this season with three errors in his 21 possessions, and it’s probably no coincidence that we haven’t seen him line up for Melbourne since Round 4.  

More concerning for Craig Bellamy is some of his centres and wings showing up this high. Three of those eight players play for the Storm. Suliasi Vunivalu is probably the worst of them and sits just outside the top ten with 17 errors at a rate of one every 10.5 possessions. No wonder Melbourne were happy to let him go to rugby union for a reported $800k per season. Paul Momrovski and Marion Seve aren’t much better with error rates of 8.5 and 9.4, but both have played half as many minutes as Vunivalu.

In fact, there are 21 players with 17 or more errors this season, and Vunivalu is one of only two of them with fewer than 200 possessions. The other is his opposite winger, Josh Addo-Carr who has had 17 errors for an error rate of 10.9. No wonder Bellamy reacts the way he does in the coaches box during games.

I’d also like to give a shoutout to Blayke Brailey, possibly the safest set of hands in the competition. The Sharks hooker has handled the ball well over 1500 times, committing just one error. The next closest is Jake Turpin with one error in 474 possession, although Tom Starling has yet to commit an error in 448 possessions so far for the Raiders, so he’s technically in second place.

Brailey’s error rate of 1,526 is over 3 times that of Turpin’s. As you can see though, the error rate for a hooker is significantly lower than most positions due to the amount of times they handle the ball.

NRL Round 14 advanced statistics – 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. Traditional rugby league statistics are counting stats and volume based, and the important work of middle and interchange forwards in the NRL goes largely unrecognised.

If you’re new to the site and want to understand how it works, I would recommend reading this post on Involvement Rate. To put it simply, it is a combination of Run % and Tackle %

which shows the estimated percentage of plays that someone completed a run or tackle during their time on field.

Adjusting for minutes played and times helps identify those middle and interchange forwards who play with a high motor but don’t play huge minutes. Think Daniel Alvaro, Christian Welch, Blake Lawrie, Moeaki Fotuaika, Toby Rudolf and Francis Molo.

With that out of the way, here’s the all minutes leaders for Round 14

After topping the Tackle % and Run % lists, it’s no surprise to see a Alex Seyfarth and Daniel Alvaro quinella in Round 14. Both players Involvement Rate topped 30% for the round, meaning they either completed a run or made a successful tackle in three out of every ten plays whilst on the field. Given the average Involvement Rate sits in the 18-19% for middle forwards and interchange players, that is a massive effort.

Jazz Tevaga from the Warriors placed third, just a shade under 30%. Why he is only playing 37 minutes for the Warriors is a mystery to me.

Next we’ll look at those players who spent 40 minutes or more on field

With a minimum minute restriction applied, David Klemmer had the highest Involvement Rate in the NRL for Round 14, at 23.5% in his 53 minutes, indicating he was involved in over one in five plays whlist on the field. Manly’s Corey Waddell next with 22.6% as he saw increased minutes with Addin Fonua-Blake and Martin Taupau missing the game. Blake Lawrie from the Dragons rounds out the top three with an Involvement Rate of 22.24%.

Finally, we have the leaders for Involvement Rate this season.

Jazz Tevaga has rocketed to the top for the season, with an involvement rate of 23.38%, pushing well ahead of the Titans Jarrod Wallace at 22.44%. With Wallace playing lock this week in Jai Arrow’s absence it will be interesting to see if he can claw back some of that gap, although increased minutes usually result in a lower involvement rate

Another Eye Testtm hall of famer, Melbourne’s Christian Welch, chimes in next and sits third for the season with an Involvement Rate of 20.99%