It’s hard to believe but we’re already thirteen rounds through the 2024 NRL season. This also means it’s as close to the midpoint of a 27 round season as you’re going to get, since I can’t do an update for Round 13.5.
Following tradition as we did last year, the year before, and the year before that, we’re going to take this time when Origin fever is taking over the eastern seaboard to see the top (and in some cases lowest ranked) players by the Eye Test’s suite of advanced statistics for rugby league. Find out which players are performing the best, or worst at key aspects of the game that traditional media don’t talk about, or only talk about in vibes rather than hard data.
Since most of these metrics are rate or per attempt, there’s no bias in here for teams that have played more games than the rest of the competition, thanks to the wonders of a 17 team competition with multiple byes. Somehow the Storm, Titans, Tigers and Rabbitohs have had two byes before the Roosters and Cowboys have received their first, but the Tricolours will get their first one next week. North Queensland must wait until Round 16, which is hardly ideal.
Because of this, anything using raw counting stats that is not adjusted for (at a minimum) games played is just showing you a list of who had played more matches than anyone, and therefore had more chances to accumulate counting stats. A very last century way of comparing players or teams.
Instead, most of these metrics are rate based, either per minute, per attempt (kick/run) or at worst possession normalised per game.
Let’s get stuck into the advanced statistic leaders for 2024 after thirteen rounds.
Eye Test Player Contribution Rating (ETPCR)
The Eye Test Player Contribution Rating (ETPCR) is a player impact metric, that weights a players statistics by how well (or how poorly) they correlate with winning games. It also adjusts for minutes played and possession to normalise these number across teams. A score of 0.0 would represent an average NRL player, who isn’t a positive contributor but also doesn’t contribute negatively either.
The reason for possession adjustment is easy with one example. The 2023 Penrith Panthers averaged nearly 20 play the balls per game more than the Canterbury Bulldogs, so to reduce the impact of all that extra possession their statistics, we standardise it for the same number of play the balls for every team.
If you want to read more about ETPCR, the explainer is here. Again I want to empahsise this is an impact metric, not a talent metric. It’s measuring which players had the biggest impact statistically on their games, not who has been the best player, although there is usually some overlap.
Now on to the top 25 players for the season at the halfway mark, with a minimum of seven games played.
In an interesting coincidence given this weekend’s news, James Tedesco is now first for ETPCR for the season at +2.786. The surprising part is that he wasn’t even inside the top 10 after Round 7, ranking 13th at +1.506. His last five rounds were impressive as well, finishing up with a +7.250 in Round 12 against the Raiders.
Broncos fullback Reece Walsh placed second at 2.493, with Jahrome Hughes third at +2.163. Hughes had been leading this metric for most of the season but had a quiet game by his lofty standards in Round 12 as Melbourne lost to Manly.
Two more fullbacks round out the top five, with the man Tedesco replaced due to injury in Dylan Edwards ranking 4th (+1.968) and another Storm player in Ryan Papenhuyzen in 5th at +1.782.
Murray Taulagi ranks ninth, which is an astounding number for a player on the second worst defensive side in the NRL. No other Cowboys player places inside the top 50, and only one other (Valentine Holmes) ranks inside the top 90. He’s somehow avoided the negative statistics that usually come with a team that allows a lot of points.
Payne Haas is the highest ranked forward at +1.217 in 13th spot, which is very impressive as forwards don’t generate the same level of tries, line breaks or assists of those as backs do. Haumole Olakau’atu is two spots behind in in 15th (+1.178) with Angus Crichton ranked 17th (+1.134, the only other forwards inside the top 20. Outside the top 20 you do see some more forwards appearing – Isaah Yeo, Eliesa Katoa and Addin Fonua-Blake place inside the top 30.
Isaiya Katoa was an early season standout by this metric, and was even leading the NRL after seven rounds. He’s had a few sub par games by his high standards of this season since then, yet still manages to rank inside the top 25 for the year. Incredibly splendid numbers for a 20 year old.
I also want to point out that if you took just the positive side of the ETPCR calculation, David Fifita would be ranked inside the top 25 and second highest of all forwards, only trailing Angus Crichton. The slow start to the season the Titans made has dragged his numbers down. It still remains mystifying to me that he couldn’t even make an extended Queensland Origin side, let alone a bench spot where he could create 20 minutes of mayhem.
Now let’s have a look at the players with the lowest ETPCR this season.
It’s a list dominated by Eels, Bunnies and Titans, with a smattering of Tigers as well. Blaize Talagi ranks last at -2.861 from eight appearances, and another Eel in Morgan Harper ranked third last at -2.078. The Eels have been terrible for most of the season, and their edge defense has been atrocious, and this chart highlights which players specifically have been credited with the negative statistics that go along with yielding points.
Sandwiched between those two is Jack Wighton at -2.771. This is why I mention that ETPCR is an impact statistic, because Wighton isn’t one of the bottom five players in the competition. What he has had to do is usually be one of the last men in defense trying to clean up the mistakes of those less experienced players around him. The same can be said for Cameron Murray’s name here, it’s hard to create enough positive production statistically on a historically atrocious defensive side like Souths. They’re not being put in positions to succeed or maximise their talent this year.
Similarly, Api Koroisau appearing in the bottom 20 is due to his high rate of missed tackles (second highest per game in the NRL) and the Tigers inability to score points. Hookers are hard to quantify with statistics as well, as good service isn’t easily tracked, meaning they mostly suffer from negative defensive numbers unless they’re a Harry Grant.
I’ll also note Will Warbrick’s placing here for friend of the site Nick Tedeschi, as you don’t usually see a player from a top four side in the bottom 20. A lot of punters have noted to me how they’ll favour whoever is running down Warbrick’s side of the field, and this data validates that.
Run Metres Over Expected per run (RMOE/run)
Run Metres Over Expected per run (RMOE/run) measures how far a players actual run metres exceed (or fail to meet) what an average player would gain from a run starting at the same position on field on the same tackle number.
It’s a great way of working out which players make the most of their runs with the ball, although some positions don’t fare as well by this metric as they’re more distributors than runners of the ball. There’s a full explainer on the site if you want to delve into more detail and which positions benefit from this analysis.
Here’s the leading 25 players by RMOE up to Round 13 this season, with a minimum run count of 40 attempts.
Raiders fans were expecting to see one of their players at the top of this chart, but it’s not the one they expected. Nor would it be their second, third or probably fourth guesses. The leader was their halfback Kaeo Weekes, who has stormed into first position from his five games, averaging 3.38 metres per run more than an average player in the NRL. Weekes is also the only player above +3 metres in the competition, however I’d expect that move down a bit more as he plays more games. Still a very impressive start to his NRL career and it creates a welcome headache for coach Ricky Stuart when Jamal Fogarty returns, as Ethan Strange has also been outstanding thus far.
It’s not only remarkable because he’s only played just over a dozen NRL games. It’s also remarkable because a #7 isn’t meant to fare well in this metric (see the bottom 25 coming up later). Most halfbacks have a negative RMOE/run, and it’s usually the running five eighths like Ezra Mam or Luke Metcalf that do post a strong number. Weekes doing it whilst also running the baby Raiders around the park is an amazing number. How did Manly let him go?
Weekes unseated last years #1 for RMOE/run in Manly’s Jason Saab, who still posted an impressive number of +2.39m for second place. Two more outside backs followed Saab in Hamiso Tabuai-Fidow (+2.35) and Newcastle bound Raiders winger James Schiller (+2.21).
The top forward was Cronulla’s bench middle Tuku Hau Tapuha, who had a very impressive RMOE/run of +2.18. The next highest forward was Brandon Smith at +1.58, who has the benefit of gaining sneaky metres out of dummy half.
The best performing non dummy half forwards after Hau Tapuha were the usual suspects. The first was Jason Taumalolo at +1.54 proving the adage about age not diminishing your ability, just how often you can repeat those efforts it is true. Viliame Kikau was next at +1.36 and his absence will be huge for an inexperienced, small and mobile Canterbury pack.
If we look at the bottom of this list you’ll notice a trend.
Most players are on this list they’re a function of a players role rather than their talent. The vast majority of these players are halfbacks, distributing dummy halves or locks who serve as link men, and not one of those types of players is being judged by metres gained.
The fact you can see Dean Hawkins and Lachlan Illias as two of the bottom three is an indication of how Souths use their #7 and not representative of their ability as a player. The bigger problem for Souths is that Cody Walker also features in this list, and indicates they’ve got halves who play overlapping styles, not a complimentary pairing such as a Dylan Brown/Mitch Moses or Ezra Mam/Adam Reynolds combination.
% of runs above expected metres
Next we’ll use our expected metre model that forms the basis of RMOE/run, and use it to check which players have the highest percentage of runs above expected.
Where RMOE/run looks at how many extra metres a player gains, the percentage of runs above expected shows which players are more consistently beating their expected metres. It might only be by 20 centimetres per run, but it shows they can be relied upon to generate yards consistently.
Here’s the top 20 players by this metric from the first thirteen rounds.
Cronulla’s Hau Tapuha takes first place here, at a very impressive 73.3% of runs above the expected metres of an average player in the same field position. That’s better than Taumalolo, who has been the king of this stat in recent years. Dragons forward Ben Murdoch-Masila placed third behind Taumalolo at 67.9%. Two New South Wales Origin players rank next with Manly’s damaging edge backrower Haumole Olakau’atu at 67.6% and Payne Haas at 67.2%.
From there you have a 4% gap to Thomas Mikaele of the Cowboys at 63.4%, ahead of Fonua Pole (63.3%) and another Cowboy in Murray Taulagi (63.2%), who ranked as the highest back in this chart. Taulagi was only slightly ahead of his Origin foes Brian To’o (62.9%) and Stephen Crichton (62.6%).
It’s not just tackle busts that are creating these runs above expected. If you compare average tackle busts by runs per game, only a handful of these players appear on this list.
The above players making more metres than expected are doing it through post contact metres after breaking a tackle, but not solely by that means. They’re creating more metres before hitting the defensive line, or finding space and not creating contact in the first place.
Error rate
Error rate is one of my favourite metrics to track, more at a team level than a player level, as it shows which sides value possession (sometimes too much) and which ones like to take risks.
On an individual level it also highlights which players are making errors at a higher rate. Two players may have similar total error numbers, but if one of them is touching the ball 30 times a game, let’s call him Sam W, and the other 12 times a game, let’s call him Dominic Y, the latter player is more of a concern with the ball.
It also shows again why completion rate is a junk statistic, as you want creative players like Reece Walsh making mistakes trying to create chances, and those playing wider like Izack Tago are often mishandling the ball trying to convert chances. It’s a fine line but being too conservative with the ball is a trap.
Here’s the 20 worst error rates in the NRL this season up to Round 13.
It feels fitting that a Roosters player takes first place here, with Siu Wong committing six errors from just 29 touches this season in five games, at a rate of one every 4.83 touches.
Second place goes to Jason Saab at a slightly less terrible 8.78 touches per error, with Tigers back and perennial error rate name Brent Naden at 9.80.
Generally players with an error rate under 10 are rare, especially as the season progresses as they don’t usually last long in first grade unless they offer something unique in attack like Saab, Izack Tago or Walsh.
Tackle Rate
Tackle rate is one of the first advanced metrics used at the Eye Test. In short it’s a possession adjusted tackles per minute metric, creating an estimate of which players made the most tackles as a percentage of available play the balls whilst they were on field. I created it because most middle forwards didn’t play big minutes, and because raw tackle counts favour players who are on the field more.
I’ll use the quote from last seasons post as to why I like this metric more than raw tackle counts as a measure of workload.
“Simply stating tackle counts presents no context. If two players made 50 tackles, but Player A did in 60 minutes and Player B in 80 minutes, Player A was completing them at a higher rate and would be taking on a larger amount of their teams’ workload.”
There’s also the issue that players making a lot of tackles usually have to do so because either their team was playing bad and they were playing in defense a lot, they’re a poor defender so opponents were running at them, or opponents were running at them because they wanted to tire them out to exploit them later.
That’s also part of the reason why tackles aren’t included in ETPCR. Tackles made has a negative correlation with winning games and margin of victory. That is, if you make more tackles, you’re more likely to lose games than win them. Making tackles is theoretically a negative production statistic.
Let’s normalise talking about tackles as a measure of effort or work rate, not a measure of defensive ability. Teams don’t usually run at good defenders.
But I digress. Here’s the top 20 players for the season by Tackle Rate. All of the “effort” metrics are using a threshold of 120 minutes played.
Parramatta’s Brendan Hands has the best tackle rate in the NRL, completing one for 38.4% of play the balls the Eels faced, or two out of every five opponent possessions. Usually teams that have played a lot of defense will end up leading these numbers, however Wong from the Roosters pops up here too, completing a tackle on 36.6% of play the balls he faced whilst on field. Penrith’s tackle machine Liam Henry rounds out the top three at 36.21%, with his monster effort of 71 tackles against the Dragons propping up this number.
It is interesting to note the Bulldogs have six players in this top 20, including two players averaging more than 50 minutes per game. Traditionally these rate based effort metrics see a decline as players minutes increase, and it’s unusual to see them in these lists.
It speaks to the effort and work rate of the smaller more mobile pack they’ve recruited, with five players – Bailey Hayward, Sam Hughes, Max King, Kurtis Morrin and Kurt Mann – all completing a tackle on three out of every ten play the balls. Reed Mahoney barely missed the 30% cut, and given that he plays nearly 79 minutes per game, that’s an outstanding amount of work he’s putting in defensively. As noted on the site earlier this season, Cameron Ciraldo has finally moulded this team into a defensive juggernaut. To have six players in this list emphasises their level of fitness and commitment.
Ball Runner Rate
The other side of Tackle Rate, but this time it’s the possession adjusted runs with the ball completed per minute. This one is designed to show the players who come on in short stints and create havoc with the ball.
Another minor victory for the Eels, with bench middle Makahesi Makatoa nabbing top spot with a run rate of 20.62%. This indicates he completed a run on one out of every five play the balls whilst on field this season.
Makatoa beats out Dolphins interchange forward Josh Kerr, another regular name on this list, at 17.79%, with Ben Murdoch-Masila of the Dragons taking third place at 17.14%.
This is another metric where the rate decreases as minutes increase, which means the presence of Terrell May, James Fisher-Harris and Joe Tapine on this list with all three playing at least 45 minutes per contest highlights their elite work rates.
Option Run (Support or Decoy) %
I’ve made a slight change to this metric for 2024. It existed last year as Total Run %, where I added in support and decoy runs (option runs as a grouping) to actual runs with the ball to get a rate of how often they were completed.
This year I’ve decided just to look at how often a player makes one of these types of runs. First to get an idea of which players show up only in support or as decoys more often, and secondly because the added option runs didn’t change the Ball Runner Rate chart. Below are the top 20 players this season.
The Warriors’ interchange forward Jazz Tevaga holds first place this season, completing a decoy or support run on 11% of the Warriors play the balls whilst he is on field. Second and third places go to the Cowboys, with Griffin Neame and Jake Granville sporting option run rates of 10.90% and 10.74% respectively. Another North Queensland player in Reuben Cotter came 7th at 9.77%.
The Dragons end up with three of the top eight placings, with Michael Molo, Blake Lawrie and Murdoch-Masila all above 9.4%, which might indicate how new coach Shane Flanagan is using his middle forwards this season.
Involvement Rate
Involvement Rate combines the three components above – tackles, runs, and option runs – into one single work rate metric to see which players are putting in the most effort during a match. Again, this isn’t a quality metric, it’s an effort metric, and Involvement Rate looks at effort on both sides of the ball.
It’s somewhat poetic that the Bulldogs are dominating this list, given the consistent level of commitment and effort this season. Sam Hughes places first with an Involvement Rate of 27.51%, indicating he completed a run, tackle or option run (decoy or support) on one quarter of all plays whilst on field.
That was slightly ahead of Murdoch-Masila at 27.40%, with another Bulldog in Max King placing third at 26.97%. The other Canterbury player in the top six was Kurtis Morrin at 26.32%, again showing how much emphasis the Dogs have placed on smaller, mobile, high work rate players. It’s harder for bigger middles to put in this amount of effort for longer stints.
King’s name on this list shows why he has one of the best work rates in the NRL, placing second despite playing nearly 51 minutes per match. No other player inside the top 30 averaged more than 46 minutes, and the next high minute forward was Cotter with an Involvement Rate of 23.14% from 63.7 minutes per game.
Lastly some run and kick angle leaders.
For narrowest run angle, or the straightest runner in the NRL this season, the leader is Davvy Moale from South Sydney at 15.79 degrees per run. Last year’s leader Josh Kerr only placed ninth this season.
The widest runner is Canterbury’s dummy half Reed Mahoney, at nearly 41 degrees and the only player above 40.
Of the above players, Jack Bird’s name on this list is the most interesting to me, as one of the few non-spine players in these 20 names. A look at his run spray chart shows just how much he likes to run laterally.
That is usually something ball players are doing trying to create gaps to put their teammates into. It’s a little unusual for an edge back rower or centre to do.
And finally, the narrowest and widest kickers this season. The narrowest kicker this season is the Broncos Jock Madden at 15.98 degrees per kick.
Looking at his kick spray chart you can see how that happens, most of his kicks are very long and direct, with few wider attacking kicks inside 30 metres.
The widest kick angle came from Te Maire Martin from the Warriors, with an average kick angle of 31.77 degrees.
Looking at his kick spray chart it shows that most of his distance kicks have been to the left, whilst most of his attacking kicks have been back towards the Warriors favoured right hand side of the field.
