Gauging the 2018 State of Origin teams – Game I
For the first time in a long time, it looks like we may have a well balanced Origin season. Indeed, the balance may even be a little Blue for my liking but when three of the last generation’s four best players retire from representative football, and they all happened to play for the same state, then the scales will shift perceptibly.
By now, you would know who’s playing for both Queensland and New South Wales in the first of rugby league’s three biggest games. You might even have formed an opinion as to which side is looking the goods. Consensus seems to have settled on this being the Blues’ year. But why settle for the thoughts of experts who have spent the last forty-eight hours tweeting out the leaked Blues lineup, when I’ve crunched the numbers for you?
A brief reminder about StatScore
You can read the short explanation in my piece rating the NRL halves pairings of 2018 or the longer primer or this same explanation in my last piece looking at the best players of the last four seasons.
StatScore is an attempt to quantify a player’s performance in one simple, easy to use number. It is absolutely prone to stat-padding and favours some positions over others but generally, the bigger the number, the better the player (taking into account a number of caveats, in addition to the philosophical implications of reducing a range of different roles, complex events, playing styles and physical attributes to a single quantum).
You can use the linked articles (or my season preview) to put some of the numbers into context against what’s below, although bear in mind that we are only halfway through this season and most of those are based on end of season results.
How the selected teams stack up
You’re about to get a lot of numbers thrown at you, so I hope you can keep up. Here are the salient points:
- StatScore is a ratio of a player’s total stats compared to the average in that role. Therefore, a 100 player is average, a 200 player twice that, a 300 three times that, etc, etc.
- I’ve calculated the StatScore for each player in the lineup based on their recent form (rounds 6 to 12), their year to date and their career average StatScore (remember that this is only 2014 through 2017).
- I’ve summed each state’s StatScore for their starting thirteen, for the whole team and by the Engine, which is their seven best starters. In a NRL team, the Engine (which is usually seven or eight guys in a roster of twenty-five or thirty) generate half the team’s total StatScore.
- StatScore does seem to add and it has a resonable correlation with winning but it’s not what I would call a predictive number.
New South Wales Blues
Broadly, while the Queenslanders have put up good numbers, New South Wales have put up excellent numbers. There is an 800 point gap between NSW and Queensland just between the full team StatScores on recent form shown over the last six weeks. That’s basically a superstar or two of difference. Damien Cook has put up huge numbers for a hooker (compare to his opposite number). Jack de Belin has triple the StatScore of Josh McGuire over the last six weeks, although admittedly McGuire was injured and missed a few games.
The only place Queensland has an edge is in the halves. That’s because Nathan Cleary has played five games this year, instead of the usual twelve. In those five games, he’s racked up enough stats to put him level with the average spine player. If we adjust his StatScore to assume he played all twelve games, he would be in the ballpark of 240. That wipes out the Queensland advantage but it remains close between the two sides in this key area.
The Maroons are a lot closer on career stats, suggesting that there’s still plenty of long-term quality in both teams. Queensland clubs, including the Storm, have struggled to find form so far this season with only Melbourne occupying a place in the top eight, and even this is well off the highs established in 2017. With one or two exceptions due to missed games through injury, the Maroon’s recent form is better than their whole of season form. Combine this with a depth of experience and there’s hope yet for some big numbers to be forthcoming.
The biggest gap is in the forwards. The Blues 8 through 13, i.e. six guys, have a combined StatScore of 1136 in 2018. Last year, the Tigers’ best eight players put up those kind of numbers. It’s like having two extra men out there. By contrast, Queensland’s equivalents have a total of 765. The stats aren’t everything but that is an almost overwhelming chasm in talent and there is an incredibly serious risk that the Maroons will be monstered off the field at the MCG.
Either way you slice it, the numbers suggest the Blues are top dogs.
What if we let StatScore pick?
Like my Team of the Year selections, I had to implement a few selection rules. Basically, these are the top guys, as rated across the first twelve rounds of 2018, for each state in their positions.
Initially, I wanted to just put the top five backs in the backline, irrespective of if they were all fullbacks or not, and do likewise for the forwards. This yielded two highly cooked Origin line-ups that I did not feel like justifying on Twitter, especially as they had some truly indefensible selections (I am not putting forward a Queensland side with Corey Norman in it).
But unlike the ToTY and more like Origin in reality, I wanted to select players in positions they wouldn’t normally play. This meant a little bit of judgment and I consulted the font of all knowledge, Wikipedia. If Wiki said a player could play a position, he slotted in there. The exception was Kyle Feldt because he has started exactly one game in centre in eighty-six appearances. That is not enough to justify handing over a the number three jersey.
I will also admit that remembering who plays for what state can be tricky and I may have overlooked a few players. For example, I didn’t know Joe Ofahengaue was Origin eligible until last week. And for another example, it has been pointed out that I will have to replace Ryan Hoffman in the Queensland squad.
New South Wales Blues
Firstly, there are ten Queenslanders and eight New South Welshman that are in both teams, so that’s a good start. There’s six Broncos, which is a little confusing. In fact, I have fewer Dragons, Panthers, Bunnies, Roosters and far fewer Storms. There are more Raiders, Sharks and Bulldogs and one appearance each from the Tigers and Knights. The Eels and Warriors fail to show in both lists.
There are a number of names in both teams that I wouldn’t have selected personally: Matt Lodge, Scott Bolton and Blake Ferguson are immediately apparent, both for the fact that they aren’t as good as the stats suggest but also their off-field “indiscretions”. Ryan Hoffman came from nowhere, mostly because I was a fair way down the list before I found a decent Queensland second rower. I had a similar problem finding Blue props to fill out the bench. And obviously, Aaron Woods is a marshmallow.
There are also some surprises in there. Anthony Milford seems to have found some form from somewhere, despite being completely useless in his last outing against the Eels. Luke Brooks taking on the seven jumper would be huge news and perhaps we shouldn’t go off half a season before giving him the most important job in the highest pressure team in the sport. The likes of Nick Cotric and, in an earlier draft of these teams, Kalyn Ponga are probably too young to play at this level but will be there sooner rather than later.
Overall, we’ll have to just admit it: New South Wales just have better players right now. Even the StatScore teams have NSW a couple hundred points ahead of Queensland on the starting squad, the whole team and in the engine. That dominance continues across time, with NSW being ahead on recent form, form to date and career stats.
David Klemmer has worked himself to be just a fraction (that fraction is 1 over 2,000) ahead of last week’s leader, Jason Taumalolo. They have pretty much the same numbers, which is highly unusual, but they are useful players on teams that are kind of crappy. Round 5 leader, Daly Cherry-Evans, has slipped down to tenth, despite a massive improvement from his team, while the round 6 leader in Luke Brooks is still the top Spine player in third.
Fourteen of the top twenty after round 5 have maintained their position in the round 12 top twenty. The new entrants are Bill Kikau, Ash Taylor, Jake Trbojevic, Angus Crichton, Cooper Cronk and Aidan Fonua-Blake. Exiting were Mitchell Pearce (injured), Johnathan Thurston (cooked), Gareth Widdop (English), Dylan Edwards, Roger Tuivasa-Scheck and Alex Johnston.
If you’re wondering why a preponderance of reasonable players on crap teams occupy the top twenty, then this by the Obstruction Rule does a pretty good job explaining why. I’m going to call it the Tamou Effect, when your stats don’t appear to be that great because you can share the load among competent teammates instead of having to carry useless pricks on your back.