Who really is the best try scorer in the NRL this season?

By Mark McGrath / Roar Rookie

Ask any NRL fan who is the best try scorer so far this season and they will nearly always go to the leading try scorers list. They will nominate the player at the top of that list.

At the moment after 19 rounds, that player is South Sydney’s try-scoring machine, Alex Johnston. But is Alex Johnston really the best try scorer in the game this season?

Scoring tries is not a level playing field
Rugby league is a team game. Try scoring opportunities are created by teams for players, who are both fortunate enough to be in the right place at the right time and good enough to convert those opportunities into tries.

But these opportunities are not distributed equally across the field. Wingers receive far more try-scoring opportunities than say prop forwards or bench players. Also, the number of try-scoring opportunities will vary across different teams, in a way that may surprise you (more on this later).

So given that the opportunities to score tries are not shared equally across positions and teams, judging try-scoring ability from a single list of total tries scored by all players can be misleading and not all that useful.

A player playing in a position that doesn’t score many tries and playing in a team with lots of try-scoring talent around him may only score ten tries for the season. But this would be a very high achievement given the player’s limited opportunities.

How best to measure try-scoring ability?
Ideally, the best way to measure try-scoring ability would be to have a system that takes into account the number of opportunities players get and then produce a rating based on these opportunities and the tries they have scored from them.

The try-scoring rating system
This is what I have done, by developing a rating system based on how many tries a player has scored above or below the number of tries they would be expected to score, then expressed this as a percentage of their tries scored.

To come up with an expected tries figure for each I player I developed a formula, using data from the 2013 to 2020 seasons, based on the following factors:

• Game Minutes Played (GMP): 1 GMP = 4,800 seconds played (80 mins)

• Team Tries (TT): the total number of tries scored by the player’s team in the games the player has played in

• Position Value (PV): a numerical value of the player’s position based on the long-term percentage share of tries across all positions.

So, if Player X was expected to score 10 tries but had scored 12 tries then his try-scoring rating would be +20per cent (12 minus 10 = 2, 2 divided by 10 = 20per cent).

I deliberately excluded performance metrics that are closely related to a player’s try-scoring ability (eg line breaks, tackle breaks) because by only forecasting on opportunity, you get the players try-scoring ability largely determining the values above or below expectation.

Finally, I calculated some minimum cut-off points to weed out the “fluke” results; seven tries scored and eight game minutes played.

2021 Try Scoring Ratings (up to Round 19)
The block of cheese gets the chocolates.

Rnk Name Rating
1 Brandon Smith 107.22 per cent
2 David Fifita 82.62 per cent
3 Sitili Tupouniua 75.22 per cent
4 Viliame Kikau 71.93 per cent
5 Nathan Cleary 66.62 per cent
6 Angus Crichton 63.35 per cent
7 Tom Trbojevic 61.85 per cent
8 Isaiah Papali’i 61.66 per cent
9 Jahrome Hughes 61.23 per cent
10 Cody Walker 51.81 per cent
11 Daly Cherry-Evans 43.88 per cent
12 Alex Johnston 42.78 per cent
13 Matt Burton 41.91 per cent
14 Josh Addo-Carr 36.11 per cent
15 Reimis Smith 34.24 per cent
16 Clint Gutherson 30.63 per cent
17 Reece Walsh 30.27 per cent
18 Adam Doueihi 24.43 per cent
19 Matthew Dufty 21.78 per cent
20 Maika Sivo 11.42 per cent
21 Justin Olam 10.14 per cent
22 Jason Saab 9.69 per cent
23 Latrell Mitchell 6.64 per cent
24 William Kennedy 4.03 per cent
25 Reuben Garrick 4.02 per cent

Brandon Smith and David Fifita
Brandon Smith and David Fifita are exceptional players, playing in positions that historically don’t score as many tries as outside backs.

They have also played far fewer game minutes than wingers, who usually play the full 80 minutes. They are both great at breaking tackles and turning those runs close to the line into tries. This has translated into high try scoring ratings.

Brandon Smith (Photo by Kelly Defina/Getty Images)

Negative try expectation
Some people may query players (like Brandon Smith) having a negative try expectation rating. This is because there is a constant in the formula (which is negative) and until players rack up enough opportunity data (GMP and TT) to overcome this constant, they will have a negative expected tries rating.

The role of team tries
When I first started developing this system, I assumed that the more tries a team scored, the more opportunities a player would get to score them. But after doing the analysis I discovered it was slightly the opposite case.

The Team Tries factor turned out to be a weak, negative factor for forecasting tries scored. The analysis showed that for every 100 team tries scored, the expected tries forecast for a player was reduced by 1.8 tries.

This basically means that good try-scoring players playing in weaker teams have a slight advantage over players in teams that score more tries (mainly because there is more competition for scoring tries).

The Crowd Says:

2021-07-30T08:36:11+00:00

Joey

Guest


What I mean is, the formula doesn’t factor in whether the player was assisted in scoring or whether it was an individual effort. How many defenders did they beat? How far did they run? I realise that’s incalculable based only on raw game stats, but just seems a try of individual brilliance might be weighted more than a try served on a platter.

2021-07-30T08:13:35+00:00

Forty Twenty

Roar Rookie


I've long claimed that Brett Stewart has the best strike rate if you combine scoring tries and setting them up but it's only a wildish guess.

2021-07-30T08:09:29+00:00

Paul

Roar Rookie


Great article and fantastic analysis. You should show your work to Ben Darwin at Gainline Analytics.

2021-07-30T06:46:19+00:00

Albo

Roar Rookie


Yep ! Still never seen a winger score so many tries untouched than Alex Johnston . To me it assists with his successful total try tallies over the years . Yet this gets no weighting in the assessments of "best try scorer" ?

AUTHOR

2021-07-30T06:45:51+00:00

Mark McGrath

Roar Rookie


Good question. I plan to do an amended version of this analysis on all-time try scorers in the NRL. Being a backrow forward with a high try scoring rate you would have to think he would be right up there. But he has some hot competition like Harold Horder, who scored 102 tries in 86 games; a try scoring rate higher than Ken Irvine.

AUTHOR

2021-07-30T06:38:13+00:00

Mark McGrath

Roar Rookie


BMoz came in just outside the top 25 (#26) at a rating of +3.92%.

AUTHOR

2021-07-30T06:35:23+00:00

Mark McGrath

Roar Rookie


Small correction; in my explanation above I said: GMP = Game Minutes Played (total game minutes divided by 4800) This should have read: GMP = Game Minutes Played (total game seconds divided by 4800).

2021-07-30T04:11:07+00:00

Joey

Guest


Most tries is obvious but best ? Most of them he only needed to catch and run 10m.

2021-07-30T03:25:43+00:00

Clint

Roar Rookie


Great stuff Mark. Love statistical analysis like this :thumbup:

AUTHOR

2021-07-30T02:36:17+00:00

Mark McGrath

Roar Rookie


Thanks guys, Following the editor's guidelines, I didn't want to bore people with too much data and statistical nerdy stuff. But for those that are interested in this side of things... The formula The formula was derived from a multivariate, linear regression on the 2013-20 dataset. The formula extracted from this regression was: Expected Tries = - 6.627 - (0.0184 * TT) + (0.357 * GMP) + (2.039 * PV) where: TT = Team Tries GMP = Game Minutes Played (total game minutes divided by 4800) PV = Position Value (a factor derived from the % distribution of tries across positions, with the Interchange position =1) The Adjusted R Squared value for this formula (a statistical measure on how good the formula fits the data) on the 2-13-20 dataset was 74.70%; a pretty good result considering that the formula includes no skill factors. Extra results data I would like to post extra results data, that will enable you to make more sense of the ratings, but the content management system running this site provides no easy way for posters like me to publish this data. I'll contact the eds about this. Potential improvements to the model There are two areas where I think the model can be improved: 1. Adjusting Team Tries to the total number of tries that were scored when the player was on the field. 80-minute players are not affected by this in the current results. But less than 80-minute players are because tries that were scored when they were on the bench are counted as an opportunity against them, when in fact they weren't (you can't be expected to score a try when you are on the bench). 2. Using Tackled in Opposition 20 data I think this would be a strong opportunity variable to use. But until I get the data and test it, I don't know if that would really be the case or not. When tries are scored Daniel, you would first have to calculate the distribution of tries across game time, to see if there were any potential advantages or disadvantages here for players playing less than 80 mins. If there were differences, then you would have to do a significance test to see if these results were just a fluke (ie randomness) or if there was something more to them. But potentially yes, you could have something to use there to improve the model. Further updates If people are interested, I'd be happy to post an updated table of results after each round.

2021-07-30T01:44:53+00:00

andyfnq

Roar Rookie


Excellent analysis of data from which you have drawn well-justified conclusions. Your description of your method was concise, clear and easy to follow. I look forward to reading more articles by you I'm the future!

2021-07-30T01:09:30+00:00

Duncan Smith

Roar Guru


This is a great article. Well conceived and written, thinking outside the box.

2021-07-30T01:05:30+00:00

Tony

Roar Guru


We were heading to the night clubs by the time the forwards had worked out how to undo their boots, and finished fooling around in the showers. :happy:

2021-07-30T00:43:37+00:00

Daniel

Guest


Being in the field less may mean that you have less time to score tries, but also means you have less time to defend so you’re potentially fresher to score tries. It would be really complicated but maybe you need to factor in what minutes during the game a player plays i.e the first 10 minutes you’re really unlikely to score points, but the last one 10 minutes of a half you’re more likely.

2021-07-29T23:43:20+00:00

Paul

Roar Guru


Nah, our heads were bowed and we followed the boots of the bloke in front of us, we were so buggered after games. By the time we got to the sheds, the backs had taken all the hot water and you had to get a machete to cut the air, which was full of hair spray and Brut or Old Spice. We didn't mind though because we could fill the air with choice words about how many bits of silly play numbers 1 - 7 had done which we had to make up for. :happy:

2021-07-29T23:23:59+00:00

Tony

Roar Guru


I was a Sunsilk man myself, and it wasn't just the shorts, there was nothing like having a clean jersey after the game. It gave the forwards something to follow as they tried to find their way to the sheds. :happy:

2021-07-29T22:59:42+00:00

Nat

Roar Guru


Where does B-MOz land? He's a winger but 11 tries in 546 minutes...

2021-07-29T22:56:33+00:00

Joe

Roar Rookie


Pretty good analysis and conclusions. I think this is why there's going to be a battle over the Cheeses signature between the Roosters and the Storm. (and likely other clubs). When you have someone in a position which doesn't traditionally have many tries seemingly scoring at will it is a statistical anomaly. Considering that position is in the spine and said person is a workhorse defender unlike Fifita in your list his value goes up significantly. Brandon Smith had a 5 game try scoring streak going. Pretty impressive from a 9.

2021-07-29T22:50:21+00:00

andrew

Roar Rookie


I reckon Kyle Feldt's amazing efforts with players all over him beats those scrapbook swan dives easily.

2021-07-29T22:37:14+00:00

Paul

Roar Guru


I'm in awe of anyone who can take the time to analyse and draw conclusions from masses of data. In this instance, you've gone a step further and devised a formula, then applied it to players over the past 8 years - all in your first piece! I guess I know what you've been up to during lockdown! One question. Can you give more explanation about the GMP please? "Game Minutes Played (GMP): 1 GMP = 4,800 minutes played (80 mins)" I don't get how 4800 minutes played equates to 80 minutes?

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