Wests Tigers Deep Dive of the Week

[innsaneink]

Are those offload numbers correct?
Seems very low

 

[Jolls]

Let me go back and check - though that was what the maths came out at.

 

[Jolls]

Are those offload numbers correct?
Seems very low

I'm a dickhead - the calculation was already done for me and I divided it by the number of games in the season. I will go back and correct it now. Thanks - too far into the number to think about the reality!

 

[Jolls]

Are those offload numbers correct?
Seems very low

and to make matters worse I used the wrong bloody column. I'm not sure how trustworthy the figures are either given that they are AI generated by a betting app - but I was trying to identify our attacking shortfalls.

I have my own feel - but I though I would see what the forum cam back with. It should be too hard to guess where I woul dtake it hough.

 

[Rock Hopper Steve]

I'm a dickhead - the calculation was already done for me and I divided it by the number of games in the season. I will go back and correct it now. Thanks - too far into the number to think about the reality!

You Jolls no I don't believe it, something growing where it shouldn't, well it's easily fixed a sharp pair of gardening shears and take a deep breath and whamo, problem fixed.

 

[Jolls]

You Jolls no I don't believe it, something growing where it shouldn't, well it's easily fixed a sharp pair of gardening shears and take a deep breath and whamo, problem fixed.

Yep, like the Fonz I was Wrrrr Wrrr Wrrr, you understand

 

[tigerballs]

Deep Dive 19: Converting Opportunities into Points: Fixing the Wests Tigers’ Red-Zone Attack and Try-Conversion Rate​

I thought I would take a different approach to this Deep Dive. Using data to highlight clear deficiencies I thought it may be good to ask what the forum thinks as opposed to me espousing my thoughts.

The data (links provided) has been used to make some basic assessments. Now it is over to you to see where the conversation goes.

Let's see how it pans out.

Introduction​

In the NRL, success hinges on a team’s ability to convert possession and territory into points, particularly inside the opponent’s 20-metre “red zone.” The Wests Tigers’ attacking statistics in this area have lagged behind league benchmarks for a long while; contributing to a failure to capitalise on scoring opportunities and impacting our overall competitiveness.

Key data point: In the 2025 season, Wests Tigers converted 58.3% of their red-zone opportunities into tries, well below the 72.1% league average and the 78-80% rates posted by elite sides like Penrith Panthers and Melbourne Storm.

Closing this efficiency gap is a tangible way for Wests Tigers’ to drag ourselves in to the eight in 2026.

Deficiency Analysis​

Try Conversion Rate Inside 20m​

(Source: NRL.com 2025 Team Stats)

Team	Try Conversion % Inside 20m
Penrith Panthers	79.2%​
Melbourne Storm	78.4%​
Sydney Roosters	75.6%​
Brisbane Broncos	74.9%​
League Average	72.1%​
Wests Tigers	58.3%​

The data shows that we convert significantly fewer red-zone opportunities compared to the competition’s leading sides; and are well below the league average. This is a must fix area for 2026. So what are the likely causes?

Offloads per Game​

(Source: SportsBettingAI NRL Team Stats 2025)

Tigers average approximately 11.5 offloads per game and are the competition leaders in this area.

Offloads are important for maintaining attacking momentum and creating second-phase plays in tight defensive zones. While this stat can’t be linked directly to what is happening inside the red zone it shows that we are not turning our second phase play into scoring opportunities.

Tactical Kicking Frequency​

(Source: NRL.com Match Stats)

We average fewer tactical kicks than league leaders, with approximately 0.43 tactical kicks per game, compared to an average of 1.32 across the NRL.

Tactical kicking (bombs, grubbers etc) inside the red zone can disrupt defensive line integrity and create try-scoring chances and repeat set opportunities. This stat can’t be linked to directly what is happening inside the red zone. Given our general kicking is significantly lower than the NRL average it is assumed that this correlates to what is happening inside the red zone.

The Eye Test​

(Source: Nil)

Despite a lack of granular, verifiable data, several factors from match observations, expert commentary, and rugby league principles underline the Tigers’ struggles in the red zone:

• Predictability and Lack of Variation​

The Tigers’ attacking sets in the red zone often rely heavily on certain edges or preferred plays, making them predictable and easier to defend.
Opposing teams crowd defensive lines around our known “go-to” channels, limiting space and forcing errors or turnovers.

• Execution Under Pressure​

The red zone is a high-pressure area where defensive intensity peaks.
We have struggled with execution errors (knock-ons, poor passes, dropped ball) in critical phases, reducing scoring chances.

Without precise data, the eye test suggests that our handling errors and failure to complete the set with high outcome plays limits our success.

• Lack of Tactical Kicking and Variation

Effective teams use tactical kicking (bombs, grubbers) inside 20m to unsettle defences and create aerial contests.

The Tigers’ attacking repertoire inside the red zone appears limited in tactical kicking variety, reducing our ability to stretch defences and create scoring opportunities.

• Player Skill and Cohesion

Red zone success often hinges on composure, skill execution, and intuitive link-up plays.

We are in a rebuilding phase with new combinations, leading to less cohesion and timing issues in attack.

This can’t be used as an excuse in 2026 given the limited roster changes over this off season.

Summary​

The Wests Tigers’ red-zone try-conversion efficiency is a clear, quantifiable weakness with a direct impact on our match outcomes.

While opportunity creation appears to be adequate, failure to convert opportunites inside the 20m zone puts pressure on all the other areas of our game.

So the big question for the forum is two-fold:

What is causing us to be so far behind in some of the key attacking stats and what can we do about it?

Jolls, do you have the raw data on that 58.3% conversion rate, as in from how many opportunities as opposed to say, Brisbane? Eg: Brisbane at75% from 100 opportunities equals 75 tries. 58.3% from 50 opportunities equals 29 tries, from 200 opportunities equals 117 tries.
It seems we were able to reach the red zone fairly often in games. If we were there more often than Brisbane, then even the league average would have us well in the top eight. It's a fairly damning stat, really. Managing to fix that single component would mean a massive improvement.

 

[Tim Sheens]

Try Conversion Rate Inside 20m​

(Source: NRL.com 2025 Team Stats)

Team	Try Conversion % Inside 20m
Penrith Panthers	[]79.2%[/]
Melbourne Storm	[]78.4%[/]
Sydney Roosters	[]75.6%[/]
Brisbane Broncos	[]74.9%[/]
League Average	[]72.1%[/]
Wests Tigers	[]58.3%[/]

The data shows that we convert significantly fewer red-zone opportunities compared to the competition’s leading sides; and are well below the league average. This is a must fix area for 2026. So what are the likely causes?

I know that this take won't be popular amongst the majority on here that have him as a pin-up star, though it all starts at dummy half, particularly near the line, so a lot of that failure to convert field position is on Koroisau for mine.

 

[Jolls]

Jolls, do you have the raw data on that 58.3% conversion rate, as in from how many opportunities as opposed to say, Brisbane? Eg: Brisbane at75% from 100 opportunities equals 75 tries. 58.3% from 50 opportunities equals 29 tries, from 200 opportunities equals 117 tries.
It seems we were able to reach the red zone fairly often in games. If we were there more often than Brisbane, then even the league average would have us well in the top eight. It's a fairly damning stat, really. Managing to fix that single component would mean a massive improvement.

The 58% red-zone try conversion rate I cited is based on an effectivenss model I pulled together as no no raw data exists. The raw data I plugged into the model came from the stats available at NRL.com. I should have made this much clearer. I did have the detail in the draft version but I pulled it out because it was difficult reading. In doing so I oversimplifed it. In trying to make it clearer I think I muddied the waters.

This is what was in the draft version ...

There’s no official data breaking down exactly how many NRL tries come from long range versus close to the line, expert analysis and match observations that I could find suggest that about 20% of tries originate from outside the opponent’s 20-meter zone. The majority of tries tend to come from close-range pressure and set plays near the try line, but plenty of scoring also happens from breaks and support plays further out. Based on this the comparison model has a baseling conversion rate of 80%.

The try conversion rate is a mathematical representation based on a team's effectiveness to develop the probably of success. The model uses a combination of statistical deficiencies: predictability, execution errors, underused kicking, and opportunity deficit to calculate the probability of success.

Definitions / symbols

• P = Probability of success
• base = baseline conversion rate
• Pi = Predictability Index (0 to 1; higher = more predictable).
• Ed = Execution Deficit (0 to 1; higher = worse execution under pressure).
• Kd = Kicking Deficit (0 to 1; higher = less tactical kicking use).
• Od = Opportunity Deficit (0 to 1; higher = fewer quality opportunities / line breaks).
• α,β,γ,δ = weights for each defecit.

Model formula
P  =  base  −  αPi  −  βEd  −  γKd  −  δOd

The model is a simple linear penalty model: start with the base probability and subtract weighted penalties.

These are the figures I used to come up with our derived probabilities:

• Pi =30% = predictability - due to our lack of shape
• Ed =15% = execution deficit
• Kd = 40% = kicking underuse
• Od= 20% = fewer quality opportunities.

The weighted coefficients were selected to represent relative importance: kicking deficit penalised most, predictability least. What I used was:

• α =0.12
• β= 0.20
• γ= 0.30
• δ= 0.15

Plugging the numbers in:

• αPi= 0.12×0.30=0.036
• βEd= 0.20×0.15=0.030
• γKd= 0.30×0.40=0.120
• δOd= 0.15×0.20=0.030

Sum of the penalties = 0.036+0.030+0.120+0.030=0.216 (21.6%)

So we take the 80% baseline and subtract 21.6% and we have 58.4% that I rounded down to 58%. The numbers are subjective but taken from our performance using the raw stats on NRL.com - for example linebreaks we averaged 3.4 v Penrith's 5.4 and Brisbane's 6.0 (we were 16th)

Sorry for the confusion - I was trying to make it simpler to understand and in doing so the model came across as hard data. That is not what I was trying to demostrate. We have known for years that Wests Tigers just con't convert in the red zone - I was trying to quantify that observation using an analysis of the stats.

 

[Jolls]

I know that this take won't be popular amongst the majority on here that have him as a pin-up star, though it all starts at dummy half, particularly near the line, so a lot of that failure to convert field position is on Koroisau for mine.

I hadn't considered him to be part of the problem, so it would be interesting to understand how he contributes to our ineffectivenss in the red zone. I see Api's job, inside the 20, as keeping the markers A/B defender interested while providing clean ball and for the most part I think he does a reasoable job. So your perspective would be good to understand.

In the model I used Penrith came out on top because of their ability to grind, their kick pressure etc and the Donkeys were lower on the table because they are more enterprising - ie score more long range tries (have more tackle/line breaks etc).

Our deficincies, as I saw them are: a lack of enterprise (predictability - not enough shape/bodies in motion); poor execution; a limited kicking game and less opportunity based on our position in most attacking stats. I think we can add to that our ability at times to get into the red zone.