Cow Talk Rounds 3 –> 4

Written by Father Dougal on April 10 2019

Small or Far Away, Father Dougal on Cows

So, it is still a week or two too soon for the normal cow projections, but I should somehow involve cows in Cow Talk. So, hmm. What do you call a lot of cows?

A herd

Right! And what do herds often have?


I asked for that. I was looking for “behavior.” As in herd behavior. Something that seems common at this point every season. And why is that? Because we are so excited to get new data that we get, well, excited, and give it too much weight. Three weeks of scores is nowhere near enough to change our thinking about players for which we already have decent data. Rookies are different, in that we start with little data and each of the first weeks is a non-trivial addition to what we know. But, non-rookies, most of them we know a lot about, and yet we throw it out the window. That makes rounds 3-5 the “Second Defenestration”

Defenestration? And what’s the first one?

To defenestrate means to throw out a window. Awesome word. The First Defenestration is when team are announced, and our pre-season plans go out the window. The Second Defenestration is now Rounds 3-5, when we throw common sense out the window, and over react to the small data samples.

I wrote in the preseason about the concept of True Level of Ability, called TLS from here out.

It basically means how good a player really is and what he would score with no luck factor. Since there is a luck factor, players will score super differently quarter to quarter, a lot differently match to match, and some differently over a season. Once a player has a decent scoring history, and more so each season past 25, we can have a good idea of what to expect from them based on their past performance. The farther over 30 they are, the more likely a drop from their past establish level.

So, for example, Dangerfield. He is 29, so I would not expect his to drop due to age.


Year Games Average
2008 2 19.5
2009 19 62.6
2010 19 69.9
2011 22 80.3
2012 22 118.9
2013 20 112.9
2014 22 105.6
2015 21 119.9
2016 22 131.8
2017 21 136.4
2018 21 121.7
2019 3 126.3


He has established he can average 130+  and last season he was hurt and still scored 121.7. After his bye, when he was fit, he averaged 132.9. So, before this season, we would expect him to average 130 or a bit more at the end. He is currently at 126.3, so really that expectation has not changed. He should average about 130 from here on out. What if he was currently averaging 150? Then we should expect him to average 130 from here on out. If he was currently averaging 100, we should expect him to average about 130 from here on out.  His final season average if he was scoring 150 now would go up to 132.7, and if he was at 100 it would go down to 125.9. But the scores that have moved his final season average have already happened. From here on out, expect a 130. But often we are so excited to get data, we treat the first few weeks as what a players TLA is, even if it is way off what we calculated it was preseason. Then we act on the idea their TLA is different than we thought.

Danger Case 1 (I love calling these Danger Cases, and send thanks to Patrick’s ancestors for facilitating my joke.)  He is averaging 150. “Oh no, I must get him in now or I will fall behind” His price has gone up so you are paying more than the people who got him before, and if you are buying R4-5 a lot more. But, you have him. Then he goes 130 the rest of the season, and you have overpaid. Darn.

Danger Case 2  He is averaging 100. “Oh no, I must get rid of him now or I will fall behind” His price has gone down so you are taking a loss, and if you are selling R4-5 a big loss. But, you are rid of  him. Then he goes 130 the rest of the season, and you have lost money and points. Darn.

Of course this year Dangerfield is under-priced due to last season’s injury affected scores. Makes him a not ideal example. Lets try something practical for this season.

I wonder what Lachie Neale’s TLA is?


Year Games Average TLA estimate
2012 11 47.4 50
2013 9 86.9 80
2014 21 87.2 90
2015 22 104.3 105
2016 22 112.6 110
2017 21 109 110
2018 22 111.9 110
2019 3 148 “X”

Neale has played 128 games before this season and is 25 years old. An old 25, too, 25 and 10 months. Not impossible for a breakout years but no longer likely. He did go to a new team. We can be open minded. So, What is the value of “X” in the above table? Before the season I would have said 110. Maybe, 115. I have this change by 5 habit, he is about 25, so give him a bump. So 115. Could we have said 120? Not without a lot of optimism. New team, maybe a better role, no Fyfe. How about 125; a 15 point increase? Not liking it. If have been ok with 110 or 115. Yet, people are treating his current average as if it was his TLA. It isn’t.

Lets try a little experiment. Anyone who wants to bet me $100 that Lachie Neale will have an average of 148, no let’s give a bit, 145.0 or more at the end of the season, assuming he plays at least 10 matches, step right up.

And, what was your reaction to the idea of making that bet? There are two sane ones. “Not a chance”, and “I like FD so much I will make it as an excuse to give him $100.”  Because you know darn well he won’t average 145 for the season. He won’t average 135. He is unlikely to manage 130. Anyone notice Lachie being just as great as Gary Ablett Jr. previously in his career?  As great as Paddy D? He is good, but after going near dead on 110 from age 22-24 he’s going to have a huge jump this year? Riiiight. 

Neale is now priced to average close to 120. If you buy him now, and he goes 120 from here on out, which is a 10 point jump from his established TLA, you are getting him at cost. If he goes less, you overpaid. If he goes more, and 125 would be a great rest of season average for him, then you are getting a small bargain. IF he manages to score his average of 148 next week, he will be priced to average about 128, which is anywhere from a little high to a lot high.

Then there is the trade cost. If you are bringing him in to replace an injured guy, well, you had to trade anyways. If not, you are probably using a trade to overpay for someone.

Let’s look at what I call the “Bending over with no lubricant” case. Clayton Oliver has had a rough start to the season. Priced to average 114.7 but currently averaging 102.3. Some dropping of price has happened and could more.


Year Games Average TLA estimate
2016 13 70.3 70
2017 22 111.5 110
2018 22 114.7 115
2019 3 102.3 “Y”


So, what should the value of “Y” be? He is only 21! Preseason I would have put it at 115. If it turned out to be 120 I would not at all be surprised. I would not be shocked at 125. Having a 111.5 average at 19 and a 114.7 average at 20 is way off the curve, and he has a big upside. The only player I know of he is behind is, one guess, Gary Ablett Jr. who had a 132 average at 20. Oliver is far ahead of Dangerfield. Do you know what Oliver’s TLA is not likely to do at age 21? Drop. It is very likely to go up. But “Oh no, Oliver is under-performing and has to go.” You sell him, at a loss. Then he scores 115-125 the rest of the season. Combine that with overpaying for Neale, and you have managed to use a trade and spend extra cash to swap players who will score about the same for the rest of the season. And the one you gave up is more likely to have the higher average from here on out.   

Let’s look at this another way. There are 10 players averaging over 120 right now. Do you think there will be 10 players averaging over 120 at the end of the season? Me either. There were only 11 players over 110 at the end of last season. There were 5 over 120, and only 1 over 130 when it was over in 2018. A lot of players are going to score at or below their TLA from here on out, and drop off. Who is over 120 currently?


Player Avg
L. Neale 148
P. Cripps 133
J. Macrae 132.7
J. Lloyd 128.3
L. Whitfield 126.7
P. Dangerfield 126.3
M. Bontempelli 126.3
T. Boak 126
B. Cunnington 122.7
R. Sloane 122.3

Neale – More likely to be under 120 then over 120. He does have three high scores to give him a leg up. If you do not have him and bring him in now, and he averages 120, he will have averaged 115.6 for you. An average of 115.6 from here out is not crazy high, thus 120+ for the season is not crazy.

Cripps – Easy to see him over 120 at the end of the season. He is 24 and was at 119.4 last season.

Macrae – Easy to see him over 120 at the end of the season. He is 24 and was at 127.1 last season. Could be over 130.Lloyd – Not likely. He is 25, and 112.0 last season.

Whitfield – Probably not. He is 24, and 99.9 last season. I expect him to do better than 99.9, but not 20 points better.

Dangerfield – Easy to see happening, again.

Bontempelli – Ohh, would not be a shock. He is 23, which bodes well for a breakout, and has been held back by too much forward time in the past. I would not bet on it, nor would I bet against it.

Boak – If you think Boak will have a 120 average at the end of the season I have a bridge to sell you. No, that’s not fair, if you think he will average 110 at the end of the season I have a bridge to sell you. He is 30, and averaged 88.0 last season. If you started with him, take the money are run in a week or two.

Cunnington – No. Less insane an idea than Boak, but that’s like saying less insane than the Joker. He is 27, averaged 96.3 last season.

Sloane = No. Sorry, hate me, but no. He is 29, and never managed to average over 114.8 in the past. I won’t try to sell you a bridge if you disagree, but it would be a serious surprise. He did average 114.8 once, in 2014, which is not a lot to hang your hopes on. Now if you started with him, well done. You got a bargain. If you did not start with him, you missed the bargain. Find a current bargain.

And Odds are someone lower than 120 now will hit it, maybe more than one person. Find the person(s) they are who you want. Not the over performers.

So, well, there you go. I hope that was helpful.

Thanks for reading!



Leave a comment / Scroll to bottom

53 thoughts on “Cow Talk Rounds 3 –> 4”

  1. Great info FD – but is the “Cow Talk” label the right one for an article on the dangers of blowing your load on a player averaging 150 after three rounds?



    1. I gotta write something while I wait for enough data to make useful projections. Didn’t you notice how I used the whole herd behavior thing? 🙂


      1. You know what – I did, and then you dropped so much wisdom that I plum forgot about the tenuous link you tried to create 😛

        Just figured it might resonate better if it was titled “The Subtle Art of Not Getting Sucked In”, or something along those line.


        1. Oh, the name is always Cow Talk, with a round. Next week or the week after there will be projections for cows. But with too little data, I find other things to write about early in the season. The cows are pretty clear right now, so I am not seeing a lot to talk about with them yet!


  2. Terrific write-up, FD. Would love your insight on a little cow debacle I’m having this week.

    I need to field 2 out of the following: Drew, Parker, Petruccelle & Setterfield.

    Considering their match-ups this week, who would you be fielding?

    Leaning towards Petrucelle and Drew atm?


    1. Hmm. I have to pick from Drew, Parker, Setterfield, and Balta.

      Leaning towards Parker and Setterfield. Want to know if any reasons for Drew to do better.


    2. I’ll offer my 2c.

      Drew gets a run for sure, and doubly so if Rockliff misses (which he should…).

      The other spot, I’d be tossing up between Petrucelle and Parker. Both similar players, in that they’re mostly outside and providing some run and carry. Given Parker’s best scores to date are about 30pts up on Petrucelle’s, and his lowest score is a few points better than Petrucelle’s lowest – I’d be leaning towards Parker.

      The argument for Petrucelle is that his scores have been increasing week on week (slightly) while Parker’s trending the other way. Still, ceiling wins out for me.

      Setterfield has been a bit underwhelming so far. With Cripps, Dow, SPS and Fisher doing a lot of the stoppage work, and Walsh, Murphy and Newman the preferred outside distributors, he’s kind of floating in no-man’s land doing a little bit here and a little bit there. Still building fitness after a slow start to his career, so probably just bench cover while he slowly appreciates unless injury opens up an opportunity for him to take on more responsibility.


      1. Cheers for the response, FD and BB.

        My concern with Parker is he’s only scored well against teams with poor backlines, which certainly won’t be the case against Hawthorn.

        My logic with Petruccelle is that the Eagles should pump Freo and hopefully he’ll get on the end of a few goals.

        Atleast there’s some consensus on Drew, so cheers again fellas.


  3. I am concerned about this “cow talk”. After witnessing a peaceful, non intrusive, highly emotional, well motivated demonstration, and powerful arguments for veganism two days ago, from among our nation’s finest, I now believe “cow talk” has to be abolished.
    Further, we MUST immediately stop any talk of culling cows…its not their fault if they go up in value just because they are successful cows. How would we humans like it if the better we were, the closer we got to judgement day !!
    I think we need to get rid of the term ‘cow talk”. Instead, doesn’t “carrot culling” sound nicer. Bean butchery ?? Asparagus annihilation ??
    Just saying…….gotta go now…need to thaw some things for tonights’s dinner.


  4. Hey FD,
    just another interesting overlay to consider for the TLA, the increase/decrease in points during wins/losses.
    For example, Neale is now at a team that is regularly winning, which could be boosting his average by 5 – 15 pts per game? I am not sure of Neales historic stats in W vs L, but intuitively it makes sense. That doesn’t fully explain his current average, which I expect to come down, but it may be boosting it above his theoretical TLA.
    Likewise, the opposite could be influencing Oliver at Melbourne. With Melbourne playing poorly, perhaps that reduces his average by 5 – 15pts.


    1. Should probably apply the TLA to Brisbane as a whole too 😉

      They’re off to a flyer, but they caught WC napping in round one, and have since only knocked over Port (middle of the road side) and North (very poor side).

      Neale has come from Freo (8 wins in 2018), and I reckon best case scenario for Brissy is that they win 14 (similar numbers to Melbourne last year), though more likely around 12.

      Do the extra 4 wins compared to what Neale had at Freo boost his average significantly across the full season?

      Have to assume he’ll get some more attention now as well, as teams put some work into trying to stop Brisbane’s high-tempo game plan.


  5. hmm this is making me rethink my trade of Fyfe to Neale. Feel like the concussion to Fyfe is concerning, dont want him bleeding cash if it takes a while for him to get up and about but now thinking I should be bringing Macrae instead of subconsciously chasing Neales points, have enough bank for either.

    Or save the trade and hope Fyfe keeps his form up. Stressful Wednesday


  6. Neale is so consistent.
    And 130 games are now his new average.
    He’s breaking out for a 130 average minimum, his consistency will keep him up, I see a few more 140+ scores coming from him.


    1. You’re smoking something if you think Neale’s gonna average 130 for the season. I started with him, absolutely stoked that I did, but he’ll average around 115 this year I reckon, 120 at the absolute most.


    2. And remember FD article about reverting to long term averages. Your saying his new average of 130 is based on a sample of 3 games.


      1. I’m saying, he is ultra consistent. He came out scoring really well, his consistency will keep it up.


  7. Hi FD,
    Did you want to run that parable over Kade Simpson? Seem to remember he had some reasonable years in his mid to late 20’s ,then dropped off for a season or two, then went bang in the last 3 or so years. Hoping Boak will do the same with an apparent role change. At worst He should end up as an F5 or F6. But I do take your point and it’s a good one.


    1. Kade Simpson output since 2009 (Year, Games, Average):

      2009, 22, 94.0
      2010, 22, 99.8
      2011, 22, 94.5
      2012, 19, 93.7
      2013, 22, 95.1
      2014, 22, 95.4
      2015, 20, 92.7
      2016, 22, 106.4
      2017, 22, 93.9
      2018, 21, 105.0
      2019, 3, 72.3

      He turned 28 in 2012, and 30 in 2014. The 2016 jump likely came about in part due to a new gamestyle under Bolton; the dip the following year coincided with Docherty elevating himself to uber-premium status, with Simpson’s output reverting back to 2016 levels in 2018 thanks to Docherty’s absence.

      His role hasn’t changed this year, and Newman shouldn’t be taking *that* many points off him, so it’s hard to say what’s behind his lacklustre scoring so far. Has his age finally caught up with him? Perhaps. Then again, 3 games is a small sample size, so we can’t say for sure just yet.


      1. RD2 and RD3 2019 is the 1st time since RD20-RD21 2015 that Simpson has recorded 2 consecutive matches below 20 disposals. From 2014-2018 only 15 of 107 matches were below 20 disposals.


  8. I must say that it’s a little concerning that people being thrown out of windows has been such a frequent occurrence over the centuries that we have a special word for it. I agree that it is a pretty awesome word, though.


  9. Great write up Father Dougal! I’ve always thought the more good games a player puts together the more likely they are due for a poor one! Don’t need to look any further to when Tom Mitchell pulled out a 79 straight after scoring 181 last year.


    1. Yes and no. On the one hand, regression to the mean is definitely a thing; on the other hand, the scores are statistically independent, so no score is inherently more or less likely as a direct result of a previous one.


      1. Essentially the same. The more good scores they put together in a row there’s more chance they’ll put in a poor score in the following weeks to bring their average back towards the mean.


        1. Not the same – that simply isn’t how probability works. if you toss a fair coin ten times, and every time it comes up heads, what is the probability that the next one will be tails? The answer is 50 percent, just like any other coin toss. This is because the coin tosses are *statistically independent*, meaning that the result of one is not connected to the result of the previous ones.

          The same thing applies to SuperCoach scores.


          1. I get your point but Supercoach scores don’t have a 50/50 probability like tossing a coin does. There are many factors which may lead to a lower score after a string of strong performances such as team performance, complacency, more attention from the opposition etc.
            As mentioned above it is reasonable to assume Neale is far more likely to average 115-120 than maintain his current average of 148 – meaning he has already had a very solid run of scoring and going forward is a far greater chance of going sub 120 than exceeding it. Why? Because these three scores have come in Brisbane wins, he has not been tagged for a full game and some games the ball just tends to find a player more than others regardless of how hard they work.
            Whilst I can’t say Brisbane won’t win this weekend and he won’t get tagged there’s no doubt he is a greater chance of posting a score back towards his mean than going 150+ again (although I’d love to see him pump out another monster score).


            1. I fully agree that Neale is likely to average 115-ish from this point forward, but that’s different to saying that he’s going to have a streak of 70s to balance his 150s out.

              As to SuperCoach scores more generally, it doesn’t matter if the odds are 50/50 or not, the rules of probability remain the same. Let’s say that a player has an average of 100, with a standard deviation of 10. This means there’s a 68.2 percent chance of any one of said player’s scores falling between 90 and 110, a 13.6 percent chance of it falling between 80 and 90 (and the same probability for it being between 110 and 120), and a 2.1 percent chance of it falling between 120 and 130 (and also of it being between 70 and 80).

              So, there’s a roughly 2 percent chance of this player scoring 120+. What are the odds of him scoring two consecutive 120+ scores? Answer: 0.04 percent (probability of the first event x probability of the second). But if he’s just scored a 120+ score, does that mean there’s only a 0.04 percent chance the next one will be, too? No. It’s still 2 percent. The other probabilities remain unchanged, too.


              1. That works if the average and standard deviation remain the same but they don’t. What was the probability of Tim Kelly getting tagged 3 weeks ago to now? It’s gone through the roof after a string of very good performances. The factors which potentially lead to a low score increase each week after each good game. He might not get tagged this week, or next week for that matter but if he continues put together 30 disposal game after 30 disposal game he will get tagged eventually.


                1. Perhaps, but saying ‘such and such has been playing well, and will probably start getting tagged’ is different to saying ‘because he scored 150, he’s necessarily going to score a 70 to balance that out’. I have no issue with the former statement.

                  When I wrote about our hypothetical player’s ‘average’ in the above post, I was really thinking about FD’s TLA metric, with the standard deviation representing the spread of scores around said TLA. Does being tagged change a player’s true level of ability? Food for thought!


                  1. Yep exactly, I think there was a misunderstanding in what we were both saying. I do agree that if a player posts a high score and all factors remain the same, they are equally likely to post that score again. But the factors change every week and looking at some of the players who have genuinely exceeded expectations (Kelly, Neale, Boak etc.) their teams have performed very strongly also. Will this be the same if their team drops off from their strong starts to the season? Only time will tell.
                    I think we should put this matter to rest… soon enough the columns will only be able to house 1 word each!
                    Happy SCing Salamander


                    1. Fair enough. It’s probably been quite an informative discussion for anyone reading along, though, so perhaps we could call it a productive misunderstanding? 😉

                      Happy SCing to you as well.


          2. Agree re the coin toss, but if you accept that statistically there is a period of observations above a long term average, probability also suggest that below average performances will be coming. When they come is the sc players right to decide/trade.
            Would you bet $100 at even money on neale hitting his season average again this week ?


            1. Only if you consider the long-run average to be preordained. If it is known with 100 precent certainty ahead of time that a player will average exactly 115 for a season, then yes, any period in which he averages above that must be balanced out by a period in which he averages below it.

              But this has the causation backwards. A player’s season average isn’t set in advance, with scores forced to conform to it. Rather, the average comes from said scores.

              So, let’s say that we think Neale will average 115 from round 4 onwards. With his first three rounds averaging 148, that will mean a final season average of 119.5, assuming he plays 22 games. No doubt he’ll have a few down games here and there, but his prior good games are not *why* he’ll have those bad ones.

              It’s just like the coin toss example: you can be pretty certain that tails will come up eventually, but the prior heads are not the reason why.

              And no, I wouldn’t take even money odds on Neale scoring 148+ again this week. 😉 20:1, on the other hand…


    1. No and no. His age is perfect, he’s just coming into that breakout period at around 21 or 22 years of age where players often explode. Number of games isn’t a worry either, we saw Clayton Oliver hit a 110 average as a teenager with 20 games under his belt. We also saw what Dunks could do last season at the age of 21 when he was given an inside mid role. He absolutely exploded after the byes.

      No , the real reason his scoring is down this year is because he no longer has an inside mid role. He’s been pushed into that no man’s land perma half fwd role where players are lucky to average 85. I have no doubt that if he played as a perma inside mid this year, he’d be the no. 2 averaging forward behind Danger.

      Unfortunately, Bevo doesn’t realise what a beast he is in the mids, and thus he has been moved to half forward. As a result, his scoring has taken a hit. Get rid of him while you can, his scoring isn’t gonna improve unless one of Wallis, Bont, Macrae or Libba goes down with a LTI.


      1. You make a good point about his role change – he only attended the fifth most centre bounces for the Dogs on the weekend.

        Oliver is probably an exception rather than the rule.


  10. On a more serious note, this was terrific. Even more terrific than your usual stuff, which is saying something –  bookmarked.

    Your point about players reverting to their TLA from here on out is an important one, because it’s something that I often see people getting subtly wrong – you’ll frequently see people say things like “he’s averaged 150 for the first three weeks, and he’s going to average 120 for the season, so he’ll average 115 from now on”, which has the causation completely backwards: a player’s season average is determined by their scores for the season, *not* the other way around. And, as these scores are statistically independent, the most likely outcome is that they will revert to their TLA, as you noted.

    Anyway, if if we assume that a player’s performance for the rest of the season will more-or-less equal their TLA, we can come up with an easy formula to determine whether a player represents value at their current price:

    Let p = priced-to-average, a = likely average from this point, and v = value. If p – a = v, then a player is good value if v > 0, bad value if v < 0, and neutral if v = 0.

    As we've discussed, likely average is equal to TLA; to get a player's priced-to-average figure, we just do current price / magic number / current multiplier.

    Of course, all this ignores the possibility of a player missing games, although you can modify their expected average to compensate: [(likely average x games remaining) – (likely games to miss x likely average) + (likely games to miss x replacement score)] / games remaining, where replacement score = the likely output of your bench cover. Then again, if the chance of them getting injured or suspended is that great, it might be best to just not bring them in at all.


    1. Sorry, those value figures should be reversed. With the variables arranged as p – a, the player is good value if v 0. I suspect my brain was thinking a – p rather than p – a when I wrote that.


  11. Backing in Boak.
    History to be broken
    No one would have backed Westoff last season to average over 100.
    Taken Drew’s midfield time and Wingard and Polac departure as well as Rozee and Butters flourishing in forward line.
    Easy option is to go Kelly instead but would simply be following the crowd.


    1. Those who ignore history will live to regret it. Why is a 30 yo who has never averaged 100, about to create history. To average 100 for the season from here, uber no’s for a fwd, his average must be below 100 for the remaining games.


  12. I absolutely love all the research that people do on this site and the mathematical formulas and figures that are discussed , then I make my choice on things like robbie gray is a gun , think ill get him in, I love this game.


  13. Anyone see Kingy’s review on the impact of 6 6 6 on inside 50s and scoring… and how players like Neale who are clearance kings are having a significant impact on outcomes and especially the huge increase in Brisbane’s scoring…
    he tabled some telling facts that would go some way to supporting the notion that Neale could well have a 10 pt increase in his TLA this season… and it has zilch to do with history because it is due to a change in the game structure. Again a 3 game sample, but the numbers clearly support a certain method of clearance under the 6 4 6 significantly outperforms others and shows an increase over last year that cannot be ignored by any club. And it appears Neale executes better than anyone. (Note the 6 4 6 – the wingers have no real influence on those particular stats )


    1. I have not, would love to.

      That might indeed up Neale’s TLA some. It wouldn’t change the general point about early season small data samples though.


      1. FD

        Thanks for a great write up.

        I would love your thoughts on another factor to consider when looking at Uber Premo’s like Neale.

        I call it the Captains factor.

        Lets say the average team took Dangers captains score of 128, giving them a Captains score of 256.

        If you managed to Captain Neale’s 177 you scored 354.

        Thats 98 points extra you can effectively add to Neale’s average for” your” team.
        This is a pretty big number and won’t be the norm.

        Lets take Cripps as another case. If you took him as Captain you scored 314. 58 points more than Danger.

        Lets just say for arguments sake that you use Cripps as your Captain five times this year. On average he nets you 50 points more than the standard Captains score for each round.
        At the end of the year he has scored “your”team 250 more points.

        If Cripps scores 2500 for the year, he has effectively scored 2750 for” your” team. Increasing his inherent value by 10%

        What I’m trying to get at is, if you can get in an Uber Premo / Captains choice priced close to their TLA. As long as you get to use them for a few above average Captains scores, they are still priced under’s.

        I would love some thoughts on whether this theory stacks up?

        I personally think Neale can come close to averaging 120 this year.
        Some players take longer than others to hit their peak.
        Add in other factors like being the No1 guy at Brisbane, More room at centre bounces allowing more time to off load the ball.
        This to me, adds up to better DE. Neale has always had high stats counts, He seems to have upped his Kick to handball ratio and increased his DE. For me I can easily see this resulting in a 10ppg increase in scoring over his last few years results.

        Just my 2c worth any way.



Leave a Reply

Your email address will not be published. Required fields are marked *