Our newest member of the SCT Writing team, Derek, has opened up here with an absolute banger!! Today Derek goes through the preseason formula he employs to find the best value in Supercoach!
Every SuperCoach pre-season starts the same way. We all open the team picker and convince ourselves this year will be different. This year we’ll be calm. Disciplined. We’ll pick value, not names. We’ll “trust the process”.
That’s SuperCoach.
I’m not immune either. Otherwise I wouldn’t have spent half my SuperCoach career finding a reason to put Cyril Rioli in my team.
The simple value formula
What the formula gives you is a number that tells you, roughly, what a player needs to score early to be “value” at that price. It’s not saying what they will score. It’s saying what they need to score to justify their price, a value benchmark, not a prediction.
So at $400k you’re basically expecting around 88. That’s the land of midpricers and breakout candidates, which is also the land where SuperCoach seasons go to die if you get this wrong.
Once you apply the benchmark to players, you now have an “expected” score for each player. Step one is done: you have a value target based purely on price.
But here’s the key. Most people try to predict 23 rounds, which is impossible. You can’t even predict the next 23 minutes in this game.
So I focus only on the short term, the next three rounds. It’s less daunting, more realistic, and fixtures and roles create the sharpest edges early in the season. Some players open with soft matchups and can go bang immediately. Others might be great players but start with a brutal run, underperform early and become value later.
In simple terms, the method becomes: calculate what they need to score to be value, estimate what you think they’ll score over the next three games, and compare the gap. If you think they’ll beat the benchmark, you’ve found value. If you think they’ll fall short, you’re either avoiding them or waiting for them to get cheaper.
There’s an obvious problem: we can’t predict scoring. We can make educated guesses, but bias creeps in for all of us. We all love certain players. We all talk ourselves into things. We all get influenced by hype and highlight clips.
And yes, that includes the loudest bloke on YouTube who insists he’s “just being objective”, while picking eight players from his own club.
That’s how I use it. Let CD set the baseline, then make the obvious tweaks.
Keidean Coleman is priced at $233,800.
The benchmark says he needs to score 67. Champion Data says 52, and my own expectation sits around 60. Coleman is the classic SuperCoach temptation: cheap, exciting, and everyone remembers the 2023 Grand Final (and the commentators will remind you every time he kicks it). But the benchmark is a big reality check. Starting him is basically saying you expect genuine defender scoring straight away, and that’s a big call for someone coming off long-term injury, especially with the new five-man bench rule potentially encouraging clubs to manage loads and minutes even more aggressively.
Rookies are a special case. Champion Data basically projects rookies by price because they have no AFL data. That means the basement rookies get projected around 22 points, which is hilarious, but also understandable. CD isn’t trying to split Jagga Smith from Cody Anderson. At that price point, a rookie is a rookie until proven otherwise.
That means this formula isn’t designed to select rookies. But it is useful for one thing: showing how much extra output you need from a more expensive rookie.
A basement rookie like Liam Riedy ($119,900) has a benchmark of 52. A slightly more expensive rookie like Dyson Sharp ($149,500) has a benchmark of 56. The difference isn’t huge, but the concept matters, if you’re paying more for a rookie, you’re expecting more.
It’s also worth pointing out that Champion Data will sometimes give a more proper projection for rookie-priced players who have played AFL before (the recycled types). In those cases CD isn’t using the generic rookie projection; they’ll use historical data. But in practice those numbers are still heavily sub-affected and often meaningless in the real SuperCoach world. If a rookie-priced player scores 22–35, they’re not a cash cow, they’re a red dot waiting to happen. You only pick them if you believe they can score 50–65 and become playable.
That’s where this simple benchmark actually helps. It doesn’t magically predict rookies, but it does highlight that if you’re paying extra for an “expensive rookie”, you need them to lift their game and justify it.
To make this practical, I grabbed a simple sample: the most popular defenders in the game right now. No cherry picking. No “this is my secret smokey.” Just the guys everyone is clicking into their teams.
|
Player
|
Price
|
Formula expected score
|
CD projection
|
Derek projected
|
Difference
|
|---|---|---|---|---|---|
|
Zeke Uwland
|
$199,000
|
62.4
|
25
|
60
|
-2.4
|
|
Connor Rozee
|
$568,500
|
108.6
|
114
|
114
|
+5.4
|
|
Nas Wanganeen-Milera
|
$622,300
|
115.3
|
110
|
110
|
-5.3
|
|
Jai Serong
|
$119,900
|
52.5
|
19
|
50
|
-2.5
|
|
Josh Lindsay
|
$122,500
|
52.8
|
23
|
60
|
+7.2
|
|
Keidean Coleman
|
$233,800
|
66.7
|
34
|
60
|
-6.7
|
|
Sam Grlj
|
$172,000
|
59.0
|
32
|
60
|
+1.0
|
|
Colby McKercher
|
$449,600
|
93.7
|
87
|
90
|
-3.7
|
|
Miles Bergman
|
$447,400
|
93.4
|
77
|
85
|
-8.4
|
|
Nic Newman
|
$439,300
|
92.4
|
93
|
93
|
+0.6
|
|
Jordon Clark
|
$568,000
|
108.5
|
96
|
96
|
-12.5
|
|
Lachie Whitfield
|
$599,200
|
112.4
|
135
|
120
|
+7.6
|
We all know SuperCoach prices rise and fall based on performance (and Champion Data gives us the break-evens), so what happens is simple: a player who starts the season overpriced might drop $60k–$100k and suddenly become interesting. Another bloke might be flying early, go up $120k, and no longer be value even though he’s still scoring well.
That’s where the benchmark helps. Every time a player’s price changes, your “value score” changes too. You can rerun the formula quickly and ask the same question: at this new price, what does he need to average over the next three weeks to actually be value?
It’s especially useful for premiums who have a couple of bad games, get cheaper, then hit a soft patch of fixtures. That’s often the best time to jump, when other coaches are rage-trading them out and you’re calmly buying a discounted premium as value.
So yes, I use this to pick a starting team… but I also use it as a simple “is he cheap enough yet?” tool throughout the year.
Wow…..genius…..
Now, if only I could find a way to convince my brain to do it and not stay on the “silly” autopilot.
Very nice.
Once the season starts, is SC premium the only way to access the CD 3rd projection?
CD is just a start. the formula is where i think the value is. even if you just take any player’s price (add $300k and divide by 8000) you get, what i think is the pass-mark. How you come up with what they will actually score is between you and the almighty, CD just takes the bias away, sort of.
Wow Derek. If that is the start of your writings I look forward to more amazing stuff. I try and run my team by the numbers but nothing as exact as that. You have confirmed a lot of my selection.
Thanks for that.
Thanks Derek. With the 3 week projections, would that mean we are ignoring players who have the early bye?
the players with early bye were included, i just had to make a manual adjustment to CD’s numbers to accomodate, otherwise it looked horrible.
Love ya work Derek, thanks.
One of the best reads I’ve had on this site, and something that will be of genuine use. Great stuff.
Why do you think McKercher will only go 90?
i’m giving him 3 more than CD 😉
its a big discussion topic, where he will play this year.
if he plays mainly in defense and gets the majority of kick ins and increases his tackle count, he could score 100+, but there is a chance that he plays in the guts or at least splits his time 50/50, if this happens i think he will be closer to the 90 average
im in the ‘midfield’ camp at the moment, especially with Wardlaw getting injured.
it will be a good watch during the practice games
Thanks for the reply, appreciate hearing the reasoning
It’s interesting I think you’re right to be cautious around the role though not sure Wardlaw impacts him at all, after moving to defence in R13, sharing KOs with Daniel he averaged 102, it’s where he played his best footy so just not sure why they’d change it.
agree, why change it? Wardlaw was going to be a mainstay in the guts, now they need Mckercher, maybe.
early in the preseason there was news from North Melbourne that he was ‘training’ with the midfield and there was talk that Hardeman and Harvey were training in the half-back role (put them on watchlist). havn’t heard any updates, but definately worth to be careful
last time i looked, he was in my team. like everyone else, a little bit of bias and hoping he has the role, needs 94 to be a value pick
Nice work Derek.
If I’m following you then, with Bont (as the highest cost player). This is ignoring the early bye for now.
– His formula expected score is 125.85 ((706800+300000)/8000).
– His CD projected 3 rd ave is 132.33 (though this score doesn’t strictly matter for your formula, you just use as a guide for your own score projections).
– I expect he’ll average 120 over these 3 rds.
So based on your formula, he’s overpriced (if my 120 is correct). But if his price was $650,000, your formula suggests an expected score of 118.75, which if I think he’ll average 120 means he’s slight value at that price?
That is exactly how I work it out, nothing to complicated.
In reality I probably look beyond 3 weeks for a player I’m keen to select, but for players who I don’t start with I try not to think too far ahead as their price can change quickly in 3 weeks.
I agree with Your estimate on Bont, Dogs start isn’t great and he’s on the other side of 30 now, most players don’t improve their scores after 30. I can see other players going past him this year, happens to the best of them
There is so much noise in the SC community and it is a genuine breath of fresh air to read something like this.
People fall into a similar pitfall in picking SuperCoach players as they do in the stock market, and it goes something like this:
The pitfall: “I think Nvidia is a great company. I want to invest in the AI trend and I think they are going to grow rapidly with all of this new demand for AI.”
In reality, it doesn’t necessarily matter what you think in-itself. It matters what you think, relative to what the market thinks, which in-turn determines the valuation of that company and the price you will pay to buy stock.
The same logic can be applied to SuperCoach. It doesn’t matter what you think a player will score in-itself. It matters what they score relative to what they averaged last year, which in-turn sets their price for this season.
The fact is, every price is set by the average score a player had last year. If we assume that we can only pick players that played last season, every team that is worth $10m at the start of the season will have had the exact same average points last season: $10m worth.
Therefore, your decision-making process in building a team should not be “I’m going to pick Nasiah Wanganeen-Milera because I think he is the best defender in the competition.”
It should be: “I’m going to pick Jack Steele, because I think he will average 10-15 more points than last season, given the changes to his role and the midfield he is playing in” (as an example).
Nasiah could be the best defender in the competition; while still underscoring his average from last year. The SC player who picks a player with greater upside and uses the extra cash saved elsewhere in their team will likely be better-off on aggregate.
Pick players such that you are maximising the difference between your team’s average points last season, and what you think they will average this season. That’s how you maximise your team’s scoring.
Great read Derek.
Great points, but the ultimate balance is in the limited trades we have, so somewhere in between is the answer. You can’t have a team full of Jack Steele’s scoring 108.
For me it’s all in the team value, which needs to be $14m+ around the byes.
Most people only focus on the cash cows that add value, for me it’s just as important that the premiums don’t lose value. Most people will answer it doesn’t matter if they are a keeper, but it does matter because they used up more if your starting $10m, and a Bont at the start of the season is a larger % of your team value than he is at the mid-point.
Great Stuff Derek.
Finding Value, and timing your trades correctly is such a huge part of SC. I’m sure this formula will help a heap of the SCT community.
Looking forward to what else you have install for 2026.
So good, thanks Derek. So true when under pressure sometimes you can’t check the spreadsheet… and that’s when season defining errors can be made.
Great article, concur with the rest. One point that resonates, I’ve definitely been guilty of looking too far ahead and pinning someone as a ‘season keeper’ when so much can happen to prevent that from becoming reality. Will definitely remind myself to look at the short term more regularly
Agree. 2025 I had only 6 players (Gawn, Macrae, Sheezel, Brayshaw, Smith and Rozee) that I started and finished the season with.
That’s such a great read Derek! Really nice simple formula that had me going through my whole team- when combined with bye theory it seems to give a totally different lens to view selections. We’ll done!
Also, for all the mathematicians, you can reverse the formula.
If you have a projected score for a player, multiply it by 8,000 and minus $300,000 = Fair Value Price
How do you get the CD projections?