Why use TooSerious?
Why use TooSerious?
So, why is TooSerious one of the biggest fantasy football support sites on the internet?
To answer that, you’ve got to ask yourself the following question: What makes for a good year in Supercoach?
Two things play a huge part in your year.
1) Your starting squad.
2) How well you trade throughout the year.
So, how can we help? Well firstly- your starting squad. We have made it our duty to provide excellent analysis of which premium players will do you well, which mid priced players look to be stepping up and which rookies will give you the best chance to cash up.
Ok, so I would love to take *all* the credit for that, but we’ve also got a fantastic array of writers on board as well as a fantastic community backing it up. Just take a look through the comments, any of them really, for an inciteful and intellegent discussion on Supercoach.
Now, while we offer advice, we also have a tab up the top there called stats. Under here, you can find a history of every player playing the game- as well as snapshots of how they were going in years gone by. We’ve got the usual stats as well as your more fantasy specific stats like highest/lowest salary/points. Standard deviations as well as handy “average against” including a players last 3 game average over the past three weeks, against the team they’re coming up against and at the ground they will be playing at.
Now, I’m hoping that that will be enough to get you a decent starting squad. But once you’ve got one of them, the rest of your season will come down to Team Management. Which is the area that we shine.
The first place to look is over on that stats tab. Over there, the first thing to notice would be the breakeven column. This column informs you what score a player will need to get in order to hold their current salary. Next are the salary movement fields (next round, Two Rounds, Three rounds and Movement (3 rounds)). These fields will give you a fairly accurate approximation of a players salary if they manage to get their average. I say fairly accurate, because salary movement cannot be perfectly predicted because it depends on what the league scores in relation to their salaries. Needless to say though, it is accurate enough to get a great idea on which players to jump on.
However, if this isn’t enough, next to every player, you will find a little calculator. Clicking here will enable you to enter your predicted score for a player, for the rest of the season, in order to see what effect that will have on their salary. This can be a fantastic tool for working out when a player is reaching their peak, or bottoming out.
And as we all know, Supercoach is won by trading out your cashcows when they are at a peak price and trading in your premium players when they are at their lowest.
Outside of that, there’s also other handy stuff that pops up. You’ve got the ability to enter in your team which will help you track injuries as they are updated round to round. (players are coloured in red when injured and orange for the rounds that they are due back (because we all know that not everyone comes back when they are supposed to; Ottens and Stevie J say Hi) – check out the last few years, with the exact cause and duration of the injury availiable when moused over). When I’m not lazy, I’ll get the teams entered in each round so you can easily see which of your players have or haven’t been named that week.
We also have the gameday pages. Here we have a pre-game page for each game (which can be a fantastic tool when selecting a captain (well if you don’t have Ablett.)). Here you will also find our live scoring which will track your team as well as the scores from every other player out there.
So there you go, a quick synopsis on how using TooSerious will improve your game, both in the preseason and throughout the year.
And of course, since we are constantly evolving, we’re always open to suggestions on how we can improve this place for you all. So if you have any ideas, or even if you would like to try your hand at writing an article or two, then drop me a line.
Its good to see this site kicking on, it deserves to, best Supercoach site on the net.
The resources are excellent, but its the senior posters that do it for me, give their opinions freely and call a spade a spade.
Well done for what you have created Walesy, and well done to all though who contribute and share their wisdom.
Why use it; so you can hear how the best Supercoachers win the day!
Even when you don’t win, to see the strategies around getting the job done…it makes the process very worthwhile.
And as for improvements to the site and the community, I’m never satisfied hehe. I would like to see, over time (and probably thinking a few years!!):
1) A search function on the main page so you can hit a player and see their stats, and in a web box at the bottom of the page, see all the comments made by people about them. Nicknames might be hard, but the rest I see as functionally doable. It’s similar to what FF does, but with the depth of insight in our comments, I think it would end up better.
Walesy, myself and a few other writers be able to work on this full-time. An absolute pipe dream! (What am I smoking!)
2) One of us wins the overall Supercoach this year, and then in future years, we do the double of SC and DT. And we also take home the Falcon this year.
3) We smash the rivals in the League of Leagues competition.
4) We create a ranking system unique to the site that adequately assesses players and their current value. I hope to have something better than the quick one I did earlier, before the season starts.
5) An ever-improving points predictor that works. It needs to take into account opponent, conditions, form, etc. But the beauty would be each score feeds in and makes the future score closer.
6) The Herald-Sun link us on their SC page or Superfooty so we hit a wider audience.
7) Our leagues to eventually be playing for Grand Final tickets rather than (or as well as) cold hard cash.
2008 without TooSerious – >10,000 place. 2009 with TooSerious – 92nd. Enough said.
I dont comment a lot but i am always checking break evens on this site and also reading all the posts and replies to pick bits and pieces of info. Great job guys keep it up!
Haha to #7 Lucas. Dream big!
Whatever you’re smoking, I’m sure that I’m not allowed to have it in my current state but save some for me in 5 months, yeah? 
As for the rest, stuff is in the works. Here’s hoping it pans out. Good minds think alike on #1. Iva been pestering walesy about some search functionality and the comment boxes for a little while now. When the poor man gets a chance to catch a breath, I’ll jump on him about it again…
92nd, well done!
I finished around 120th last year thanks to some of the excellent advice on this site. Best site on the net for supercoach by far!
Just wanted to comment on this one, and thank Walesy and all the other site contributors. Very similarly to Timmy, I was about 12,000th in 2008, and about 200th in 2009 due to finding TooSerious in about round 3. Let’s hope that having TooSerious from the get-go in 2010 will put me into the top 100 =)
Keep up the excellent work!
On the GF tickets, I reckon they could be prizes about the time that the Pies are in the mood and the form to win them.
And they are given out on the condition that they smuggle us in in a backpack, right?
Great conditions there Walesy
Lucas, you know that comment was asking for it don’t ya mate
Sounds like TooSerious users made most of the top 200! 195th for me last year
A lot due to the site.
Hi Guys,
267th for me last year, hoping to crack the top 100 this year. Keep up the good work, clearly the best supercoach site on the net.
Hehe you guys owned me last year!
Ended up embarrassed after a 1750 on my wedding day in Round 2. Thankfully the wedding was a great success, and now I am primed for a huge year.
Still, I am happy in a competitive league with such a disarray of a start I was able to take a back-to-back flag and had one over 2700 score (pity it was the wrong round!)
If you can bring some suggestions to the table particularly in terms of what you’d like to read, we will be happy to hear your thoughts. I like the idea of the discussion so we can get the majority of the point across in the main text. I am sure Best Buys will return, and Griff I am fully aware we need to get our team reviews up and running.
Other than that, Walesy loves his Monday update, and I enjoy the mid-round swearing from our perfectionists who think 2350 is not good enough! With the improvements to the gameday page, I think that will be quite a hit!
League Teams we will probably have on a Thursday or Friday morning once lists are in. And I can certainly see a quiet point of the week maybe Tuesday for a review from our Leagues. I can guarantee that’s an area I want a lot more debate, banter and fun this year as we go from strength to strength.
An additional benefit of this great site that might have perhaps gone unnoticed to a lot of the semi-seirous/serious players here, is with the ever growing list of statistical measures being made available, a supercoacher can take as much or as little out of the stats as they like and the site caters for everyone in that respect.
Whether you want the latest and greatest to give yourself the best possible chance of measuring when a cash cows peak and a premiums badpatch will coincide to enable what could be a killer trade, or whether you just want a friendly, easy-to-navigate layout to check a certain players’ price and the position in which he can be chosen, this site offers it all.
Posters here at all all different levels in relation to supercoach experience and everyone is always willing to answer questions as best they can with supporting eveidence and hunch, incorporating both their understanding/expertise of not just the pure stats, but quite often a deeper understanding of their club of choice which can be invaluable to a person who knows little about said club (eg.a midpriced player may at first glance look like a bargain, but there could be an up and comer who has flown under the radar during preseason training that might knock that midpricer out of the 22)
Read it, love it, spread the word, and add another entertaining dimension to a brilliant Aussie game by joining in the discussions.
As a second year SuperCoacher I have to admit this site was invaluable when making trades last season. I’m also busy trying to piece together this year’s squad and look forward to reading more great hints
Your knowledge of rookies will hopefully save me from some first season mistakes.
Cheers!
Lucas, your point #5 above is an interesting one. You know what you really need to do to go somewhere with predicting though? regression analysis. Averages are very crude as you’re well aware. a 3 game average can be distorted by so many things (high variance in score, structural change in a player’s skill, role or team) and only ever measures one variable at once. the beauty of a regression is that it controls for all variables simultaneously and gives you corellation coefficients which give a measure of the strength of each effect.
What you want to do is create a model with all factors which you think might affect a player’s score, eg:
* opponent
* ground
* number of years in the system
* team’s position on the ladder
* recent injury
* 3-game average (to measure whether ‘hot streaks’ is a real phenomenon)
* field position
and so on. some of these stats already exist in the database, some could be added relatively easy, and some probably can’t.
you could construct 2 types of models here. one for individual players. you’d only be able to do it for players with some minimum number of games (maybe 75 or so) but what you’d get is a predictive model that says, for eg, that Gary Ablett scores 20ppg better at Skilled stadium and 15ppg worse vs Fremantle or something. Now, I’m not sure how robust this model would be given that a lot of these conditions are going to have small sample sizes, but it would be better than a raw average and you could do some analysis to see how significant the stats are.
The other model you could make is a global model which could ask questions like do midfielders score better at the gabba, do 3rd year players score better than second year players, do players from one team consistently score higher against another particular team, do forwards score worse against one particular team and so on.
tbh I’m disappointed Champion hasn’t tried to do something like this for the prospectus. They’ve got those tables near the end with players averages vs teams which are 90% meaningless imo. they give absolutely no indication of whether those historic averages have any future predictive power and in many cases they specifically note that they dont. that’s the beuaty of a regression, it gives you a lot more comfort that what you find is meaningful.
anyway, i’ve got some economics training and I think I still have my stats package from uni. I could honestly have a shot at doing something like this if I had the data – lmk if you’re interested Lucas/Walsey.
Spud, aw mate- you’re making me tear up over here. :_)
JJ, what’s a LMK, and how do I give you my data! I’ll drop you an email
Oh wait, it’s let me know. Thanks google, and thank you urban dictionary.
Haha don’t you dare Walesy
JJ, feel free to hit me up if you want a hand bud as ive spent 6 years at uni doing econometrics mate and am not long out of uni so its still semi-fresh(albeit the last 2 years were playing with finance/market data and was slightly different in its approach), nothing but model forecasting using eviews/ANOVA(excel addon) etc. Though i don’t still have access to the uni programs which were extremely well built, i’m sure the excel addons can handle at least some level of multiple reg. Would be happy to discuss what variables needed to be included, how to approach the model, etc etc. If nothing else itd be nice to do something and NOT have it marked
Ground type should be easy enough to factor in using dummys, and im thinking perhaps even throwing in variabes to denote what year player the person was at the time as im sure the weightings for a ‘years_played’ variable would be rather important as different positions tend to peak at different ages. What might take some thought though is how to factor in games in which the player was injured.
Like you said, i too was rather suprised that they didnt include something of a similar nature in the prospectus, but perhaps they have tried over and over and found it simply too unpredictable for any forecast results to be statistically significant? Which could well make sense given the nature of the same and sometimes differing agendas for team coaches when their side isnt doing too well *cough* tanking *cough*
Sounds great spud. I don’t like giving my email out publicly, can you email Too.Serious.Team.Management@gmail.com and get them to put you in touch with me? It’d be great to have someone who’s been doing this more recently, It’s been five years now since I did any econometric classes! I’ve got a copy of eviews lying around and my wife uses SPSS and Genstat, but you’re right, the excel addon’s probably going to be enough.
You could definitely be right re champion, it’s possible that nothing has good predictive power and sample sizes are too small to be meaningful. If that was the case though, I would have thought they’d NOT report the team against averages! I think the first thing to do will be to do some simple correlations of variables to see if it looks like they’ve got any predictive power at all. Anyway, happy to chat over email.
It’s interesting I have been involved in financial data management in my time, as has Walesy.
Fantasy football seems to be the activity that attracts those with a love for the game and a talent for numbers.
In terms of dealing with the t word (which incidentally shouldn’t be an issue until GC and GWS are settled into the comp) then I suggest a variable called “team form”. If your teams up the creek, so will your scores often be (Hodge an example last year).
Also I gather you’ve already seen the Walesy calculated predicted score in the Predicted Scores option. I am sure Walesy, myself, Braydog and a few others came up with some settings, and it eventually made it into live, but we never got feedback, or checked how right/wrong they were.
I’d want ours to be better than BigFooty (and demonstratively so) before we start spruiking!!
The other thing I would like to do is integrate the predicted score into the calculator page for a player, so you can auto-create the future scores (this would unfortunately take out some elements such as team form unless auto assumption on the fly) and more importantly a realistic guide of future prices. This would lead you to work out the optimal time to do a trade.
(Walesy – offline if you want to send the current code to generate the predicted score that would be good)
Have you tried to test the predictive power of the score calculator at all by running it on historical numbers and seeing how good it is from week to week? Eg. plug in the data as it would have been at the start of last season, and see what the variance of the predicted numbers to the actual numbers were. If you’re getting within 10% week on, week off that’s probably pretty good (especially considering many players are varying by 30% or more every week). Something interesting to do would be to check how much better the formula is at predicting the score than a simple last 10 game average.
Click on the Predicted Score button to get it up. I haven’t run any script on it because until 2 weeks ago, it was slow as molasis.
But now I could. At a simple look though (Starting from round 2 cause I didn’t generate the round 1 scores) For Ablett last year:
PPS – ACTUAL
147 – 139
153 – 150
202 – 197 – woohoo!
168 – 149
159 – 91 – awwwww
122 – injured
150 – injured
133 – 149
131 – 150
110 – 175 – awwwww
93 – 98
133 – 202 – awwwww
158 – 105 – awwwww
96 – injured
111 – 124
135 – 139
145 – 115
141 – 81 – awwwww
134 – 164
142 – 122
104 – 146
Obviously some deficiencies.
Our aim with the original predictor was to try to get within 10%
And Ablett…that’s an easy candidate. He gets 130 every week!
How about someone with a bit of up and down to them like Goodes or ROK!
Another variable which would really throw a spanner in the works and is something that im struggling to figuring away around model wise, is the issue of injuries to your own team mates.
Consider a teams #2 midfield for example. Say you play against a team that historically utilisers only one tagger that always takes the oppositions #1 midfielder. By using a “VS_TeamX” variable, the #1 players estimated score will reflect the fact he has historically copped a tag when playing against team X and therefore his estimated score will likely be lower. However, midfielder #2 has normally been allowed to run around untagged/weak tag on him because he isnt the most dangerous.
The issue here is if the #1 midfielder is injured or rested in the week these two sides meet. All else being equal, midfielder #2 is now likely to cop the number one tag which has every chance of severely hindering his score (say, lingy is tagging him) while the model, even accounting for the vs_team difference, will be estimating his score based on him being allowed to run freely.
The same could be said for the #2 or even #3 tall forward if a better forward is injured, and similarly with defenders if a #2 defender who is used to taking kosi is suddenly forced to shutdown roo because the #1 defender is not on the park.
Anyone have any ideas as to how this could be incorporated as im struggling to even come up with a thought. I believe the situation could be more common than we’d like to think as well as it could happen even midgame. Eg. referring back to the midfield tag scenario – if gazza would normally get the a.joseph tag it would allow jimmy to run rampart. If, however, for whatever reason, gaz is having an unusually quiet day (not as a result of the tag – perhaps he is having an emotional moment about his ex), then a.joseph could be told at half time that gaz isnt damaging enough to worry about and he should try and shut down jimmy. This has the potential once again to throw jimmys score estimate way off.
you’re running into the limits of statistical analysis here, you’re never really going to be able to capture that kind of thing. Likewise for things like a change in a player’s role, change in the quality of disposal by their teammates and change in team tactics, you just can’t be precise about it. The best you can do would be to try to get an overall sense of the ‘midfield’ or ‘forward’ pressure that a team exerts – measured by a global analysis of how well players of certain positions score against that team – and then seeing how much that variable helps in predicting a particular players score. You can’t get down into the micro player-on-player tag level, you can only hope that that effect is picked up by other variables.
Hey guys. Just wondering if anyone has done any stats on players ave returning from injury compared to beforehand. Im thinking in particular ACLs. It would be interesting to see how much lower aves are in the first season back. And how long it takes to return to their previous ave. Dont mean to sound greedy – feel free to tell me to bugger off and look it up myself!
ACL’s hey… that’s a good idea.
Sadly my injury stats don’t go back very far 
I wouldnt use Max Bailey for that study
Think we all know by now what happens when he returns from injury…seems to miss the place that badly that he puts himself in for another 12 month stint, almost like a repeat offender!
Malceski will be a good example, particularly if he burns this year.
I notice we have a little ad also on the main blog page. Let’s hope google can start paying more of the mortgage and the infrastructure for the site can keep a quick response.
Just a word of warning, i know it sounds bizzare but do not in any way encourage your site users to click on the banners even in the most obscure or joking way. I’ve known tiny little sites have their google ads pulled because of a joke the owner said in the comments. I think they’ve got text recognition bots floating around and they just insta-ban, no questions asked, no right of appeal.
oh, and malceski’s already an of what happens with coming back from ACL. 2007 avg 100. 2008 avg (before doing knee) 60. 2009 average (after coming back from the super surgery) 50.
Yeah, definitely not JJ, no telling people to, no inciting, nothing. Just gunna try my best to avoid talking about them in general.
Hi Boys,
Only just found your site where have you been for the last few years i mustn’t of look to hard to find you but i am glad i have now.
Is the pps on the predictor page what they have to avg for the first 3 round to stop the price from dropping.
Cheers Keep up the good work. Manboobies
Nah, the PPS is just a predicted score that we’ve been working on slowly.
For the first three rounds, a player will need to average their average. Plus about 9% extra to keep even.
But it all makes a lot more sense once the season is up and running.
Cheers Walesy
will you also be putting up a rate your team blog so people can’t get feed back ?
during the week before kick off mate.
Any earlier and a fair amount of the advise becomes invalidated.
@JJ the thing about Malceski is you could be able to draw a conclusion that the quick knee op can get you back and playing quickly but you take a full 12 months still to get back to your best.
From a SC value prospective, that type of news is gold. You get him when he’s a gun, drop him when he does the ACL and don’t return until 12 months after the recovery. Then whammo you get him cheap and he burns.
Not saying I’m certain to take him on this year, but he’s one of many tasty backline options.