JR-Academy-Web-Post-Image

 

Introduction:

Huzzah!

Greetings and welcome to this, the first in an ambitious Draftstars Academy weekly series.

Jock has graciously charged me with the task of exploring the new and exciting frontier that is Draftstars. I will start by honing my skill and cunning by gathering performance data within the safe confines of Jock’s free-play Draftstars Academy. I will develop and sharpen excel battle tools on a weekly basis, tracking performance and tinkering until my Daily Fantasy selection muscles are lithe and responsive.

If I prove combat worthy within the confines of Jock’s free-play environment, I will then bound with proven strategy, cunning and a certain pre-determined degree of confidence into the pay-to-play arena.

The significance of this task is such that I have decided it best be tackled with the most stringent and rigorous of approaches. Yes Community, I have decided to employ the proven Scientific Method as my guide; hypothesising, formulating, gathering, testing, analysing, forming conclusions.

Let us begin.

ENTER THIS WEEK’S JOCK REYNOLDS DRAFTSTARS ACADEMY CONTEST HERE

Draftstars Todays Contest


 

Title:

The Effect of Applying an Analytical System-Based Approach to Performance within the Daily Fantasy Environment

Hypothesis:

If Daily Fantasy lineups are selected using historic performance based data linked with clearly defined strategic guidelines then it will result in successful gamesmanship as measured by a positive return on investment.

Method:

1.     Build Drafstars Optimisation Machine – “DOM”– a player score projections tool

Weekly player projections have been formulated using the following four key statistics;

–       Long Run Scoring History & St. Deviation (x0.25 Weighting Factor)

–       2017 Season Scoring History and St. Deviation (x0.3 Weighting Factor)

–       Last Three Game Scoring History & St. Deviation (Anchor Statistic)

–       Scoring History V Opponent (Adjustment Factor)

The “Ceiling” statistic has been calculated taking into account each player’s recent and historic scoring standard deviation trends. It aims to give a feel for what an above average game may deliver.

Of extreme importance is the “$/Pt.” statistic. This is a basic calculation that, based on the forecasted score, gives us a player value rating. It places a dollar value on each point a player is predicted to deliver us – An extremely important element when working within a team Salary Cap!

"DOM" Draftstars Score Forecasts - Round 11 - FRE v COL

PlayerPOSLong Run Av. (SD)2017 Av. (SD)Last 3 Av. (SD)Av. V Opp.ForecastCeilingPrice$/Pt.
S PendleburyMid109.07 (19.5)112.1 (25.19)119 (28.48)102.00111.54160.32$16,250145.68
A TreloarMid107.33 (19.37)113.56 (23.04)117.5 (12.02)127.00116.18152.47$15,700135.13
T AdamsDef/Mid98.04 (29.65)117.5 (21.56)109.33 (10.69)92.00106.06147.32$15,650147.56
S SidebottomMid104.46 (21.88)103.9 (24.85)116.33 (20.03)77.00102.36146.87$14,900145.56
B GrundyRuc89.66 (25.58)106.7 (16.98)112.33 (6.11)96.50102.94135.39$14,750143.28
C BlakelyMid78.65 (26.06)88.4 (31.82)116.67 (18.61)67.0090.65141.65$14,000154.44
L NealeMid98.73 (29.24)99.6 (21.25)87.33 (24.19)76.6791.16140.95$13,650149.74
J SmithDef77.21 (25.42)78.9 (28.78)88 (34.07)96.0084.71143.57$12,900152.28
B HillMid/Fwd74.51 (24.7)94.3 (31.27)87.33 (36.53)66.6682.72144.39$12,750154.13
N FyfeMid100.92 (20.57)92.2 (16.63)81.67 (7.64)87.0089.74119.63$12,700141.51
M WaltersFwd74.6 (27.69)69.1 (36.3)97.67 (52.54)90.6783.08160.77$12,550151.05
J HoweDef75.65 (24.16)89 (23.89)94 (29.61)65.0083.03134.81$12,500150.55
J CrispMid86.8 (18.29)84.2 (21.14)80.67 (18.56)92.5085.32123.98$12,450145.92
D MundyMid95.92 (23.13)88.2 (26.9)78.33 (28.54)86.0086.34138.72$12,350143.03
D WellsMid80.53 (24.61)86.6 (7.8)82 (6)101.2386.93112.54$12,300141.49
B MaynardDef65.97 (21.74)69 (19.04)81.33 (16.8)123.0082.89121.29$12,000144.76
L GreenwoodMid/Fwd86.46 (25.46)70.13 (14.89)78 (9.54)87.0079.13112.39$11,900150.38
S HillMid88.43 (22.35)82.43 (21.4)61.5 (10.61)87.6778.40114.64$11,750149.88
J ElliottFwd80.05 (22.83)76.14 (23.93)90 (11.14)64.5078.75117.35$11,400144.76
L WellerDef/Fwd64.83 (21.08)77 (17.73)84.67 (28.71)52.0071.87116.88$11,400158.63
T PhillipsMid/Fwd73.53 (20.41)73.56 (16.99)77 (13)92.0078.27111.88$11,300144.37
B ReidDef66.79 (22.75)73.43 (23.73)60 (0)93.0071.99118.46$11,250156.28
D PearceMid77.72 (22.49)72.6 (10.57)71.67 (14.29)72.0073.22104.79$11,150152.27
A SandilandsRuc83.68 (18.72)83.33 (9.42)80 (4.24)108.0087.34108.93$11,100127.10
W Hoskin-ElliottMid/Fwd65.67 (27.64)82 (22.36)76.67 (9.29)76.32100.26$10,550138.23
C MayneFwd74.09 (22.02)63 (9.54)58.3368.5589.58$10,350150.99
H CrozierDef61.95 (22.54)69.25 (10.7)69.33 (6.66)60.0065.9792.57$10,200154.63
M JohnsonDef72.8 (22.65)66.5 (16.57)66.67 (20.03)87.0071.91111.42$10,050139.76
A FasoloFwd68.76 (23.98)66.9 (24.83)64 (25.36)86.0070.22119.67$10,050143.12
G IbbotsonDef65.31 (21.69)54.8 (9.38)52.67 (9.61)95.0064.3091.42$10,000155.52
D TuckerMid63.05 (18.47)59.29 (11.9)69 (16.97)42.0063.8791.05$9,800153.44
E LangdonMid/Fwd65.38 (21.58)70.67 (19.94)67.5 (24.75)68.9298.70$9,750141.47
J De GoeyMid/Fwd69 (19.69)64.25 (7.23)65.67 (8.14)67.5066.2889.65$9,700146.36
D MooreFwd52.64 (20.71)57.2 (24.09)81 (14)72.5491.19$9,500130.96
J GriffinRuc59.83 (16.81)68 (10.39)62 (0)60.0778.17$9,450157.32
L SpurrDef73.04 (21.23)72.8 (20.44)58.33 (10.79)53.0064.5599.52$9,350144.85
T SheridanDef60.63 (21.84)47.8 (27.11)46.3354.2186.85$9,350172.47
M TabernerFwd54.58 (24.84)54 (43.75)54.33 (31.09)49.0053.22119.67$9,350175.70
S KerstenFwd53.89 (23.89)62.2 (21.26)66 (30.61)36.0056.44106.95$9,300164.78
T BroomheadFwd56.75 (22.94)60.71 (20.88)74 (0)95.0070.76114.59$9,200130.01
L DunnDef65.96 (17.91)59 (10.22)63 (12.17)66.2663.0489.91$9,200145.93
M ScharenbergDef57.8 (20.87)67 (0)67 (0)67.2493.51$9,150136.08
C SutcliffeDef66.77 (17.1)61.83 (11.02)55.33 (12.9)65.6761.6488.98$8,900144.39
J BlairFwd67.9 (18.54)51.83 (9.91)50.67 (8.5)76.0059.5384.16$8,800147.83
C McCarthyFwd53.42 (21.85)62.3 (16.48)54 (11.53)64.0058.3791.61$8,600147.33
B GreyMid62.27 (14.97)60 (16.8)52.67 (12.34)54.9175.67$8,400152.98
T GoldsackDef54 (17.37)53.6 (9.91)60.67 (9.29)34.5051.9876.37$8,150156.79
E HughesDef56.2 (20.92)48.44 (21.16)56 (8.89)54.3276.55$8,050148.20
J HamlingDef48.36 (12.95)53.7 (16.26)65.67 (10.02)61.3171.64$8,000130.48
H SchadeDef46.43 (14.41)53.25 (12.07)50.5 (2.12)51.7359.48$7,900152.72
J AishMid64.68 (24.73)46.33 (11.68)40 (5.66)79.0054.6482.68$7,400135.44
2.     Analyse predictive scores as delivered by DOM to establish a successful forecasting model by gathering weekly comparison data
This forms a key part of the experiment. Using forecasts as supplied by www.fantasyinsider.com.au, DOM performance data will be routinely checked against Fantasy Insider’s forecasting model and adjusted as required.

A challenge. A game within a game. DOM v Fantasy Insider!

I do expect DOM to be soundly beaten initially given that the Fantasy Insiders modelling draws on masses of additional data such as Venue, Home/Away factors, Weather Conditions, however, I am excited by DOM’s humble beginnings.

If you would like to build your own DOM and create your own challenge, Fantasy Insider are offering a wonderful trial where you can access score projections across the entire round.

DOM Projections V Fantasy Insider Projections

PlayerDOM's ForecastF.I's ForecastDifferenceActual Score% DOM Error% FANTASY INSIDER Error
Totals3613.103658.89-45.79
A Treloar116.18113.702.48
S Pendlebury111.54113.00-1.46
T Adams106.06112.90-6.84
B Grundy102.9493.409.54
S Sidebottom102.36105.30-2.94
L Neale91.1698.80-7.64
C Blakely90.6589.301.35
N Fyfe89.7491.00-1.26
A Sandilands87.3479.168.18
D Wells86.9386.900.03
D Mundy86.3485.001.34
J Crisp85.3286.80-1.48
J Smith84.7184.200.51
M Walters83.0875.008.08
J Howe83.0391.70-8.67
B Maynard82.8972.6010.29
B Hill82.7289.90-7.18
L Greenwood79.1375.403.73
J Elliott78.7579.60-0.85
S Hill78.4084.20-5.80
T Phillips78.2775.003.27
D Pearce73.2275.40-2.18
M Johnson71.9170.101.81
L Weller71.8771.000.87
T Broomhead70.7661.908.86
A Fasolo70.2267.103.12
C Mayne68.5573.03-4.48
J De Goey66.2871.70-5.42
H Crozier65.9771.60-5.63
L Spurr64.5574.20-9.65
G Ibbotson64.3061.902.40
L Dunn63.0463.30-0.26
C Sutcliffe61.6468.50-6.86
W Hoskin-Elliott76.3278.50-2.18
J Blair59.5360.40-0.87
D Tucker63.8770.40-6.53
C McCarthy58.3761.50-3.13
S Kersten56.4463.00-6.56
E Langdon68.9266.602.32
T Sheridan54.2167.90-13.69
M Taberner53.2260.50-7.28
D Moore72.5459.0013.54
T Goldsack51.9856.70-4.72
M Scharenberg67.2468.30-1.06
J Griffin60.0759.001.07
B Grey54.9157.70-2.79
J Hamling61.3157.803.51
E Hughes54.3259.00-4.68
3.     Apply DOM forecasts and key selection strategies to finalise a weekly contest lineup

IMPORTANT NOTE: Given that each week this post will be uploaded PRIOR to final team selections, potential updates will be re-posted following the release of squads. 

And now the important task of building a squad based on DOM’s projections. 

Week 1 Selection Notes:

Blindly trusting in projection tools is dangerous. Let’s take Lachie Neale as a prime example.

DOM has forecasted a score for Neale of 91.16. As described, an adjustment factor based on average scores verses opponent has come into play here; Neale’s last three scores against Collingwood have been 82(away), 120(home) and 23(away). The 23 Neale scored occurred in Round One at Etihad in 2014. This has, in my opinion, negatively impacted on his “Opponent” average and his projection resulting in an unjust value rating.

I do like the Neale selection and feel he will easily outperform DOM’s forecasted score.

The challenge in using these selections is balancing Value with Point Score while hitting the Salary Cap constraint – THIS IS JUST LIKE SUPERCOACH!

I will now reveal my final LineUp for this Sunday’s game along side a Fantasy Insider team that was generated using their LineUp Crunching Tool (a tool that does the Value v Point score balancing for you).

My Weekly LineUp for Sunday’s JR Draftstars Academy Contest;

**UPDATED 30 Minutes prior to kickoff due to the Sandilands LATE OUT

DOM-v-FI-lineups

I will not delve too deep into selection strategy in Week 1, however – I will make one important point which did guide me in my final selection process.

I have settled on a relatively safe team selected with a risk minimisation strategy. If my aim was to finish first then more risks would be taken. Players such as Walters, Hill and Pendlebury may hit their ceiling and reward owners with a very high finishing rank. I am forecasting that these players, for their price, offer too great a risk in terms of consistency of rank in the long term.

Jock’s exclusive Draftstars Academy contest is returning a reward to anyone who finishes ranked within the top 35 places. I am aiming to finish 35th.

Wish me luck my friends – I look forward with great anticipation to the discussion in the comments below. This will indeed be an interesting journey!
Kind regards,

Peter J Higginbotham

 

ENTER THIS WEEK’S CONTEST HERE

 

 Fantasy Insider have a two week free trial on the go at the minute, they also have a SuperCoach ‘who should I pick’ tool which may arouse you.. jump on over and give our great supporters a try!

 

DFS_post_cruncher-(1)


25 Comments

Jamers · 01/06/2017 at 18:29

Hi Higgo, looking forward to tracking this over the next weeks. I've had no luck in CoachKings so far on the Sunday contest it seems as if the teams that win each week always have a few picks that I would never have thought about bringing in before the game. I've tried adding some points of difference a few times but that hasn't worked yet.

    P_J_Higgo · 01/06/2017 at 18:46

    Keep at it Jamers. I hope you have managed a few qualifications into next week's CoachKings $10k Quarter Final. Points of difference are important, keep trying my friend. I will be entering the above lineup into a venue on Sunday. Most probably down at The Cove in Patterson lakes.

      Jamers · 01/06/2017 at 18:50

      Thanks Peter – I just saw that Sandilands and Luke Ryan are in. Both monties on Sunday surely?

    SC_Kev7 · 01/06/2017 at 19:05

    Keep at it, Jamers. I found it really difficult at the start of my CoachKings journey to turn off my SuperCoach mind and get used to a different scoring system, regularly finishing 400th+. Started using DS start of the season and since they use the same scoring system, I'm a pretty consistent top 100 on the play at home comps. Just haven't cracked the top 6… yet.

    Have a play around with the tables above

SheriffsBigRig · 01/06/2017 at 18:45

Amazing Higgo!! Will be following this formula with great curiosity! My CoachKings selections this years so far haven't been getting the results I've been hoping for. Hopefully this is the key to turning around my fortunes. Love your work Higgo

Patch · 01/06/2017 at 18:46

I'm very, very excited – the community getting a foothold in CoachKings, Fantasy Insider and now Draft Stars means we've got fantasy footy coming out the wazoo! Hopefully that means with enough practice I might even get good at it!

I love any insight into your beautiful mind, Dearest Higgo, but this week I was hampered my traumatic experiences reading scientific methodology in school meaning I get a mild aneurysm whenever I see the words "hypothethis" and "method" one after the other.

    SC_Kev7 · 01/06/2017 at 19:16

    Oh yeah, I see those big sciency looking words and I just tune ou… hey look! That dogs got a fluffy tail!

      Patch · 02/06/2017 at 10:21

      "Ah, the ballet…"

discojim · 01/06/2017 at 18:52

Have entered a lineup and gone Lyndon Dunn as my smokie on sunday. Nice tables tool. Could you do it for all games? I would like to use it for the coach kings at my local. Thanks Higg.

LEKD0G · 01/06/2017 at 18:59

Now this is some sexy maths I can get around

BarronVonCrow · 01/06/2017 at 19:05

I may need to re-read it a few times for it to make sense to me Higgo, but I like what I understand so far.

Look at Jock though, not just content to create CoachKings for us, his massive reach is spreading across every damn format of fantasy footy available. I love it!

Gaz · 01/06/2017 at 19:21

This is like a gateway to gambling

    Bells E Bubb · 01/06/2017 at 23:53

    Yep.
    Normally I’d be dead set against it. But whatever they need to do to get a podcast out; I’m supportive.
    Grownups here xan make up their own minds. Kids better keep well out as gambling keeps you poor and is totally for mugs.

SC_Kev7 · 01/06/2017 at 19:29

Love the amount of work you've poured into this Higgo, already made 5 changes to my initial team I was happy with. Cheers mate

    Boydo · 01/06/2017 at 21:49

    Notice both teams in post have McCarthy, Spur, Treloar and De Goey. Using this as my template and adding a few uniques.

P_J_Higgo · 02/06/2017 at 09:08

TEAM SELECTION UPDATE (9am Friday)

Watching and waiting for a Sandilands final confirmation & news on potential value picks; Ryan, Cox, Brown and Crocker.

FREMANTLE
Fremantle has dropped midfielder Danyle Pearce for and will regain ruckman Aaron Sandilands. Draftee Luke Ryan, who is yet to make his debut, has been named in the squad, alongside defender Tom Sheridan and midfielder Ed Langdon on the extended bench.

COLLINGWOOD
Callum Brown, Mason Cox, Ben Crocker, Jackson Ramsay and Henry Schade are all in the mix to take on the Dockers after being added to the extended 25-man line up.

Pierce34 · 02/06/2017 at 10:33

So wait, Josh Smith has a higher ceiling than Nat Fyfe?

Other than that LOVE IT!

Do disagree with you having Treloar as the highest projected player on the field tonight though

    P_J_Higgo · 02/06/2017 at 11:49

    Just the feedback we need, Pierce34!

    Yes, the ceiling calculation seems quite off as demonstrated by your Josh Smith example.

    I will be adjusting inputs accordingly.

      jockreynolds · 02/06/2017 at 13:29

      Should see Higgo at the minute folks – tapping away at his spreadsheets, hasn't spoken for hours, don't even reckon he realises I've been sitting here in the bungalow next to him for the last few hours! As focussed as I've seen the great man – and that's saying quite a bit haa

dpwoodford · 02/06/2017 at 14:13

With ceiling numbers it's often worth comparing the output of your algorithm to a players previous historic top-score. 131 for Josh Smith vs 137 for Nat Fyfe. The term is used in different ways too, we (Fantasy Insider) tend to view them as confidence intervals, so the goal is if the game was played 100,000 times, a player would be between floor and ceiling 85% of the time, where as for others a ceiling is the 1 in 100 outcome. Depends a bit on your risk profile!

In our updated lineup Sandilands does make the cut, he's a better upside play than Griffin for sure.

    Jamers · 02/06/2017 at 18:00

    DP Woodford in the comments! Shit just got real

      P_J_Higgo · 02/06/2017 at 18:31

      Agreed. Will be working closely with DP, Jamers – a fine DFS brain indeed.

Eric_the_Red · 02/06/2017 at 19:27

No NSW entries, Jock?

Gambit · 04/06/2017 at 17:29

Must have been a memo to get all the gang to post here, haha good work patch, higgo,jock and crow. doesnt look obvious at all 🙂

web designing · 13/04/2018 at 22:12

Thanks – that's a very useful writeup!
web designing courses in Chandigarh

Comments are closed.