Hockey is not a Money ball Sport:
Most analytics look at table scrap Affects in hockey.
Looking for Moneyball binary ( 2 outcomes) from hockey actions that have multiple 3+ success% based outcomes.
Baseball has the large affect outcomes of 100 yrs ago being played the same by all teams.
So table scrap moneyball (2 outcome analytics has value.)
Hockeynnalytics has failed to identify all large % affects thru Sequence of Events (SOE) mapping.
That allows you to identify the best and worse ways to play the gm.
Current hockey analytics people are trained academically.
Using theoretical approach to the gm.
But they are in communities that see small% affect mistakes as valueable.
Their is no real current value to their work cause of the huge% errors in their data.
High Resolution Complex outcome analysis:
Being high function Autistic I was real world trained in mapping all theoretical outcomes and identifying real world method (sports human machine play) By age 8.
My father (Offered lead in Orbit based assets for 1st yrs of European Space agency) was a lead on design of Avro Arrow, Appollo lunar lander & Service Module, Coversion of Hawk Missle to first self guided SAM, Design of first Earth Resources Technology Satelite (LandSat), Design of SeaSat basis for all orbit based Sub locating, Area 25: magnetic guided Nuclear powered Rockets. He travelled the world setting up other countries Orbit asset tracking divisions.
I was exposed to a group of friends from the projects in “late 50’s, 69’s and 70’s who designed things like Maglev.
O% mistake/ high% success approach is the only way:
I was educated that 0% mistake analysis was critical.
Mistakes have huge outcomes. Look up Aerospace occurances.
January 28, 1986
February 1, 2003
Their are fields in Academia that see 15% affects as a huge success.
A poor standard.
Multiple high resolution affects Methodology to achieve desired high% success goal:
I have 50+ theories that lead to an identification of 26 yrs of repeat final 4 roster cores based on my High danger shot density shot area observation of 50+ hrs ago and Closed shot identification of 45+ yrscago.
The champ roster theory I presented on here around April 17-20 pre VGK exp draft ( stated would be a GA cup final team) is now the only Pro sports roster proof based on high outcome affects.
VGK selected 100% of players in Expansion that fit my Roster Core Theory. They made the final which I stated.
1.00 to 2.00 GAA to win 4 gm in a Conf or Cup series:
Most Analytic people fail to understand that final 4 series winning teams only give up 4g (1.00 GAA) to 8g (2.00 GAA) in their Series 4 wins.
Get strong GA players they are cap cheap:
When you build a roster your value acquisition of Strong even & PK ga reduction players.
This yr median.
Evg/60 2.64
STG/60 7.16
7.16/2.64 = 2.71
PPG are 2.71 times easier than evg.
PK reduction is 2.71 times harder than evg reduction.
PK special teams +ve goal dif affect is 5.42 times harder than PP goal dif affect
Seek strong top 125 fwd evg and evp depth:
1.65 assist are given for each goal.
Evg are a superior direct outcome affect than EVA1
EV1 are superior to EVA2.
That is a reflection of average pass completion % compounding.
Non 1.000 values being timed by each other the failure rate potential increases for every extra pass needed.
I used this Methodology to look for strong fwd Prispects in the draft:
Homeplate theory:
Is based on shot density succes from an x,y locations.
Open / closed shots:
All non scoreable Corsi must be identified
( Blocks + misses + hit goalie = Wall) so that the open shots are identified. Pucks that hit into a Goalie have 0% chance of going in.
Pucks that deflect off a goalie Are scoreable.
hit posts with zero off data value:
Corsi that hit posts and do nit go in are not a shot.
They are a miss.
They have zero off performance value but are important in the measure of a open shot reduction analysis.
(Blocks + misses + closed shots/ CA
Their are 7 open holes:
Their are 7 holes in net elevation based Y,Z location on every plane established by a goalies set position (Angle & distance from net elevation).
7 open hole shot maps:
So their are 7 identified y,z range ( holes) maps on a single holes open shots x,y Success map. Fir a group of equal result based set positions?
A Goalie is a wall:
With arms, legs, head to Move to stop open shots.
The entire Hockey analytics world works of a belief that all shots from the same x,y location have the Same chance of going in.
If you take 2 nets and cover one completely with plywood and the other completely open.
You cannot tell a kid you have the same chance of put a shot in the net with both nets.
their are slot of standard open shot maps:
Shots from a single location can
- be open or closed
- hit 7 diffrent open shot hole locations (must be a hole not A Goalie)
- have difrent hole sizes based on set positions of goalie.
Neanderthal DNA:
Their is Bio Evolutionary targeting built in the human brain.
But instead if trying to hit the body (Mammoth/goalie) in the visualized plane. We are suppose to hit the open space which is counter intuitive targeting that must be mentally and visually practised.
Low resolution thinking leads to mistakes:
The more detailed a look at things the better we understand the best way to succeed at something.
Complex mutivariable outcome Rocket Science comes from many military non grade 12 grades who have complex Triarch design/renovate; build/ maintain; operate/run individuals.
Low resolution thought leads extensive changes. I have found theoretical design will go thru 40-45 changes before respectability in construction.
Shot mass = shot volume x expected sSH syuccess density (each set position hole size map)
Elite Fwds are identified by:
their Homeplate penetration by then are high comp% passes and open shot targeting Succes.
No fwds has the Same xSH% ( ie xG)
Elite Dmen are identified by:
-the Open xSave% ((Open shots - xG)/open shot) baseline they establish to their side.
-A dman covering a partners abandoned side does not get charged to the covering dman.
- a dman coming On Does not get charged for Coverage to a side not being established from Last Player back dman (Rover) Going off. It is still the abandoning dmans affect.
Elite Goalies are identified by:
Their +ve save% performance over the xSave% baseline established to each side.
Most of the large affects of the gm have been identified by me.
And used to get 26 yrs repeat roster and system play success.
No Real results:
Current Analytics stumbles along only using 1/2 of goal density identification for shot mass equation.
No closed shot exclusion = no real Science.
PDO has no value:
Each individual player has their own averages.
3 fwd xSH%
2 Dmen with their own xSave% to their side.
1 goalie with 2 Save% from each dman side xSave% to be measured against.
No combination of 7 Position averages are the same.
Their is no Simple War in complex sports:
In 07/08 I created a 3D graph of Desjardins Team, Comp, FO ZS
With team and comp set into
8 groups (upper/lower 1st/2nd/3rd/4th)
and 8 FO ZS groups; 8 x 8 x 8 = 512 possible player situation averages to get a season based xAvg for all 512 groups of play.
Coaches kill Corsi analytics:
Coaches choices in ZS with or without pocession leads to a 40% range in error of CF and CA data.
Eliminating Coach ZS affect on player analytics:
But quite quickly saw the need ZS to be broken up into 4 seperate zone start 3 D graphs with 4 Team, 4 Comp & 6 ZS% = 96 avg
FOZS with pocession (FO win)
FOZS without pocession ( Loss)
On the fly (bench ZS) with pocession
On the fly ( bench ZS) without pocession.
You get to identify a +ve or -ve performance for any of the 3D player situations 96 (team, comp, FOZS%) x 4 graph = 384 avg That a player is put in by the Coach.
3f - 2D -1G def sys vs. 3F - 1Rover - 1D -1G:
Off Dmen abandon 2D - 1G def of high danger shot area to chase offence. They occupy a higher% of fwd zone space. They take off zone pocession from fwds. They are a hybrid of Fwd/ Dmen based on zone space.
NZ transition Defence affects:
Corsi results are dictated By Zone entry success which has a large dependence on weather a NZ def is run or not.
- A Coach can dictate the fwds approach to NZ def which affects zone entry/ CA.
- Off dman who abandons their def responsibility affects Fwds and dpartners approach to NZ transition/ Zone entry/ CA.
Eliminate NZ def affect in performance:
4 further diferentiations must be done to get true player performance.
Fwd NZ Def run in 3F - 1R - 1D - 1G structure
fwd NZ Def run in 3F - 2D - 1G structure
Fwd NZ def Not run in 3-1-1-1 Structure
Fwd NZ def Not Run in 3 - 2 - 1 Structure
Corsi against is not a Defenceman measure:
Current Hockey analytics believes these 2 Dmen should have the same xCA
- 1 dman sees a high% of on the fly bench change without pocession while coming on after No fwd NZ def has been run in a (3 - 1 - 1 -1) attack of opp OZ and high% of def FOZS.
- 1 dman sees a lot of on the fly Bench change With pocession in a (3F - 2D - 1G) attack of opp OZ and a high% of OFF FZS.
I just laugh at how bad low resolution analytics taught in Academics is.
I literarly stated on Lowetide That Sports IQ would be a gm changer cause of the extreme complex humAn machine analytics I identified could be used.
Shook my head at low res stuff presented!
Just a short user guide of my Analytucs that nailed the first Campionship Sports proof.
PS: did this during my Rainman and Beautifulmind sessions (wife calked it) from 10 pm. To 2-4 am.
During the last 13 yrs of chasing modeling and prototype data fir engineering on the ATCO Lead on Coal Power Plant Conversion to Nat. gas.
Dealing with cancer last 2 1/2 yrs.
Though thevPlant I worked at in Alberta was a critical Node in NA VAR Network.