O-scores analysis of Barebones

Official results are at the Barebones.ca

Absolute all standings:


Absolute Women standings - very interesting in comparison with official results



By course analysis is here

Interesting subset of the course analysis with Women only


As always (!) and (!!) means 7.5% and 15% above the estimate for this runner, and (?), (??) correspondingly below.Additional mark {new} shows runners whose name mentioned first time this year and therefore their score is not reliable due to lack of data.

NAOC top performers

Following table show those who improved significantly relative to their own average during the NAOC event

Runner	Class	Club	Power	Improvement
Patricia Mace	F45+	QOC	52.6	47.7%
Mark Mace	M55+	QOC	51.9	46.8%
Oriana Riley	F-10	DVOA	25.2	46.0%
Maxwell McWhirt	M-16	HOC	38.3	40.5%
Lucas Lyons	M-10	ROC	66.3	38.5%
Brian Ellis	M	GVOC	66.5	35.6%
Sue Kuestner	F	COC	51.4	30.9%
John Charlow	M80+	Ramblers	30.9	30.7%
William Cusworth	M40+	COC	92.3	30.4%
Adam Caplan-Bricker	M-18	NEOC	69.9	30.0%
Dana Breseman	F-16	COC	61.1	30.0%
Adeline Charles	F	FWOC	35.3	29.5%
Jane Pataki	F65+	A/L	29.3	28.0%
Eileen Breseman	F50+	COC	67.5	27.9%
Rob Rapkins	M60+	Ugly Gully	78.5	26.8%
Nicole Lennon	M	QOC	31	26.5%
Michael Lyons	M45+	ROC	82.9	25.0%
Rick Worner	M60+	ROC	67.4	24.9%
Rick Breseman	M55+	COC	87.9	24.1%
Raymond Chung	M45+	TOC	65.7	23.0%
Linda Moore	F70+	LVOC	51.4	23.0%
Glen Tryson	M55+	EMPO	91.5	23.0%
Vern Nelson	M-21+	CAN	63.9	22.8%
Heidi Cusworth	M40+	COC	49.4	21.9%
David Yee	M45+	NEOC	75.1	21.8%
Peggy Dickison	F50+	OK	83.5	21.2%
Shirley Donald	F70+	KOC	43.6	21.1%
Alex Kerr	M75+	GVOC	61.5	21.0%
Mike Poulsen	M50+	CROC	64.7	19.5%
Kathleen Lennon	F45+	QOC	62.9	18.0%
Barbara Bryant	F45+	NEOC	64.5	16.9%
Masha Konkov	F-10	BAOC	41.5	16.4%
Liam Tasker	F	NEOC	59	15.6%
Jonathan Rickel	M-12	TSN	59.3	14.5%
Michael Svoboda	M50+	SLOC	63.5	14.3%
Margaret Ellis	F60+	GVOC	67.3	13.7%
Scott Drumm	M45+	CROC	53.1	13.2%
Lennart Lundgren	M60+	FWOC	54.1	12.9%
Max Lennon	M-14	QOC	59	10.3%
Greg Chatfield	M60+	Ugly Gully	80.6	9.4%
Kimball Forrest	M55+	ARCT	99.1	8.4%

Enjoy

O-scores version of the Björn Kjellström Cup

Following discussion at Attackpoint, here is the O-scores evaluation of the CAN/USA team efforts


(EXCEL Source file is here) and here are overall Performance list and O-speed table

Following table of runners was used, top 3 O-scores from each country, same people as in discussion above.

Runner	Class	Club	LONG	MIDDLE	Short
Alison Crocker	F	USA	114.4	109.4
Angelica Riley	F	USA	90.8
Carol Ross	F	CAN	93.9	106.9	97.3
Ekaterina Orekhova	F	USA		96.5	90.7
Louise Oram	F	CAN	115.4	119.1	101.6
Marie-Cat Bruno	F	CAN	87.4	92.4
Nicki Rehn	F	CAN			89.8
Samantha Saeger	F	USA	112.9		107.8
Sandra Zurcher	F	USA		112.1	104
Boris Granovskiy	M	USA	128.1	127.4	120.4
Brian May	M	CAN			118.1
Eric Bone	M	USA	131.3	136.1	121.5
Mike Smith	M	CAN	141.7	143.3	125.5
Nick Duca	M	CAN	126.5	134.2
Patrick Goeres	M	CAN	140.3	133	131.9
Ross Smith	M	USA	132.3	145.4	118.6

Following table of results was compiled (plain sum of all related scores)

	Club	Class
	CAN		CAN Total	USA		USA Total
Values	F	M		F	M
LONG	296.7	408.5	705.2	318.1	391.7	709.8
MIDDLE	318.4	410.5	728.9	318	408.9	726.9
Short	288.7	375.5	664.2	302.5	360.5	663
			2098.3			2099.7

Resulting sum of scores for each country is amazingly close (2098.3 and 2099.7)

Accuracy of the score calculation doesn't allow to call winner on the margin of 1.4 points.


What is clear is that USA ladies and Canadian men are significantly better than their corresponding rivals

Billygoat results 1979-2010

Here is even more questionable analysis:

thanks to  times published in the convenient format at billygoat.org I made O-speed compilation of all Billygoats 1979-2010

Notice that average score for all events 1979-1999 is 50, because Billygoat is the only event available for these years and average runners by definition must have score 50.

Power at the view above is calculated using current power of the runner ( calculated within last rolling year), so evaluations do not matter much. If one goes to the event view, all powers for early years will be identical to the scores, as Billygoat currently the only event for each year before 1999.

O-scores analysis of West point meet

Official results are on the USMAOC web page

Absolute all standings:


1.Ross Smith (M-21+), CSU *141.3*(1)
2.Boris Granovskiy (M-21+), CSU *140.2*(2)
3.Daniel Griff (M), BAOC *131.8*(3)
...
17.. Samantha Saeger (F-21+), NEOC *119.4*(17)

Absolute Women standings



Samantha Saeger (F-21+), NEOC *119.4*(1)
Jenny Arvidsson (F35+), DVOA *110.4*(2)
Erin Nielsen (F-21+), UNO *106.3*(3)

By course analysis is here

Interesting subset of the course analysis with Women only


As always (!) and (!!) means 7.5% and 15% above the estimate for this runner, and (?), (??) correspondingly below.Additional mark {new} was added recently. It shows runners whose name mentioned first time this year and therefore their score is not reliable due to lack of data.

Terrain was on average .1100-1200 GV/km (takes 11-12 minutes for 100 point runner to go through the nominal km of the race.
Examples of 100 point runners are

Steve Olafsen (M50+), UNO (99.9)
John Campbell (M50+), DVOA (99.7)

Absolute standings analysis:

All above mentioned top runners were running blue.
Top red runner was
Vadim Masalkov (M40+), DVOA *123.4*(11)

Top green runner is

Peter Gagarin (M65+), CSU *106.3*(36)

Top Brown runner is
David Cady (M65+), BFLO *87.5*(78)

Top Orange runner is

Frank Boscoe (N/A), EMPO *82.0*(86)

Top Yellow runner is

Evalin Brautigam (F-14), WCOC *81.7*(88)

Top White runner is

Peter Zakrevski (M-12), DVOA *66.8*(145)


Women standings analysis:
  
Top runners mentioned above were running mix of red and blue, so there is no way to say for sure who is best in red or blue.


Top green runner is without any doubt
Alison Campbell (F-20), DVOA *99.2*(5)



next by the O-speed core is top runner on Yellow!!!

Evalin Brautigam (F-14), WCOC *81.7*(13)


The top Brown runner is 

Janet Tryson (F55+), EMPO *73.0*(17)


Top orange runner is 

Heather Campbell (F-16), DVOA *64.6*(27)

and top white runner is

Hannah Collinsworth (F-10), ROC *30.1*(68)

Here is updated rolling A-series Women  rankings
Here is updated  rolling Men A-series Rankings

Enjoy.

P.S. Extreme performers are below:

Runner	Class	Club	improve
Eugene Frolenko	M-18	DVOA	32.9%
John-Eric Nelson	M65+	WCOC	30.6%
Richard Nietupski	M60+	WCOC	30.0%
Yuri Zakrevski	M-20	DVOA	24.6%
Mark Mace	M55+	QOC	22.4%
Rhonda DeWeese	F55+	WCOC	21.3%
Robert Field	M45+	QOC	18.3%
Geoffrey Connor	N/A	HVO	18.2%
Kean Williams	M50+	COC	15.0%
Daniel Schaublin	M50+	HVO	14.9%
Eric Smith	M65+	CNYO	13.8%
Lisa Carr	F40+	NTOA	13.2%
Evalin Brautigam	F-14	WCOC	13.0%
Lynn Aldrich	F60+	DVOA	12.3%
Nicolai Mejevoi	N/A	none	12.2%
Linda Kohn	F60+	ROC	11.7%
Candice Raines	F55+	EMPO	11.5%
Melanie Sergiev	F-14	GMOC	11.5%
Rick Breseman	M55+	COC	11.3%
Nathan Collinsworth	M-10	ROC	10.5%
Elisabeth Chiera	F75+	HVO	10.2%
Dmitry Lavrov	M45+	HVO	10.0%
Piotr Zielczynski	M50+	HVO	-10.1%
Karl Ahlswede	M45+	DVOA	-10.8%
Tim Parson	M50+	NEOC	-10.9%
Joan Roos	F70+	BAOC	-11.0%
Bernie Breton	N/A	HVO	-11.3%
Ed Hicks	M75+	HVO	-11.5%
Julia Zielczynska	F-14	HVO	-12.4%
Alex Bishop	M50+	QOC	-12.7%
Phil Bricker	N/A	NEOC	-13.3%
Bob Fink	M60+	DVOA	-13.7%
Michael Lyons	M45+	ROC	-14.8%
Hannah Collinsworth	F-10	ROC	-15.2%
Dan Felitsky	M35+	SDO	-15.3%
Donna Fluegel	F50+	WCOC	-15.7%
Nadezhda Popova	F60+	HVO	-16.0%
Julie Keim	F-21+	SVO	-16.4%
Brendan Shields	M-21+	CSU	-18.2%
Caroline Fleming	F45+	NEOC	-20.2%
Walter Lyons	M65+	BFLO	-21.1%
Mary Jo Childs	F55+	GMOC	-21.4%
Betsy Hawes	F65+	HVO	-24.1%
Val Duca	F40+	STARS	-24.8%
Zachary Lyons	M-14	ROC	-27.4%

ROC Webster park event Analysis from O-scores

Official results are at the ROC web Page

Thanks to Steve Tylock for intense communication and for providing me with data for this analysis

NOTE: Data for Orange, Yellow and White course might be not reliable due to lack of data for intermediate and beginning ROC orienteers. It will become more reliable with time


Absolute All standings


Absolute Women standings



By course analysis is here

As always (!) and (!!) means 7.5% and 15% above the estimate for this runner, and (?), (??) correspondingly below.Additional mark {new} was added recently. It shows runners whose name mentioned first time this year and therefore their score is not reliable due to lack of data.

Terrain was on average  ~900 GV/km which usually means course was fast



Here is rolling ROC Ladies Ranking  (Unofficial, incomplete O-scores version, using only data I have available now)

Men ROC rolling rankings is here   (Unofficial, incomplete O-scores version, using only data I have available now)


Top performers are below:

Runner	Class	improve
Steven Tylock	M45+	15.1%
Karl Kolva	M85+	13.4%
Robert Bundy	M65+	12.5%
Patricia Lyons	F55+	11.1%
Lucas Lyons	M-10	9.1%

O-Scores calculation methodology

External links:

http://www.attackpoint.org/discussionthread.jsp/message_149323 discussion about GV calculation

Original Methology post at Geocities is no longer available and I do not know where it was moved.

http://www.geocities.com/nikdangerdvm/03methods.html - original write-up of the GV algorithm calculations.

Methodology was called by many people as cumbersome and I will try to explain here in my words.

I will quote the Methodology where applicable and explain practical application details.

Originally Adapted for USOF from Wyatt Riley's BAOC ranking rules, 1999.

One more time adapted by S. Krechetov 

Definitions:  

There are four items here and they all depend on each other. Must be consumed as a whole dish. Don’t get disappointed until done reading.

1. Runner Local Power (RLP)   = Race Gnarliness Value (GV) divided by Runners Time (RT)

RLPⁱ_r = GV_r /RTⁱ_r; where r is running over all races (1..N_R) and i is running over all runners (1.. N^I)

 Example: GV is 5000, your time was 1:40:00 or 100 minutes. Your  RLP for that race is 5000/100 = 50.

2. Runner Global Power  (RGP)   = plain average of Runner Local Power (RLP) over all races

RGPⁱ = 1/N_R*sum_r(RLPⁱ_r)

3. Runners Race Difficulty (RRD) =  Runner Global Power (RGP)  multiplied by  Runners Time (RT)

RRDⁱ_r = RGPⁱ*RT_r;

Example: If your RGP = 80, and your RT = 60 minutes, your RRD would be 80*60=4800

4. Race Gnarliness Value (GV)  =  harmonic average (reciprocal of  average of reciprocal values ) of Runners Race Difficulties (RRD) for all runners in current race

1/GV_r = 1/ N^I *sum_i(1/ RRDⁱ_r);

Example:

·         John  has  RGP = 100 and runs RACE in 30 min. (RRD = 100 * 30 = 3000)

·         Mary has  RGP = 60 and runs RACE in 100 min. (RRD = 60 * 100 = 6000)

·         1/ GV = ½ (1/(100*30) + 1/(60*100)) = 1/4000

Then

·         GV = 4000

Some observations:

• If you are on average twice as fast as somebody, you should end up with about twice their score.

Practical Implementation details.

• Input data for the algorithm are three columns: Person, Race and Time.  No other information is needed
• All valid finishes of the season are used. Valid finishes are times (not OT, DNF, MSP, etc...).
• Algorithm is recursive over items 1-4. Must be stopped after next iteration changes results by negligible amount.
• Initial conditions are Runner Local Power (RLP) which can be set to any positive nonzero number
• Algorithm converges to the same point independently on initial conditions. For simplicity  all runners can be given RLP  = 100 at first step
• Algorithm is linear relative to initial conditions. Meaning that if all initial  RLP are increased by factor F, the resulting GV, and RGP will be increased by the same factor.
• The only nontrivial output of the algorithm is set of GV, which is one number per race. The rest of the results can be immediately derived from GV and Runners Times (RT)
• At the last step, all RGP RGP, GV are normalized so that  1/ N^I*sum_i(RGPⁱ) = 50 and the rest of the quantities are changed proportionally.

Additional Notes

• Final RLPⁱ_r is score of the runner for this race. Using scores one can calculate various Ranking scores. (RS) characterizing performance of particular runner in this particular discipline.
• pick top 4 scores  and average them (No Tail)
• pick 4 scores and half of the rest and average them (Tail)
• pick only A meet scores and  perform Tail or No-Tail calculations
• pick only A-meet Sprints and perform Tail or No-Tail calculations
• Pick everything but Sprints and  perform Tail or No-Tail calculations
• Pick only Extra Long races and  perform Tail or No-Tail calculations
• Pick only races of this particular Color and perform Tail or No-Tail calculations
• Pick only races organized by this particular club and perform Tail or No-Tail calculations
• Pick only A meet races and only one Color of Races, perform "Tail" calculation with them (USOF scores)

All above mentioned possibilities and more are implemented in the O-scores database interface