Which Ironman event gives me the best chance of qualifying for Hawaii?

 

INTRODUCTION.. 1

ELITE REFERENCE TIME [ERT] 2

HAMMOND QUALIFICATION COEFFICIENT [HQC] 2

YOUR RACE SELECTION METHODOLOGY.. Error! Bookmark not defined.
AGE GROUP HQC TABLES
FORTHCOMING ENHANCEMENTS TO THIS ANALYSIS

 

 

INTRODUCTION

Is this a question that you have asked yourself? More than likely you have if you have aspirations for Hawaii. If you are an improving triathlete who is knocking on the door of a Hawaii spot then your race selection can be critical to your chances of getting there sooner rather than later. How much of a difference can race selection make? Well I calculate that for my age group there could be a difference of 6% in the overall performance required to qualify between the easiest event and the hardest. At this point I stress that this is a 6% true performance difference. Take a minute out here and calculate what 6% might mean for you if you make race selection a lottery. Put it another way, if you are confident of qualifying, how critical would 6% added on to your time be to your qualification chances? Feel confident now?

 

So is it that easy to sift through the available data and evaluate your choices? My own situation obviously prompted me to go through all this. I am a 40-44 Age Grouper who been in Triathlon for less than 2 years. But Iím dedicated and want to get to Kona as soon as I can. A rudimentary look through what kind of time it is going to take to get there throws up more questions than answers. For example, in my category, an 11h15 minute time at Wisconsin (2005) would have got me to Kona in 2006. But in Switzerland it would have taking an incredible 9h49 to secure the last qualification spot. Germany seems like a great bet because they had 25 slots in my age group for Kona 2006, much better than say Western Australia that just had 2 slots. Would it therefore make sense to go to Frankfurt instead of Busselton? In fact, the answer was no in 2006! How can I determine if I stand more chance of grabbing the last of the 8 slots at Lanzarotte (a comfortable 10h44 in 2006) versus having to push myself to do 10h06 in Brazil to get one of only 5 slots available? Incredibly my analysis shows that Brazil is the better option.

 

Before we go any further letís have a look at the entire scope of Ironman Races in the 2007 schedule. Apologies to Race Directors of 70.3 events with qualifying slots, Iíll get that info included at some point. I began by creating an event profile for all the races including the inauguration year, the time zone, race date, average weather conditions, participation numbers, slot allocations, basic course info for the Swim, Bike and Run, cut-off times along with the course records. I also included an element I will explain later called the Elite Reference Time. This table is available on my Ironman Event Profile Table. I would be grateful to anyone who has any complementary information to add as I have not been able to garner 100% of the data elements. I am also particularly interested in the Bike and Run elevation numbers if anyone has done the courses with an altimeter. The majority of this information is not really required for my analysis; however at some point you will want to review this data so see if the course that offers you the best chance from a pure performance basis also meets your particular preferences in a host of other areas. If you canít do hills, then donít go to Lanzarote, if you donít like swimming in salt water, then donít go to Busselton, if you donít like running in the heat then perhaps Malaysia is not your best option despite what the analysis kicks out.

 

So where do we start with all the analysis. There are two key variables between the races, the time and the number of slots. But if what I have claimed in the opening is true, then both of these factors can lead me in the wrong direction. It is patently obvious that courses like Lanzarotte, Nice and the Sherbourne (all with bike elevations over 2000 metres) are not going to produce comparable race times with courses like Austria, Germany and Arizona which are essentially flat. Salt water swims are likely faster than fresh water swims, doubly so when the organisers leave 400+ metres off the course (France 2006). What about the marathon elevation, Sherbourne has an incredible 800 meters of total climb versus nothing for Nice, itís just that in Nice you are running in temperatures about 10c hotter. So you can do all the data analysis you like on the times recorded, but trying to keep track of the course changes the organisers make each year and then factoring in the weather conditions will soon have you ripping out your hair in large tufts. Even if the race directors change nothing from one year to the next, differences in the temperature, humidity and wind will still render the race times incomparable.

 

Now consider the second factor, the number of slots available. The 25 spots that will go to my age group in Germany is going to grab a lot of attention from Kona hopefuls, whereas the 3 spots offered in Malaysia may pass unnoticed leading to a significant disparity in both the quantity and quality of the field. Even that doesnít tell the whole story. The 8th and final slot offered in Lanzarotte was taken by the 10th place finisher. But the 6th and last spot in Austria rolled all the way down to 14th place.

 

Have I sufficiently confused you now? Have I made something which you thought might be a 15 minute decision armed with a web browser and notepad into a confusing nightmare with your $500 entry fee and Kona dreams lying shredded along with your training plan?Good. Were I more mercenary than I am, I could now convince you that purchasing my analysis for 10% of your next IM entry fee would be a prudent insurance policy to make the most of your investment. However, good natured chap that I am, Iíll just go ahead and explain it to you.

 

Now Iíll preface all this by saying that even all the analysis I have done is not absolutely bullet proof even though it is pretty good. I will endeavour to point out the holes in the amour as we go. Finally as your financial broker will always tell you, ďpast performance is no guarantee of future resultsĒ.

 

ELITE REFERENCE TIME [ERT]

 

TABLE 1

 

 

 

 

 

 

 

Elite Reference Time

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Grand Total

Austria

 

08:18:00

08:20:25

08:23:46

08:16:52

 

08:19:46

Germany

 

 

 

08:32:00

08:22:28

 

08:27:14

Western Australia

 

 

 

08:32:50

08:32:25

08:25:52

08:30:22

Arizona

 

 

 

08:43:11

08:26:39

08:33:54

08:34:35

Switzerland

08:42:43

08:38:38

08:31:22

08:34:27

08:27:21

 

08:34:40

Australia

 

 

 

08:35:32

08:35:15

 

08:35:23

Florida

08:31:35

08:37:09

08:37:08

08:39:22

08:38:26

08:34:31

08:36:29

Brazil

 

08:28:56

08:32:41

09:00:08

08:25:41

 

08:36:52

New Zealand

08:39:07

08:36:50

08:41:21

08:37:08

 

08:40:05

08:38:54

South Africa

 

 

 

08:37:21

08:39:05

08:45:11

08:40:32

Canada

 

08:43:55

08:38:22

08:40:33

08:48:45

 

08:42:54

Coeur D'alene

 

09:03:31

08:54:39

08:35:03

08:51:04

 

08:51:04

Malaysia

 

 

 

 

08:52:57

08:51:41

08:52:19

Lake Placid

09:00:13

08:57:15

08:45:55

08:51:35

08:47:52

 

08:52:36

France

 

 

 

08:59:04

08:46:42

 

08:52:53

United Kingdom

 

 

 

09:05:42

08:45:06

 

08:55:24

Japan

 

08:56:22

09:02:31

08:55:49

08:53:05

 

08:56:57

Lanzarote

09:00:00

 

09:04:22

09:07:49

09:00:35

 

09:03:11

Korea

08:55:34

09:19:09

 

09:07:14

 

 

09:07:19

Wisconsin

 

09:02:38

09:06:10

09:01:08

09:09:44

09:23:14

09:08:35

Grand Total

08:48:45

08:47:29

08:45:00

08:46:16

08:41:02

08:44:55

08:45:01

The first objective, and really the key to the whole exercise, is to neutralise the differences between the races. There have been studies done to achieve this by comparing the performance of the Kona participants at Kona versus their qualifying races in order to quantify the relative difficulties of the qualifying events. I think this approach certainly has its merits, but also has some pitfalls.

 

 

1.       The condition of the athletes in the two races. Did they peak better for Kona than they did for their qualifying race?

2.       The time difference between the qualifying event and Kona. Wisconsin is over a year away and the qualifiers have time to have an off season, improve and re-peak for Kona the next year. No such luck for the Korea qualifiers.

3.       The differences in the courses. Qualifiers from courses with large bike elevations are typically less suited to Kona. Will a comparison of their respective performances lead to a conclusion that they qualified from a weaker event?

 

I intend to perform that analysis at a later date as a secondary validation; however my initial approach at determining the relative strengths of the race is via another route. I have taken the times of the top 5 finishers in each race (including age groupers that came in the top 5) and calculated the average of that time. This time I am calling the Elite Reference Time [ERT].Why the top 5 finishers? Well just looking at the winning time would subject the ERT to large fluctuations based on the quality of the winner. Taking an average over more athletes statistically yields a more stable result. So why not the first 10 or 20 finishers? Well at some point if we go too deep then the strength in depth of the Male Pro field will end up being judged rather than the race itself. Somewhere between these numbers there lies a compromise and I have chosen five as the number. A future opportunity for study would be to see how the analysis changes based on that choice.

Another important point to make about the ERT is that it is specific to each race and not each event. What I mean here is that Ironman UK is the event and Ironman UK 2006 is the race. Because of a bike course change the ERT varied significantly between IMUK 2005 and IMUK 2006.

 

I have analysed all the course data available to me going back as far as 2002. I have had to make one or two judgement calls along the way and Iíll explain them here so that you understand what has been included and omitted.

1.       Shortened races (NZ 2006, Malaysia 2005, Korea 2006 etc) have not been included

2.       For events with a complete change of venue and management like Ironman France, only data from Nice 2005 and 2006 is included. Similarly Germany only includes the Frankfurt event and not Roth

3.       The reference times of Coeur DíAlene and Lake Placid have only been included when the menís professionals have competed. For the gap years the ERTs from the surrounding years were used.

 

What we then have is the reference table Table 1. (right) which shows the ERTs for each race for each year. I have calculated an average ERT for the event but for the reasons stated earlier, please treat this average with extreme caution. Also note that I have assigned the races by the qualification season. So the Florida, Wisconsin and Western Australia 2007 races were actually raced in the 2006 calendar year, but qualified for the 2007 Hawaii event. Just in case any of you thought I had some clairvoyant skills.

 

Now there is a huge assumption here that most of you will have noticed already. We are assuming that the strength of the menís field is the same in each race. Obviously the strength of the menís field will vary with the following factors.

1.       Prize Money

2.       Pro Slots Available

3.       Travel And Expense to get to the location. Note now the value of my Grand Prix table to determine in which geographical areas the strength of the field lies.

4.       Proximity in the calendar to Hawaii. Unlikely that Normann and Faris are ever going to be competing in Wisconsin and Florida is it?

5.       Course type. There are ďgrimpeursĒ and ďrouleursĒ and most of the really top pros are not climbers since only 3-4 courses really provide a significant elevation to be considered. So these could be argued as specialist courses. Iím not for a moment saying that Herve Faure, Marcel Zamora, Gilles Reboul are not top quality triathletes. They absolutely are, as Tim Deboom found out in 2005, however I would suggest that their prize was the ďmaillot a poisĒ rather than the ďmaillot jauneĒ.

6.       Course history, conditions and organisation. Will the weather conditions in the courses that were shortened and nearly postponed in recent years weaken the field?

 

However that being said, the data show a good level of consistency year over year for the same events and the results do bear out the levels of difficulties of each course as anecdotal reports have indicated over the years. I would therefore advance that this table serves us well in determining a valid reference time for each race for each year.

 

HAMMOND QUALIFICATION COEFFICIENT [HQC]

M40 AG

 

 

 

 

 

 

 

HQC

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Grand Total

Lanzarote

25.4%

 

20.6%

21.4%

19.2%

 

21.7%

France

 

 

 

22.5%

20.3%

 

21.4%

South Africa

 

 

 

19.0%

16.9%

27.4%

21.1%

Lake Placid

20.1%

25.1%

21.0%

20.4%

18.8%

 

21.1%

Malaysia

 

 

 

 

23.4%

18.5%

20.9%

Arizona

 

 

 

19.6%

22.1%

20.6%

20.8%

Canada

 

18.6%

23.0%

23.6%

17.8%

 

20.8%

Brazil

 

25.8%

21.1%

15.2%

20.0%

 

20.5%

New Zealand

19.7%

20.1%

23.0%

21.2%

 

16.5%

20.1%

Korea

20.5%

19.3%

 

20.1%

 

 

20.0%

Wisconsin

 

18.9%

21.0%

18.1%

22.9%

13.8%

18.9%

Austria

 

17.4%

23.6%

14.3%

19.6%

 

18.7%

Australia

 

 

 

18.2%

19.2%

 

18.7%

Japan

 

18.0%

20.5%

16.2%

19.4%

 

18.5%

Germany

 

 

 

17.3%

19.4%

 

18.4%

Coeur D'alene

 

16.8%

15.1%

18.0%

23.4%

 

18.3%

United Kingdom

 

 

 

19.4%

16.3%

 

17.9%

Switzerland

19.9%

8.1%

18.1%

20.4%

16.1%

 

16.5%

Florida

17.7%

17.9%

13.5%

13.4%

14.8%

14.4%

15.3%

Western Australia

 

 

 

13.1%

23.2%

6.0%

14.1%

Grand Total

20.6%

18.7%

20.0%

18.5%

19.6%

16.7%

19.0%

 

Now that we have established this the next step is simply to determine the time of the last qualifier in each age group for each race to determine the degree of difficulty for qualification.Letís calculate this as follows. In IM France 2006 the time recorded by the last qualifier in the M40-44 age group was 10h33m42s by a M. Olivier Bianchi. This was 20.3% more time that the reference time for this event 8h46m42s.

 

I call this the number (20.3%) the Qualification Coefficient. Actually I take that back. Iím now going to call this the Hammond Qualification Coefficient [HQC] and since youíre all getting this for free you can jolly well call it that too. Canít you?

 

So all you need to know in fact is which race gives you the highest HQC. i.e. which race allows you to run the slowest relative to the elite reference time and still qualify for Hawaii. Notice now that we have not even considered how many slots were available in the race, how many were allocated to each group, how many rolled down etc.

 

For my age group I was then able to create the table showing the HQC for each race each year (Table 2)

 

I am desperately trying to figure out how to publish my database in an interactive format so that you simply have to click your AG to get Table 2 for your own AG. However Iím still struggling with the technology for the moment. In the interim, please click on the following link to get the HRQ Table for your own AG

M18

M25

M30

M35

M40

M45

 

 

THE ROLL DOWN FACTOR

Slot Acceptance Rate

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Grand Total

Malaysia

 

 

 

 

94.3%

94.0%

94.2%

Florida

95.4%

84.7%

90.4%

83.9%

91.1%

91.7%

89.4%

Korea

81.8%

92.0%

 

81.3%

 

 

85.0%

Wisconsin

 

87.8%

84.2%

91.8%

72.0%

89.0%

85.0%

Western Australia

 

 

 

81.9%

78.6%

86.1%

82.2%

Arizona

 

 

 

72.3%

79.3%

94.9%

82.2%

Japan

 

77.2%

76.1%

94.3%

80.6%

 

82.1%

South Africa

 

 

 

88.1%

77.1%

64.4%

76.6%

Lanzarote

61.4%

 

73.4%

85.6%

79.3%

 

74.9%

Coeur D'alene

 

74.4%

74.2%

77.5%

67.6%

 

73.6%

France

 

 

 

67.2%

76.6%

 

71.9%

Germany

 

 

 

70.3%

73.0%

 

71.6%

New Zealand

58.4%

76.3%

67.2%

64.9%

 

77.1%

68.8%

Brazil

 

54.3%

57.2%

82.4%

81.1%

 

68.8%

United Kingdom

 

 

 

56.5%

79.6%

 

68.0%

Lake Placid

61.9%

58.5%

70.5%

62.3%

67.4%

 

64.2%

Australia

 

 

 

67.4%

59.9%

 

63.7%

Switzerland

69.0%

29.5%

73.6%

66.8%

68.9%

 

61.4%

Canada

 

60.9%

56.7%

61.8%

63.7%

 

60.8%

Austria

 

59.6%

52.4%

60.0%

61.9%

 

58.5%

Grand Total

70.8%

68.6%

70.5%

74.6%

75.2%

85.3%

74.0%

Although I think the pure analysis does not really require it, I will address the roll down factor as the question is frequently asked.

Evidently not everyone who earns a qualification slot actually wants to go to Hawaii and thus the slots roll down. The roll down factor varies by year, by event and by Age Group. The more the slots roll down, the higher the HQC obviously. I have seen some wild roll downs in my short IM experience and typically they occur in the upper age groups and the womenís categories. Including those wild data events in my database would basically skew my overall averages significantly. So for that reason I have chosen to restrict my analysis to the M18, M25, M30, M35, M40 and M45 age groups. I sincerely apologise for appearing to be ageist and sexist in this most inclusive of sports, however I feel that not only would including the other categories skew some of the overall data, but the lower slots and participation in those categories would yield unreliable results.

 

Here are some interesting facts about the rolls downs.

1.       Globally the acceptance rate of earned Hawaii Slots has changed as follows over recent years

a.       2003 56%

b.      2004 63%

c.       2005 68%

d.      2006 66%

2.       Florida has the highest pick up rate at 94% and Austria is the lowest at 36%

3.       North America has the highest slot acceptance rate although it did actually decrease in 2006. The acceptance rate in Europe has risen dramatically over the last few years and if the trend continues will surpass NAMís in 2007

Slot Acceptance Rate

Season

 

 

 

 

Area

2003

2004

2005

2006

Grand Total

NAM

68%

69%

79%

72%

73%

AFR

 

 

100%

40%

70%

ASA

67%

68%

61%

61%

63%

EUR

20%

50%

61%

70%

58%

LAM

50%

60%

57%

56%

56%

Grand Total

56%

63%

68%

66%

65%

 

 

 

 

 

So please note that whilst Austria has an extremely low acceptance rate of the Hawaii slots the qualification performance requirement was about average. This is why the number of slots and the pick up rate is really only an interesting aside to the true determinant which is the HRQ.

 

TABLE 3

Event

City

Inaguration Year

Total

Std Dev

Germany

Frankfurt

2002

120

1.26%

Coeur D'alene

Coeur d'alene

2003

80

2.83%

New Zealand

Taupo

1985

80

1.35%

Arizona

Tempe

2005

80

1.46%

Wisconsin

Maddison

2002

80

1.79%

Canada

Penticton

1983

80

2.68%

Lake Placid

Lake Placid

1999

80

2.42%

Florida

Panama City

1999

80

0.59%

Switzerland

Zurich

2002

75

5.00%

Australia

Port Macquarie

1985

70

0.59%

Lanzarote

Lanzarote

1992

60

2.45%

France

Nice

2005

50

1.27%

Japan

Goto

2001

50

1.81%

Brazil

Florianopolis Island

2001

50

4.38%

Austria

Klagenfurt

1999

50

3.90%

Korea

Seogwipo

2001

50

0.56%

Malaysia

Langkawi

2001

35

0.00%

South Africa

Port Elizabeth

2005

30

1.22%

United Kingdom

Sherborne

2005

30

1.79%

Western Australia

Busseltown

2004

30

5.84%

Your Race Selection Methodology

 

Now that we have the mechanism in place, please realise that this is just a tool and apply some common sense in using it. Also remember to apply the other factors that will weigh into the equation.

 

First of all I would treat this like I would if I were evaluating an investment. Remember that phrase ďpast performance is no guarantee of future resultsĒ. Well that is indeed true, but for some investments it is truer that others. This is no different. The key word is volatility. If this chart is going to play a large roll in my quest for Kona, then Iím going to study the history very closely. So whilst top of the pile with the highest HQC is Malaysia, guess what, I only have 1 yearís worth of data. So just how reliable is that? How long has the manager of that mutual fund been at the helm?

 

In the same vein another question is ďhow long has the race been in going on?Ē UK has only run for 2 years and in its inaugural year the HQC was 19.4% but dropped to 16.3% in its second year.

 

Ultimately a large number of slots available is a good thing, but not for the obvious reason. The reason that it is a good thing is that it will provide more consistency in the roll down factor and therefore allow a more solid projection of the next yearís required qualifying time. With 2 slots available at South Africa, you never know whether they will roll down to the 5th place (2005) or if first 2 guys are going to grab it (2006). That roll down lowered the required performance by an effective 11 minutes.

 

Mathematically a good way to look at the volatility is to measure the Standard Deviation of the data, the lower the Standard deviation, the greater chance that future results will indeed reflect past performance. As an added tool the Table 3 shows the three factors to consider along with the HQC to validate your choice, the inauguration year, the Total slots available and the Std Deviation (for the M40-44Age group only)

 

My advice to your overall approach would be as follows.

1.       Determine the order of events by HQC for your Age Group

2.       Eliminate the events that fail to meet the required your required statistical certainly standards

3.       Eliminate the events that do not meet your other constraints in terms of course type, calendar placement, cost, travel and registration availability.

4.       From what is left, the event with the highest HQC should be your choice.

 

For the 2007 season I selected France as my A race. I eliminated Malaysia due to the variable weather conditions and lack of data and the next choice was between Lanzarotte and Nice with very similar HRQs. Well Nice is a little closer to home and Iíve also done the course twice already.

I added South Africa as an early season test of the winter training base. I was waiting to try China but the race didnít get the go ahead and my first fall back plan Arizona (with a good HRQ) closed a few days before we heard the news about China. I then added Louisville as a fall back option if something goes wrong in Nice.

 

I sincerely hope that this helps you make your best choice in your personal journey to Kona. Good Luck and Hope to see you some day on the Big Island.

FORTHCOMING ENHANCEMENTS TO THIS ANALYSIS

I am actively working on the following items to enhance this analysis

1.       Obtain more historical data from 2002-2004

2.       Include data from 70.3 Events with Hawaii Qualifying slots

3.       Conduct Kona performance versus qualifying race performances to validate Elite Reference Times

4.       Add HQC tables for guaranteed qualification place. (i.e. if there were 5 slots available, what was the HQC for the time of the 5th place person)

5.       Add complete analysis for 70.3 Florida World Championship qualification

 

AGE GROUP HQC TABLES

 

M18 HQC

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Average

Arizona

 

 

 

25.5%

24.8%

22.0%

24.1%

Canada

 

26.0%

20.8%

21.9%

13.2%

 

20.5%

Lake Placid

21.7%

25.6%

11.7%

22.9%

18.9%

 

20.2%

France

 

 

 

21.4%

17.5%

 

19.5%

Malaysia

 

 

 

 

24.9%

12.7%

18.8%

South Africa

 

 

 

21.8%

14.6%

17.0%

17.8%

Coeur D'alene

 

19.2%

13.7%

16.3%

20.7%

 

17.5%

New Zealand

21.1%

16.4%

13.8%

13.0%

 

22.2%

17.3%

Japan

 

15.7%

18.5%

17.2%

15.1%

 

16.6%

Korea

33.2%

7.3%

 

7.8%

 

 

16.1%

Wisconsin

 

14.7%

16.3%

15.8%

23.2%

9.8%

16.0%

Florida

21.1%

18.5%

10.1%

20.7%

14.1%

7.5%

15.3%

Germany

 

 

 

11.0%

18.2%

 

14.6%

Brazil

 

13.1%

13.3%

12.5%

13.4%

 

13.1%

Australia

 

 

 

12.6%

12.8%

 

12.7%

Western Australia

 

 

 

10.2%

9.7%

15.1%

11.7%

Switzerland

 

11.6%

6.8%

12.7%

12.6%

 

10.9%

Austria

 

11.5%

9.4%

11.4%

10.7%

 

10.7%

Lanzarote

13.7%

 

11.1%

10.7%

4.9%

 

10.1%

United Kingdom

 

 

 

8.2%

11.9%

 

10.1%

Grand Total

22.2%

16.3%

13.2%

15.4%

15.6%

15.2%

15.7%

M25 HQC

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Average

Austria

 

8.5%

48.1%

9.9%

15.0%

 

20.4%

Arizona

 

 

 

13.5%

21.7%

16.6%

17.3%

Canada

 

15.6%

18.9%

21.5%

11.9%

 

17.0%

Korea

21.3%

13.8%

 

14.3%

 

 

16.5%

South Africa

 

 

 

21.0%

15.0%

13.3%

16.4%

Lake Placid

16.4%

16.2%

14.5%

18.8%

14.0%

 

16.0%

Brazil

 

21.1%

15.7%

11.5%

14.4%

 

15.6%

Wisconsin

 

14.4%

13.2%

15.0%

21.9%

9.8%

14.9%

New Zealand

13.7%

11.9%

13.2%

17.2%

 

15.3%

14.2%

Coeur D'alene

 

15.8%

13.8%

13.2%

14.1%

 

14.2%

Japan

 

14.3%

19.4%

10.2%

11.4%

 

13.8%

France

 

 

 

13.6%

13.1%

 

13.4%

Lanzarote

13.4%

 

18.6%

9.2%

11.7%

 

13.2%

Switzerland

16.7%

11.4%

12.5%

12.4%

10.5%

 

12.7%

Florida

14.2%

13.9%

10.5%

13.4%

8.0%

12.1%

12.0%

Germany

 

 

 

12.2%

11.4%

 

11.8%

Malaysia

 

 

 

 

15.7%

7.1%

11.4%

Australia

 

 

 

9.6%

12.5%

 

11.0%

United Kingdom

 

 

 

11.9%

9.7%

 

10.8%

Western Australia

 

 

 

6.7%

12.0%

7.5%

8.8%

Grand Total

15.9%

14.3%

18.0%

13.4%

13.6%

11.7%

14.3%

M30 HQC

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Average

Brazil

 

19.4%

22.0%

15.0%

21.6%

 

19.5%

Arizona

 

 

 

13.7%

19.3%

17.1%

16.7%

Lanzarote

18.9%

 

11.3%

18.5%

16.0%

 

16.2%

Canada

 

14.2%

20.2%

16.2%

14.1%

 

16.2%

Lake Placid

15.9%

15.9%

16.7%

16.3%

15.8%

 

16.1%

New Zealand

16.8%

15.0%

14.9%

14.9%

 

16.4%

15.6%

Germany

 

 

 

13.0%

18.1%

 

15.5%

Malaysia

 

 

 

 

17.8%

12.6%

15.2%

Coeur D'alene

 

18.0%

11.8%

16.0%

14.2%

 

15.0%

Switzerland

20.0%

14.7%

14.0%

12.6%

12.3%

 

14.7%

South Africa

 

 

 

17.6%

11.4%

14.9%

14.6%

Wisconsin

 

13.0%

13.5%

14.3%

18.9%

10.5%

14.0%

United Kingdom

 

 

 

17.9%

8.0%

 

13.0%

Korea

15.4%

12.5%

 

10.7%

 

 

12.9%

Florida

15.3%

15.1%

12.1%

11.6%

10.0%

12.9%

12.8%

Japan

 

11.8%

12.9%

10.9%

15.5%

 

12.8%

France

 

 

 

12.6%

12.1%

 

12.3%

Western Australia

 

 

 

10.9%

13.3%

12.0%

12.1%

Austria

 

8.9%

15.6%

10.7%

12.5%

 

11.9%

Australia

 

 

 

11.3%

11.4%

 

11.4%

Grand Total

17.0%

14.4%

15.0%

13.9%

14.6%

13.8%

14.6%

M35 HQC

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Grand Total

Lanzarote

17.7%

 

16.5%

23.1%

16.8%

 

18.5%

Lake Placid

16.3%

24.6%

18.7%

16.3%

15.5%

 

18.3%

Arizona

 

 

 

16.2%

20.4%

16.7%

17.7%

New Zealand

16.6%

18.7%

17.9%

17.4%

 

17.8%

17.7%

Malaysia

 

 

 

 

16.2%

18.5%

17.3%

Canada

 

14.5%

19.7%

19.2%

15.9%

 

17.3%

Brazil

 

19.4%

17.4%

14.7%

16.9%

 

17.1%

Coeur D'alene

 

15.7%

16.2%

17.3%

16.9%

 

16.5%

Wisconsin

 

14.1%

20.1%

16.5%

20.5%

10.6%

16.4%

Germany

 

 

 

15.4%

17.4%

 

16.4%

Korea

16.1%

15.4%

 

16.9%

 

 

16.1%

Switzerland

18.6%

13.2%

18.0%

15.3%

14.6%

 

15.9%

South Africa

 

 

 

18.7%

13.9%

15.2%

15.9%

France

 

 

 

16.3%

15.1%

 

15.7%

Japan

 

19.7%

17.3%

12.8%

10.7%

 

15.1%

United Kingdom

 

 

 

16.4%

12.9%

 

14.7%

Australia

 

 

 

13.8%

15.5%

 

14.6%

Austria

 

13.7%

17.1%

13.3%

14.4%

 

14.6%

Florida

15.8%

15.4%

13.9%

12.7%

12.7%

14.0%

14.1%

Western Australia

 

 

 

7.9%

16.3%

14.3%

12.8%

Grand Total

16.8%

16.8%

17.5%

15.8%

15.7%

15.3%

16.2%

M40 HQC

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Average

Lanzarote

25.4%

 

20.6%

21.4%

19.2%

 

21.7%

France

 

 

 

22.5%

20.3%

 

21.4%

South Africa

 

 

 

19.0%

16.9%

27.4%

21.1%

Lake Placid

20.1%

25.1%

21.0%

20.4%

18.8%

 

21.1%

Malaysia

 

 

 

 

23.4%

18.5%

20.9%

Arizona

 

 

 

19.6%

22.1%

20.6%

20.8%

Canada

 

18.6%

23.0%

23.6%

17.8%

 

20.8%

Brazil

 

25.8%

21.1%

15.2%

20.0%

 

20.5%

New Zealand

19.7%

20.1%

23.0%

21.2%

 

16.5%

20.1%

Korea

20.5%

19.3%

 

20.1%

 

 

20.0%

Wisconsin

 

18.9%

21.0%

18.1%

22.9%

13.8%

18.9%

Austria

 

17.4%

23.6%

14.3%

19.6%

 

18.7%

Australia

 

 

 

18.2%

19.2%

 

18.7%

Japan

 

18.0%

20.5%

16.2%

19.4%

 

18.5%

Germany

 

 

 

17.3%

19.4%

 

18.4%

Coeur D'alene

 

16.8%

15.1%

18.0%

23.4%

 

18.3%

United Kingdom

 

 

 

19.4%

16.3%

 

17.9%

Switzerland

19.9%

8.1%

18.1%

20.4%

16.1%

 

16.5%

Florida

17.7%

17.9%

13.5%

13.4%

14.8%

14.4%

15.3%

Western Australia

 

 

 

13.1%

23.2%

6.0%

14.1%

Grand Total

20.6%

18.7%

20.0%

18.5%

19.6%

16.7%

19.0%

M45 HQC

Season

 

 

 

 

 

 

Event

2002

2003

2004

2005

2006

2007

Average

France

 

 

 

40.6%

23.0%

 

31.8%

New Zealand

25.3%

31.5%

22.4%

25.5%

 

22.6%

25.5%

Arizona

 

 

 

23.8%

27.4%

24.8%

25.3%

Malaysia

 

 

 

 

26.7%

22.8%

24.7%

Canada

 

20.3%

26.0%

32.2%

20.4%

 

24.7%

Lanzarote

30.1%

 

19.2%

24.0%

24.7%

 

24.5%

Korea

25.6%

21.2%

 

25.4%

 

 

24.1%

Germany

 

 

 

18.3%

29.0%

 

23.7%

Japan

 

20.6%

25.4%

22.0%

24.7%

 

23.2%

Lake Placid

22.9%

26.9%

23.3%

21.3%

20.7%

 

23.0%

Brazil

 

23.9%

26.7%

19.0%

21.1%

 

22.7%

Coeur D'alene

 

22.4%

18.8%

24.6%

19.8%

 

21.4%

Switzerland

19.4%

23.1%

19.5%

16.6%

24.4%

 

20.6%

United Kingdom

 

 

 

23.3%

17.6%

 

20.5%

Wisconsin

 

16.6%

23.6%

18.5%

24.9%

18.0%

20.3%

Australia

 

 

 

19.7%

20.7%

 

20.2%

South Africa

 

 

 

20.0%

17.8%

20.2%

19.3%

Florida

19.9%

22.0%

18.0%

17.1%

15.5%

21.2%

19.0%

Austria

 

16.9%

14.1%

20.0%

17.6%

 

17.2%

Western Australia

 

 

 

19.5%

18.3%

12.9%

16.9%

Grand Total

23.9%

22.3%

21.6%

22.7%

21.9%

20.3%

22.1%

Any commentscorrections and critique of this analysis will be warmly received and considered for improvement. Please send to neil@neilhammond,com