28 April 2019
For a while the stats showed an uncanny
fit to losing an average of 1.5 runners a year. Recently you’ve
been beating the odds and we only lost one this year (Dale,
sorry this eventually had to end).
So we have 4 more EPs than we might have
expected statistically. I’m sure you will all want to complete
the 40th if at all possible
Rainer
|
Year |
|
Ever-present |
|
1.5 times |
|
Expected |
|
Discrepancy |
| |
|
Number |
|
no. years |
|
at 1.5 loss |
|
Actual less |
| |
|
of finishers |
|
|
|
per year |
|
Expected |
| |
|
|
|
|
|
|
|
|
|
1995 |
|
42 |
|
0 |
|
42 |
|
0 |
|
1996 |
|
42 |
|
1.5 |
|
40.5 |
|
1.5 |
|
1997 |
|
41 |
|
3 |
|
39 |
|
2 |
|
1998 |
|
41 |
|
4.5 |
|
37.5 |
|
3.5 |
|
1999 |
|
40 |
|
6 |
|
36 |
|
4 |
|
2000 |
|
39 |
|
7.5 |
|
34.5 |
|
4.5 |
|
2001 |
|
36 |
|
9 |
|
33 |
|
3 |
|
2002 |
|
35 |
|
10.5 |
|
31.5 |
|
3.5 |
|
2003 |
|
29 |
|
12 |
|
30 |
|
-1 |
|
2004 |
|
29 |
|
13.5 |
|
28.5 |
|
0.5 |
|
2005 |
|
28 |
|
15 |
|
27 |
|
1 |
|
2006 |
|
25 |
|
16.5 |
|
25.5 |
|
-0.5 |
|
2007 |
|
24 |
|
18 |
|
24 |
|
0 |
|
2008 |
|
22 |
|
19.5 |
|
22.5 |
|
-0.5 |
|
2009 |
|
21 |
|
21 |
|
21 |
|
0 |
|
2010 |
|
20 |
|
22.5 |
|
19.5 |
|
0.5 |
|
2011 |
|
18 |
|
24 |
|
18 |
|
0 |
|
2012 |
|
16 |
|
25.5 |
|
16.5 |
|
-0.5 |
|
2013 |
|
15 |
|
27 |
|
15 |
|
0 |
|
2014 |
|
14 |
|
28.5 |
|
13.5 |
|
0.5 |
|
2015 |
|
12 |
|
30 |
|
12 |
|
0 |
|
2016 |
|
12 |
|
31.5 |
|
10.5 |
|
1.5 |
|
2017 |
|
11 |
|
33 |
|
9 |
|
2 |
|
2018 |
|
11 |
|
34.5 |
|
7.5 |
|
3.5 |
|
2019 |
|
10 |
|
36 |
|
6 |
|
4 |
22 April 2018
After tracking our 1.5 a year average loss for so long, the last
4 years, losing only 1 EP, have blown that correlation out of
the window. As expected perhaps as the sample gets smaller.
We now know we will lose at least 1 by this time next year, I’ll
be delighted if that is the only loss even though my record as a
forecasting statistician will take a beating!
23 April 2017
I attach my stats showing actual v expected numbers of
finishers. With only 1 loss this year and none last year we are
beating the odds. It would take losing 3 next year to bring the
average back to the longer term trend. Heres hoping for
continual defiance of the odds!
25 April 2016
I’ve updated my little table from last year. Because we had all
12 finishing this year, this is the first year since 2003 that
the discrepancy between expected (given an average of 1.5 a year
dropping out) and actual is greater than the minimum of 0.5
people (in odd years only)! I wonder if we will back “on track”
this time next year?
28 April 2015
I noticed several years ago that our numbers started tracking
the number of years since we were formed as a group of 42 very
precisely with an annual average loss of 1.5 runners per year.
Struck with the perfect match this year I’ve filled an idle
moment by producing the attached spread sheet showing how the
actual numbers compare with the postulated algorithm of 1.5 a
year.
We lost a bit below average for the first few years but made up
for it by losing 6 in 2003. Since then the tracking has been
uncannily close with the discrepancy never more than 1 person
and for the last 10 years either at 0 or +/- 0.5 which is a
close as you can get given that runners come in whole units!
We all know that extrapolation is not a cast iron accurate guide
to the future but this suggests that the last runner has another
8 years and Chris may not reach his target of 50. However Chris
is notably younger than the rest of us so I actually think his
chances are a good deal better than the algorithm suggests.
Best of luck to the survivors in their quest to beat the
algorithm!
Regards
Rainer
