CQ WPX SSB and CW logs for 2023 have been added to this repository of public CQ WPX logs.
CQ WPX SSB and CW logs for 2023 have been added to this repository of public CQ WPX logs.
Using the public logs, it is rather easy to generate unofficial station-by-station reports for the entrants in the ARRL DX contests.
The ARRL generates official reports and generally makes these reports available individually to each entrant. But these are not made public. The unofficial reports, while not necessarily identical to the official ones, may therefore hold some interest.
The
unofficial reports may differ from the official ones because the
contest committee has access to checklogs, which are not made public.
Also, there are various pathological occurrences in logs that require a
decision to be made as to how to classify one or more QSOs; the rules by
which such decisions are made are not public, so the decisions that I
made when constructing the unofficial reports may well be different from
those made by the ARRL. Nevertheless, pathological logs
(or pathological QSOs within a log) are relatively rare, so these
decisions should affect a relatively small percentage of logs and QSOs.
(Typical examples [there are many more] of circumstances in which
decisions must made be are: by how much may clocks be skewed and a QSO
still be considered valid? what to do if the transmitted callsign
changes for some number of QSOs in the contest? what do to if more than
one entrant claims to have used the same transmitted callsign?)
The complete set of unofficial reports for the CW and SSB versions of the ARRL DX contest for the years 2018 to 2023 may be found in appropriately named files in this directory.
I
note that despite explicitly informing me in 2017 that they would do so, the ARRL have never made public the logs that they hold for the
ARRL DX contests for years prior to 2018.
One note regarding interpretation of the information in these unofficial reports: all the fields should be self-explanatory, except that in the listing for EXCHANGE BUSTS, some values are enclosed in parentheses: this indicates that the worked station did not submit a log, and the value of the exchange sent by that station was deduced from QSO: lines in the logs of other entrants.
For example, the report for HL2ZN in the 2021
ARRL DX CW contest contains the line (the line below may be wrapped on
your display):
QSO: 14000 CW 2021-02-21 2245 HL2ZN 599 0500 N7DR 599 KY [ (CO) ]
This indicates that we can deduce that HL2ZN probably bust N7DR's exchange, even though N7DR did not send in a log: HL2ZN recorded N7DR's state as KY, even though N7DR probably sent CO (indeed, I did send CO).
The raw logs for the ARRL DX CW and SSB contests for 2023 have been added to this directory.
Logs for the Worked All Germany contest from 2017 to 2022 are now available in this repository of public WAG logs.
First three items are from upgrade of my shack computer.
Item #4 is from upgrade of my main desktop computer.
Item #5 is from my home server.
Item #6 occurred on both the main desktop computer and the home server.
Following an error-free upgrade from debian bullseye to bookworm, I encountered the following problems:
Solution: I installed the package fonts-dejavu.
Solution: Explicitly export TERM=256-color in the ~/.bashrc file.
Comment: This looks like a bug; setting termName in the resources file has always worked in the past.
Solution: Add the line:
kernel.core_pattern = core
to /etc/sysctl.conf.
Comment: I have been using versions of UNIX since the late 1980s. Every single version until debian bookworm would automatically dump core to the current working directory. This seems to be Yet One More example of the madness of systemd taking everything over. Why debian would change the default behaviour of something on which so many people rely seems ridiculous. But then, so did their decision to support systemd.
The autotrash website says that the script can be installed with:
pip install --user autotrash
However, that produces:
[ZB:bin] pip install --user autotrash
error: externally-managed-environment
× This environment is externally managed
╰─> To install Python packages system-wide, try apt install
python3-xyz, where xyz is the package you are trying to
install.
If you wish to install a non-Debian-packaged Python package,
create a virtual environment using python3 -m venv path/to/venv.
Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make
sure you have python3-full installed.
If you wish to install a non-Debian packaged Python application,
it may be easiest to use pipx install xyz, which will manage a
virtual environment for you. Make sure you have pipx installed.
See /usr/share/doc/python3.11/README.venv for more information.
note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
hint: See PEP 668 for the detailed specification.
[ZB:bin]
Solution:
Install the python3-full package. Then execute:
[ZB:~] python3 -m venv ~/.venvs/autotrash
[ZB:~] ~/.venvs/autotrash/bin/python -m pip install autotrash
Collecting autotrash
Downloading autotrash-0.4.5-py3-none-any.whl (22 kB)
Installing collected packages: autotrash
Successfully installed autotrash-0.4.5
[ZB:~]
Now autotrash can be run as:
~/.venvs/autotrash/bin/autotrash
This computer uses two ethernet ports: one to my ISP and hence to the Internet; one to my home LAN. On completing the upgrade (without error) and rebooting the machine, neither network was functioning.
The networking was originally configured as part of the process of installing stretch on this machine, probably about six years ago; networking has worked flawlessly since then, until this upgrade.
Solution:
The directory /etc/NetworkManager/system-connections directory contains two files, rather oddly called:
The contents of these files are:
Wired connection enp11s0(eth0).nmconnection:
[connection]
id=Wired connection enp11s0(eth0)
uuid=8e308949-5232-47aa-b9b6-8aab6369ec4d
type=ethernet
permissions=
[ethernet]
mac-address-blacklist=
[ipv4]
address1=209.97.232.18/24,209.97.232.1
dns=127.0.0.1;209.97.224.2;209.97.224.3;
dns-search=
method=manual
[ipv6]
addr-gen-mode=stable-privacy
dns-search=
method=auto
[proxy]
Wired connection enp12s0(eth1):
[connection]
id=Wired connection enp12s0(eth1)
uuid=251dd901-f8b7-42ee-b568-b15ba565a81b
type=ethernet
permissions=
[ethernet]
mac-address=D8:50:E6:C2:76:03
mac-address-blacklist=
[ipv4]
address1=192.168.0.1/24
dns-search=
method=manual
[ipv6]
addr-gen-mode=stable-privacy
dns-search=
method=auto
The fix is to add a MAC address to the first file.
I note that it is odd that this is necessary: as enp12s0 is mapped directly to a particular port by the MAC address, Network Manager should know that enp11s0 should therefore be mapped to the other port. It has worked that way on this machine since stretch, but apparently this behaviour has changed in bookworm.
It took quite a while to figure this out; more details of the flailing around can be found in the threads that start at:
https://lists.debian.org/debian-user/2023/09/msg00024.html and
https://lists.debian.org/debian-user/2023/09/msg00061.html.
There is also an official response to the issue at:
https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1051086,
which I note is remarkably unhelpful (if only because it suggests use of a utility that is not part of debian stable; but it also suggests that the problem is due to kernel timing, which is hard to believe given the discussion in the threads on lists.debian.org -- can a problem that depends on timing of the order of many seconds really be due to a change in kernel timing? -- also, the suggested fix seems less clean than the one I provide above; and, in any case, if a human can figure out which connection goes with which port, Network Manager should have been able to do the same. And Network Manager should in no circumstance have tried to assign two connections to each other, as is described in the first lists.debian.org post; the worst that should have happened is that the connection without a MAC address should have failed, and a useful error message provided).
When trying to connect to remote systems over ssh, various error messages would be received. This is a typical such message:
Unable to negotiate with 77.109.148.18 port 22: no matching host key type found. Their offer: ssh-dss,ssh-ed25519
The messages all suggested that ssh was unable to find a common acceptable key type.
It seems that the default types of keys that are deemed acceptable must have changed in bookworm. The easiest fix is simply to restore the old keys types as being acceptable, by adding the following lines to ~/.ssh/config:
PubkeyAcceptedKeyTypes +ssh-rsa
PubkeyAcceptedKeyTypes +ssh-dss
HostKeyAlgorithms +ssh-rsa
HostkeyAlgorithms +ssh-dss
The basic notion of reverse NILs (rNILs; or, I suppose, RNILs) is described here, along with a description of a simple script for calculating rNILs for CQ WW contests
and the result of applying that code to the contests for 2005. See also
the comments at the end of that post. I would be delighted if anyone
who spots any errors in the script would inform me.
We
can also look at the results for periods of ten years at a time; the
only difference in the way that these decadal tables are
calculated is that the minimum number of rQSOs is raised from 50 to 250
for tables pertaining to all QSOs and from 25 to 125 for those
pertaining to intra-W QSOs. (That is, the value of the variable MIN_QSOs is changed from 50 to 250.)
Here are the results for 2022 and for the period from 2013 to 2022. As in prior years, I refrain from comment.
2022 SSB:
Call | Total rQSOs | Total rNILs |
---|---|---|
PY2HT | 1270 | 1079 |
LU9WE | 772 | 559 |
VA3MLV | 487 | 486 |
CN3A | 13955 | 272 |
BY3CQ | 1504 | 267 |
D4Z | 13418 | 227 |
K1LZ | 7785 | 174 |
RT5F | 175 | 174 |
DJ4DN | 289 | 172 |
VP2EIH | 185 | 165 |
Call | Total rQSOs | Total rNILs | % rNILs |
---|---|---|---|
VA3MLV | 487 | 486 | 99.8 |
RT5F | 175 | 174 | 99.4 |
VP2EIH | 185 | 165 | 89.2 |
DJ5AM | 140 | 122 | 87.1 |
VP9NR | 111 | 95 | 85.6 |
PY2HT | 1270 | 1079 | 85.0 |
W1ACB | 56 | 42 | 75.0 |
LU9WE | 772 | 559 | 72.4 |
OE3MDB | 211 | 140 | 66.4 |
PD7LJ | 198 | 128 | 64.6 |
Call | Total rQSOs with Ws | rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws |
---|---|---|---|---|
KV0Q | 88 | 35 | 594 | 9 |
N7DD | 52 | 34 | 664 | 15 |
NY6DX | 62 | 29 | 1536 | 28 |
N2IC | 130 | 24 | 2360 | 30 |
K8LX | 29 | 23 | 1450 | 21 |
K1LZ | 403 | 20 | 7382 | 154 |
K3LR | 903 | 17 | 7735 | 86 |
W7RM | 157 | 17 | 1943 | 20 |
NA6JD | 42 | 15 | 88 | 26 |
KT7E | 397 | 10 | 1394 | 10 |
Call | Total rQSOs with Ws | Total rNILs against Ws | % rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws | % rNILs against non-Ws |
---|---|---|---|---|---|---|
K8LX | 29 | 23 | 79.3 | 1450 | 21 | 1.4 |
N7DD | 52 | 34 | 65.4 | 664 | 15 | 2.3 |
NY6DX | 62 | 29 | 46.8 | 1536 | 28 | 1.8 |
KV0Q | 88 | 35 | 39.8 | 594 | 9 | 1.5 |
NA6JD | 42 | 15 | 35.7 | 88 | 26 | 29.5 |
K5NZ | 32 | 7 | 21.9 | 434 | 6 | 1.4 |
N2IC | 130 | 24 | 18.5 | 2360 | 30 | 1.3 |
AB3CX | 28 | 5 | 17.9 | 2260 | 17 | 0.8 |
W7VJ | 34 | 5 | 14.7 | 663 | 6 | 0.9 |
K8GL | 41 | 5 | 12.2 | 1401 | 19 | 1.4 |
2022 CW:
Call | Total rQSOs | Total rNILs |
---|---|---|
IK3UNA | 1329 | 1048 |
CS2C | 948 | 905 |
F6GOE | 689 | 638 |
DF8AE | 652 | 352 |
CN3A | 14048 | 197 |
HF95PRK | 249 | 178 |
A44A | 8591 | 177 |
CR3DX | 12718 | 165 |
V47T | 7868 | 152 |
EA8RM | 8055 | 151 |
Call | Total rQSOs | Total rNILs | % rNILs |
---|---|---|---|
TG9ADM | 62 | 61 | 98.4 |
CS2C | 948 | 905 | 95.5 |
F6GOE | 689 | 638 | 92.6 |
IK3UNA | 1329 | 1048 | 78.9 |
HF95PRK | 249 | 178 | 71.5 |
HB9IQB | 78 | 49 | 62.8 |
R3QX | 85 | 52 | 61.2 |
DF8AE | 652 | 352 | 54.0 |
VU2IVV | 163 | 74 | 45.4 |
JA1DBG | 58 | 26 | 44.8 |
Call | Total rQSOs with Ws | rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws |
---|---|---|---|---|
K0RF | 280 | 38 | 4134 | 38 |
W5ZN | 70 | 30 | 1473 | 10 |
NN7CW | 172 | 26 | 3213 | 30 |
K8LX | 110 | 26 | 3615 | 30 |
K1ZM | 28 | 24 | 215 | 5 |
KV2K | 43 | 21 | 1003 | 17 |
K1RX | 235 | 15 | 5871 | 50 |
N7DD | 33 | 14 | 877 | 11 |
K5TR | 200 | 12 | 3244 | 44 |
K3LR | 455 | 11 | 8038 | 76 |
Call | Total rQSOs with Ws | Total rNILs against Ws | % rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws | % rNILs against non-Ws |
---|---|---|---|---|---|---|
K1ZM | 28 | 24 | 85.7 | 215 | 5 | 2.3 |
KV2K | 43 | 21 | 48.8 | 1003 | 17 | 1.7 |
W5ZN | 70 | 30 | 42.9 | 1473 | 10 | 0.7 |
N7DD | 33 | 14 | 42.4 | 877 | 11 | 1.3 |
K8LX | 110 | 26 | 23.6 | 3615 | 30 | 0.8 |
W7RM | 52 | 9 | 17.3 | 2641 | 27 | 1.0 |
W4RM | 26 | 4 | 15.4 | 1853 | 27 | 1.5 |
NN7CW | 172 | 26 | 15.1 | 3213 | 30 | 0.9 |
K0RF | 280 | 38 | 13.6 | 4134 | 38 | 0.9 |
W2CG | 46 | 6 | 13.0 | 2962 | 27 | 0.9 |
As I write this, the results for the 2022 contests are yet to be
announced. I fully expect that, as in years past, that none of the people in the final table of each group whose rNIL
rate against Ws exceeds 50% will be disqualified for unsportsmanlike
conduct -- or even be investigated
in order to determine the reason for what appears on its face to be an
excessive rNIL rate against Ws. Year after year, the situation remains the same.
(I do note that rNILs do
occur naturally when one of the two operators is a bit sloppy, and a
rate that is higher against Ws than against non-Ws could [possibly] be
explained as a natural occurrence: for example, the running W operator
hears two callers, one W and one DX, and the running station would
normally go back to and work the DX station if he can, while the W
caller might sloppily believe that he was being worked. What is
concerning, though, and should reasonably be a cause for (at a minimum) further
investigation, is when the rNIL rate against Ws greatly exceeds the rate against non-Ws, or when the same calls appear in the tables year after year.)
2013 to 2022 SSB:
Call | Total rQSOs | Total rNILs |
---|---|---|
EA2DMH | 5864 | 1650 |
CN3A | 81269 | 1559 |
LZ9W | 93036 | 1379 |
PJ2T | 72613 | 1193 |
JE5JHZ | 1603 | 1185 |
A73A | 57153 | 1118 |
PY2HT | 3122 | 1111 |
YL2014W | 1106 | 1099 |
MI0M | 3870 | 1085 |
OT5A | 62321 | 1058 |
Call | Total rQSOs | Total rNILs | % rNILs |
---|---|---|---|
YV4GMG | 328 | 327 | 99.7 |
YL2014W | 1106 | 1099 | 99.4 |
CU4AT | 274 | 270 | 98.5 |
ZZ5Z | 297 | 292 | 98.3 |
KP4ROS | 667 | 653 | 97.9 |
EA8DDS | 503 | 387 | 76.9 |
JE5JHZ | 1603 | 1185 | 73.9 |
LU9WE | 772 | 559 | 72.4 |
CO2SG | 343 | 232 | 67.6 |
OK1KZ | 933 | 599 | 64.2 |
Call | Total rQSOs with Ws | rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws |
---|---|---|---|---|
N7DD | 577 | 378 | 8460 | 161 |
KV0Q | 825 | 374 | 7677 | 116 |
K3LR | 5238 | 107 | 62815 | 758 |
NY6DX | 206 | 98 | 6239 | 101 |
N2IC | 761 | 95 | 12809 | 115 |
N9RV | 728 | 91 | 11705 | 120 |
K5TR | 2982 | 73 | 21465 | 357 |
K3EST | 1494 | 69 | 13071 | 231 |
W3LPL | 2420 | 66 | 46188 | 620 |
KC1XX | 1795 | 45 | 42867 | 622 |
Call | Total rQSOs with Ws | Total rNILs against Ws | % rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws | % rNILs against non-Ws |
---|---|---|---|---|---|---|
N7DD | 577 | 378 | 65.5 | 8460 | 161 | 1.9 |
NY6DX | 206 | 98 | 47.6 | 6239 | 101 | 1.6 |
KV0Q | 825 | 374 | 45.3 | 7677 | 116 | 1.5 |
AB4B | 173 | 23 | 13.3 | 7137 | 98 | 1.4 |
N9RV | 728 | 91 | 12.5 | 11705 | 120 | 1.0 |
N2IC | 761 | 95 | 12.5 | 12809 | 115 | 0.9 |
N3AD | 165 | 20 | 12.1 | 9410 | 148 | 1.6 |
N7TU | 131 | 14 | 10.7 | 1524 | 23 | 1.5 |
W8PR | 248 | 26 | 10.5 | 11862 | 168 | 1.4 |
K3UL | 195 | 19 | 9.7 | 10234 | 182 | 1.8 |
CW 2013 to 2022:
Call | Total rQSOs | Total rNILs |
---|---|---|
PJ2T | 93139 | 1381 |
LZ9W | 106708 | 1376 |
P33W | 81257 | 1140 |
IK3UNA | 12053 | 1135 |
9A1A | 88591 | 1052 |
PJ4A | 63571 | 1040 |
CS2C | 13862 | 1028 |
ZF1A | 51855 | 1027 |
V47T | 56107 | 1016 |
PI4DX | 13591 | 1009 |
Call | Total rQSOs | Total rNILs | % rNILs |
---|---|---|---|
RA9KY | 459 | 458 | 99.8 |
RZ9CJ | 462 | 460 | 99.6 |
OK1KZ | 1226 | 993 | 81.0 |
WB0CFF | 430 | 313 | 72.8 |
CO2IZ | 258 | 178 | 69.0 |
F6GOE | 1123 | 640 | 57.0 |
AB3UM | 276 | 153 | 55.4 |
XF1IM | 702 | 385 | 54.8 |
YS1MS | 433 | 232 | 53.6 |
PP5BLU | 305 | 148 | 48.5 |
Call | Total rQSOs with Ws | rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws |
---|---|---|---|---|
N7DD | 334 | 189 | 7815 | 153 |
K0RF | 2231 | 152 | 33718 | 402 |
NR5M | 1237 | 140 | 15932 | 152 |
KV2K | 396 | 129 | 20213 | 333 |
N9RV | 679 | 80 | 16153 | 171 |
NA3M | 191 | 78 | 11906 | 98 |
WJ9B | 795 | 71 | 12185 | 109 |
W3LPL | 2674 | 69 | 69176 | 601 |
K3LR | 3245 | 69 | 68369 | 596 |
NN7CW | 901 | 67 | 15625 | 175 |
Call | Total rQSOs with Ws | Total rNILs against Ws | % rNILs against Ws | Total rQSOs with non-Ws | rNILs against non-Ws | % rNILs against non-Ws |
---|---|---|---|---|---|---|
N7DD | 334 | 189 | 56.6 | 7815 | 153 | 2.0 |
W1IE | 140 | 62 | 44.3 | 3313 | 136 | 4.1 |
NA3M | 191 | 78 | 40.8 | 11906 | 98 | 0.8 |
KV2K | 396 | 129 | 32.6 | 20213 | 333 | 1.6 |
K8LX | 197 | 54 | 27.4 | 7977 | 84 | 1.1 |
NE3F | 228 | 59 | 25.9 | 14863 | 271 | 1.8 |
KZ5D | 247 | 58 | 23.5 | 10859 | 138 | 1.3 |
W5ZN | 212 | 48 | 22.6 | 4476 | 48 | 1.1 |
KV0Q | 200 | 43 | 21.5 | 1930 | 63 | 3.3 |
W0QQG | 152 | 28 | 18.4 | 1443 | 216 | 15.0 |
Prior posts in this series:
I begin with an ordered list of the stations with the lowest probabilities of busting a call in 2022 CQ WW SSB.
2022 CQ WW SSB -- weighted mean values of $p_{bust}$ (all) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | OK1WCF | 0.0005 | 1,719 | 0 |
2 | M3AWD | 0.0006 | 1,506 | 0 |
3 | PY2KJ | 0.0008 | 1,213 | 0 |
4 | N2BJ | 0.0010 | 964 | 0 |
5 | PY5FO | 0.0010 | 926 | 0 |
6 | G4P | 0.0010 | 909 | 0 |
7 | I2WIJ | 0.0011 | 882 | 0 |
8 | W1ARY | 0.0012 | 772 | 0 |
9 | W6DVS | 0.0013 | 762 | 0 |
10 | IK1PMR | 0.0013 | 741 | 0 |
2022 CQ WW CW -- weighted mean values of $p_{bust}$ (all) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | DL4FN | 0.0004 | 2,040 | 0 |
2 | SN5J | 0.0005 | 1,722 | 0 |
3 | DL6NDW | 0.0006 | 1,572 | 0 |
4 | W3KB | 0.0007 | 1,342 | 0 |
5 | EU8U | 0.0007 | 1,266 | 0 |
6 | N3NR | 0.0009 | 1,087 | 0 |
7 | K1ZZ | 0.0009 | 3,418 | 2 |
8 | SP9XCN | 0.0009 | 2,155 | 1 |
9 | K3PH | 0.0009 | 2,142 | 1 |
10 | M2J | 0.0010 | 992 | 0 |
It is interesting to plot the aggregated probability function for $p_{bust}$ weighted by the verified number of QSOs, $Q_v$, for all stations:
In case it isn't clear, the location of the solid vertical lines represent the weighted means of the probability curves.We can limit the analysis to calling stations (i.e., not the running station).
2022 CQ WW SSB -- weighted mean values of $p_{bust}$ (no-run) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | OK1WCF | 0.0006 | 1,436 | 0 |
2 | M3AWD | 0.0008 | 1,234 | 0 |
3 | 9A2EU | 0.0010 | 955 | 0 |
4 | N5RZ | 0.0010 | 954 | 0 |
5 | N3FJP | 0.0010 | 918 | 0 |
6 | G4P | 0.0011 | 876 | 0 |
7 | N2YO | 0.0012 | 793 | 0 |
8 | I2WIJ | 0.0012 | 791 | 0 |
9 | W1ARY | 0.0013 | 765 | 0 |
10 | W6DVS | 0.0013 | 762 | 0 |
2022 CQ WW CW -- weighted mean values of $p_{bust}$ (no-run) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | DL4FN | 0.0006 | 1,634 | 0 |
2 | SN5J | 0.0006 | 1,598 | 0 |
3 | DK1KC | 0.0007 | 1,428 | 0 |
4 | DJ5MO | 0.0008 | 1,226 | 0 |
5 | DL6NDW | 0.0008 | 1,194 | 0 |
6 | W3KB | 0.0008 | 1,164 | 0 |
7 | IO1T | 0.0008 | 1,125 | 0 |
8 | K3PH | 0.0009 | 1,082 | 0 |
9 | N2RC | 0.0009 | 1,076 | 0 |
10 | EA2ESB | 0.0009 | 1,053 | 0 |
And similarly for running stations.
2022 CQ WW SSB -- weighted mean values of $p_{bust}$ (run) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | PY2KJ | 0.0009 | 1,074 | 0 |
2 | OH0V | 0.0011 | 884 | 0 |
3 | VC3R | 0.0013 | 1,499 | 1 |
4 | 5Q2J | 0.0014 | 674 | 0 |
5 | PY5FO | 0.0014 | 673 | 0 |
6 | W1GD | 0.0017 | 571 | 0 |
7 | Z68XX | 0.0018 | 546 | 0 |
8 | VE3VN | 0.0019 | 1,050 | 1 |
9 | NT6X | 0.0019 | 500 | 0 |
10 | K1BX | 0.0020 | 488 | 0 |
2022 CQ WW CW -- weighted mean values of $p_{bust}$ (run) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | N2GC | 0.0011 | 886 | 0 |
2 | EU8U | 0.0011 | 880 | 0 |
3 | K3WJV | 0.0012 | 802 | 0 |
4 | K1ZZ | 0.0012 | 2,467 | 2 |
5 | DL1SAN | 0.0012 | 774 | 0 |
6 | K1DG | 0.0015 | 2,651 | 3 |
7 | HG0Y | 0.0015 | 1,979 | 2 |
8 | K5ZD | 0.0017 | 3,581 | 5 |
9 | SP9XCN | 0.0018 | 1,118 | 1 |
10 | DM2M | 0.0019 | 519 | 0 |
We can also look at the changes over the period from 2005 to 2022.
First for all QSOs:
Then for calling stations:
And for running stations:
I think it's also interesting to see who appears to have the lowest probability of busting a call over an extended period. So, for the last ten years:
2013--2022 CQ WW SSB -- weighted mean values of $p_{bust}$ (all) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | IK1PMR | 0.0005 | 1,669 | 0 |
2 | IK4OMU | 0.0006 | 1,501 | 0 |
3 | RU3SD | 0.0007 | 1,318 | 0 |
4 | ES2MC | 0.0007 | 2,780 | 1 |
5 | K4RUM | 0.0007 | 1,267 | 0 |
6 | K0PC | 0.0008 | 1,217 | 0 |
7 | NW0M | 0.0008 | 3,649 | 2 |
8 | LY3CY | 0.0008 | 4,832 | 3 |
9 | W4EE | 0.0008 | 1,130 | 0 |
10 | IZ4JMA | 0.0008 | 1,129 | 0 |
2013--2022 CQ WW CW -- weighted mean values of $p_{bust}$ (all) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | NW0M | 0.0002 | 3,926 | 0 |
2 | HL1VAU | 0.0002 | 3,893 | 0 |
3 | WB4TDH | 0.0004 | 5,406 | 1 |
4 | K6WSC | 0.0004 | 4,955 | 1 |
5 | SE6N | 0.0004 | 4,735 | 1 |
6 | AD1C | 0.0004 | 4,731 | 1 |
7 | DL4FN | 0.0004 | 9,137 | 3 |
8 | KM3T | 0.0005 | 1,966 | 0 |
9 | DP4X | 0.0005 | 4,132 | 1 |
10 | JA1QOW | 0.0005 | 3,915 | 1 |
A good argument can be made that a better measure of copying ability is to consider only run QSOs:
2013--2022 CQ WW SSB -- weighted mean values of $p_{bust}$ (run) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | F4FTA | 0.0009 | 1,108 | 0 |
2 | N1EU | 0.0009 | 1,013 | 0 |
3 | R7MM | 0.0011 | 869 | 0 |
4 | ES2MC | 0.0012 | 1,682 | 1 |
5 | CF7RR | 0.0013 | 1,557 | 1 |
6 | DL8RDL | 0.0013 | 734 | 0 |
7 | EE1A | 0.0014 | 673 | 0 |
8 | K0AP | 0.0014 | 665 | 0 |
9 | VA7RR | 0.0015 | 5,494 | 7 |
10 | DL7URH | 0.0016 | 1,262 | 1 |
2013--2022 CQ WW CW -- weighted mean values of $p_{bust}$ (run) | ||||
---|---|---|---|---|
Position | Call | weighted mean | $Q_v$ | $B$ |
1 | LY3CY | 0.0005 | 1,717 | 0 |
2 | RW5CW | 0.0006 | 1,664 | 0 |
3 | W3OA | 0.0006 | 1,573 | 0 |
4 | WQ5L | 0.0006 | 1,520 | 0 |
5 | WB4TDH | 0.0007 | 3,016 | 1 |
6 | SE6N | 0.0007 | 1,369 | 0 |
7 | YU1RA | 0.0007 | 2,787 | 1 |
8 | VX7SZ | 0.0007 | 1,294 | 0 |
9 | KM3T | 0.0008 | 1,193 | 0 |
10 | OM7AT | 0.0009 | 1,102 | 0 |
We can also look at the calls associated with the highest probability of busting calls in either the forward or the reverse direction:
2022 SSB -- Most Busts | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | CN3A | 13,659 | 233 | 1.7 |
2 | FM5KC | 7,324 | 200 | 2.7 |
3 | OT5A | 7,125 | 198 | 2.8 |
4 | K1LZ | 7,577 | 174 | 2.3 |
5 | PJ2T | 10,739 | 163 | 1.5 |
6 | CQ8M | 4,870 | 150 | 3.1 |
7 | CR6K | 9,443 | 149 | 1.6 |
8 | ZF1A | 9,973 | 143 | 1.4 |
9 | F6KOP | 6,423 | 140 | 2.2 |
10 | EA8RM | 11,501 | 139 | 1.2 |
2022 CW -- Most Busts | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | F6KOP | 7,534 | 219 | 2.9 |
2 | EA8RM | 7,981 | 194 | 2.4 |
3 | CN3A | 13,863 | 189 | 1.4 |
4 | TK0C | 12,254 | 188 | 1.5 |
5 | JA3YBK | 5,019 | 145 | 2.9 |
6 | A71BX | 3,542 | 144 | 4.1 |
7 | OT7T | 9,500 | 143 | 1.5 |
8 | IB1D | 2,719 | 141 | 5.2 |
9 | LZ9W | 11,215 | 138 | 1.2 |
10 | PJ2T | 11,682 | 134 | 1.1 |
2022 SSB -- Highest Percentage of Busts (≥100 QSOs) | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | IS0AGY | 108 | 20 | 18.5 |
2 | YD1CMZ | 132 | 20 | 15.2 |
3 | VU2OO | 165 | 24 | 14.5 |
4 | WB7EUJ | 161 | 23 | 14.3 |
5 | YB1KEL | 162 | 23 | 14.2 |
6 | VR2UNG | 120 | 17 | 14.2 |
7 | YB2SPP | 102 | 14 | 13.7 |
8 | YF1ANL | 102 | 14 | 13.7 |
9 | W5AAG | 126 | 16 | 12.7 |
10 | UA3PI | 183 | 21 | 11.5 |
2022 CW -- Highest Percentage of Busts (≥100 QSOs) | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | AI2U | 141 | 34 | 24.1 |
2 | OK1MKD | 110 | 25 | 22.7 |
3 | CM3OR | 193 | 41 | 21.2 |
4 | DL7CO | 181 | 37 | 20.4 |
5 | JJ5NFT | 191 | 39 | 20.4 |
6 | K9HXO | 215 | 42 | 19.5 |
7 | CE6VMO | 295 | 53 | 18.0 |
8 | JK1CNL | 131 | 22 | 16.8 |
9 | DL4DRG | 146 | 24 | 16.4 |
10 | VU2VTI | 117 | 19 | 16.2 |
2022 SSB -- Highest Percentage of Busts (≥100 QSOs) | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | IS0AGY | 108 | 20 | 18.5 |
2 | YD1CMZ | 132 | 20 | 15.2 |
3 | VU2OO | 165 | 24 | 14.5 |
4 | WB7EUJ | 161 | 23 | 14.3 |
5 | YB1KEL | 162 | 23 | 14.2 |
6 | VR2UNG | 120 | 17 | 14.2 |
7 | YB2SPP | 102 | 14 | 13.7 |
8 | YF1ANL | 102 | 14 | 13.7 |
9 | W5AAG | 126 | 16 | 12.7 |
10 | UA3PI | 183 | 21 | 11.5 |
2022 CW -- Highest Percentage of Busts (≥100 QSOs) | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | AI2U | 141 | 34 | 24.1 |
2 | OK1MKD | 110 | 25 | 22.7 |
3 | CM3OR | 193 | 41 | 21.2 |
4 | DL7CO | 181 | 37 | 20.4 |
5 | JJ5NFT | 191 | 39 | 20.4 |
6 | K9HXO | 215 | 42 | 19.5 |
7 | CE6VMO | 295 | 53 | 18.0 |
8 | JK1CNL | 131 | 22 | 16.8 |
9 | DL4DRG | 146 | 24 | 16.4 |
10 | VU2VTI | 117 | 19 | 16.2 |
2022 SSB -- Highest Percentage of Reverse Busts (≥100 QSOs) | |||
---|---|---|---|
Position | Call | QSOs | % Reverse Busts |
1 | NP4WW | 147 | 100.0 |
2 | PT4Z | 1,011 | 20.3 |
3 | TA7YLY | 209 | 18.2 |
4 | 9M4BCN | 170 | 17.1 |
5 | BY4DX | 918 | 14.5 |
6 | OZ0JD | 459 | 13.1 |
7 | BD3OD | 114 | 12.3 |
8 | CT2KNA | 1,122 | 10.8 |
9 | YC0BOY | 115 | 10.4 |
10 | BG6HOK | 117 | 10.3 |
2022 CW -- Highest Percentage of Reverse Busts (≥100 QSOs) | |||
---|---|---|---|
Position | Call | QSOs | % Reverse Busts |
1 | F5PP | 216 | 19.4 |
2 | N3HEE | 340 | 13.5 |
3 | HB75SG | 119 | 13.4 |
4 | EB7A | 6,198 | 13.1 |
5 | SP2HHX | 505 | 12.7 |
6 | IU2OZV | 356 | 11.8 |
7 | W0GJ | 452 | 11.7 |
8 | K3HW | 505 | 11.3 |
9 | SV0SYH | 170 | 11.2 |
10 | BG3HMQ | 117 | 10.3 |
In tables of reverse busts, one sometimes finds what seems like an unreasonable number of reverse busts (as is the case, for example, for NP4WW in the 2022 SSB table above). This is generally caused by a discrepancy between the call actually sent by the listed station and the one recorded as being sent in at least some QSOs in the station's log.
2013--2022 SSB -- Most Busts | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | LZ9W | 91,388 | 1,633 | 1.8 |
2 | CN3A | 79,598 | 1,437 | 1.8 |
3 | OT5A | 61,077 | 1,275 | 2.1 |
4 | PJ2T | 71,347 | 1,261 | 1.8 |
5 | A73A | 55,906 | 1,080 | 1.9 |
6 | V26B | 54,777 | 929 | 1.7 |
7 | YT5A | 61,330 | 895 | 1.5 |
8 | II2S | 48,429 | 870 | 1.8 |
9 | ED1R | 56,728 | 837 | 1.5 |
10 | CR6K | 50,573 | 813 | 1.6 |
2013--2022 CW -- Most Busts | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | LZ9W | 104,970 | 1,176 | 1.1 |
2 | PJ2T | 91,720 | 1,155 | 1.3 |
3 | TK0C | 73,216 | 1,092 | 1.5 |
4 | PI4CC | 48,781 | 970 | 2.0 |
5 | ZW8T | 12,253 | 881 | 7.2 |
6 | JA3YBK | 48,387 | 862 | 1.8 |
7 | RW0A | 49,639 | 830 | 1.7 |
8 | YT5A | 80,598 | 772 | 1.0 |
9 | HG7T | 68,110 | 771 | 1.1 |
10 | VY2TT | 46,404 | 746 | 1.6 |
2013--2022 SSB -- Highest Percentage of Busts (≥500 QSOs) | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | K2JMY | 1,632 | 262 | 16.1 |
2 | EA7JQT | 572 | 71 | 12.4 |
3 | JR1MQT | 775 | 89 | 11.5 |
4 | OH1TS | 660 | 75 | 11.4 |
5 | EA1HTF | 1,762 | 177 | 10.0 |
6 | PU2TRX | 655 | 65 | 9.9 |
7 | EA4GWL | 931 | 91 | 9.8 |
8 | IS0ILP | 553 | 53 | 9.6 |
9 | LU4DJB | 672 | 64 | 9.5 |
10 | YB9KA | 706 | 67 | 9.5 |
2013--2022 CW -- Highest Percentage of Busts (≥500 QSOs) | ||||
---|---|---|---|---|
Position | Call | QSOs | Busts | % Busts |
1 | W2UDT | 668 | 148 | 22.2 |
2 | BD3MV | 896 | 189 | 21.1 |
3 | 4Z5FW | 527 | 108 | 20.5 |
4 | DJ5UZ | 723 | 136 | 18.8 |
5 | DL7CO | 991 | 164 | 16.5 |
6 | WP3Y | 570 | 93 | 16.3 |
7 | CE6VMO | 695 | 111 | 16.0 |
8 | AE3D | 1,016 | 161 | 15.8 |
9 | LZ1BY | 789 | 124 | 15.7 |
10 | IK0YUO | 670 | 104 | 15.5 |
2013--2022 SSB -- Most Reverse Busts | ||||
---|---|---|---|---|
Position | Call | QSOs | Reverse Busts | % Reverse Busts |
1 | DF0HQ | 83,594 | 2,489 | 3.0 |
2 | JA3YBK | 34,097 | 1,177 | 3.5 |
3 | CN3A | 79,598 | 1,084 | 1.4 |
4 | TM3R | 24,257 | 1,049 | 4.3 |
5 | K3LR | 67,007 | 1,019 | 1.5 |
6 | CA3CLF | 982 | 915 | 93.2 |
7 | IK2YCW | 25,411 | 830 | 3.3 |
8 | GM2T | 34,451 | 781 | 2.3 |
9 | OT5A | 61,077 | 775 | 1.3 |
10 | YT5A | 61,330 | 765 | 1.2 |
2013--2022 CW -- Most Reverse Busts | ||||
---|---|---|---|---|
Position | Call | QSOs | Reverse Busts | % Reverse Busts |
1 | JS3CTQ | 22,376 | 2,689 | 12.0 |
2 | DF0HQ | 80,316 | 2,602 | 3.2 |
3 | ES9C | 72,304 | 2,252 | 3.1 |
4 | HG7T | 68,110 | 1,572 | 2.3 |
5 | R2VM | 1,426 | 1,426 | 100.0 |
6 | W2FU | 53,926 | 1,421 | 2.6 |
7 | RM9A | 63,391 | 1,399 | 2.2 |
8 | K3LR | 70,698 | 1,354 | 1.9 |
9 | YT5A | 80,598 | 1,325 | 1.6 |
10 | DR4A | 52,681 | 1,273 | 2.4 |
2013--2022 SSB -- Highest Percentage of Reverse Busts (≥500 QSOs) | |||
---|---|---|---|
Position | Call | QSOs | % Reverse Busts |
1 | CA3CLF | 982 | 93.2 |
2 | PT4Z | 1,011 | 20.3 |
3 | ZP6DYA | 963 | 12.1 |
4 | OG60F | 4,258 | 11.4 |
5 | BY4DX | 1,269 | 11.3 |
6 | BH7PCT | 846 | 10.9 |
7 | LU9DDJ | 862 | 10.4 |
8 | BV55D | 919 | 10.2 |
9 | JG3SVP | 1,270 | 10.1 |
10 | DX3EVM | 527 | 10.1 |
2013--2022 CW -- Highest Percentage of Reverse Busts (≥500 QSOs) | |||
---|---|---|---|
Position | Call | QSOs | % Reverse Busts |
1 | R2VM | 1,426 | 100.0 |
2 | YT65A | 1,149 | 37.2 |
3 | G3RWF | 2,682 | 35.5 |
4 | 5K0A | 1,853 | 32.1 |
5 | PE75W | 1,408 | 29.3 |
6 | OG55W | 3,265 | 28.6 |
7 | TA1C/2 | 1,513 | 18.1 |
8 | DP65HSC | 516 | 16.9 |
9 | 5J1E | 1,523 | 15.6 |
10 | SB0A | 1,102 | 15.5 |
Logs for the REF contest from 2010 to 2023 are now available in this repository of public REF logs.
In addition to zone-based analyses, we can perform similar analyses based on continent rather than zone using the public CQ WW logs (see here for details of the augmented format) for the period from 2005 to 2022.
A counter is maintained for every possible pair of continents and the pertinent counter is incremented
once for each distinct QSO between stations in those continents.
Separate
figures are provided below for each band, led by a figure integrating
QSOs on all bands. The figures are constructed in such a way as to show
the results for both the SSB and CW contests on a single figure. (Any
pair of continents with no QSOs that meet the above criteria appears in
black on the
figures.)
Below is a series of figures showing the distribution of distance for QSOs as a
function of continent.
Each
plot shows a colour-coded distribution of the distance of QSOs for each
continent, with the data for SSB appearing above the data for CW within
each continent.
For every half-QSO in a given continent, the distance
of the QSO is calculated; in this way, the total number of half-QSOs
in
bins of width 500 km is accumulated. Once all the QSOs for a particular
mode have been binned in this manner, the distribution for each
continent
is normalised to total 100% and the result coded by colour and plotted.
The mean distance for each continent and mode is denoted by a small
white
rectangle added to the underlying distance distribution. The 99%
confidence range of the value of mean is marked by a small blue
rectangle (typically entirely subsumed by the white rectangle). The
median is marked with a vertical brown rectangle.
As
usual, only QSOs for which logs have been provided by both parties, and
which show no bust of either callsign or zone number are included. Bins
coloured black are those for which no QSOs are present at the relevant
distance.
The
resulting plots are reproduced below.
A simple way to display the activity in the CQ WW contests
is to count the number of half-QSOs in each continent (a single QSO
contains two half-QSOs, so a single QSO may contain two different
continents or the same continent twice). We count half QSOs, making sure
to include each valid QSO
only once (that is, if the same QSO appears in two submitted logs, it is
counted only once).
If we do this for the entire contest without taking the individual bands into account, we obtain this figure:
The plot shows data for both SSB and CW contests over the period from 2005 to 2022. I include only QSOs for which both parties submitted a log and neither party bust either the zone or the call of the other party. The black triangles represent contests in which no half-QSOs were made from (or to) a particular continent. Perhaps more than any other plot, this makes unmistakable the dominance of EU in the CQ WW contests.
We can, of course, generate equivalent plots on a band-by-band basis:
As in prior years, the activity from EU so overwhelms these figures that in order to get a feel for the activity elsewhere, we need to move to a logarithmic scale:
We can also easily look at the percentage of QSOs that are between two
stations on the same continent, and in particular between two EU
stations:
So, for example, in CQ WW CW in 2022, a quarter of all QSOs were
within the same continent; nearly a fifth of all QSOs were
between two European stations. This despite much-improved conditions for DX contacts and the near-elimination of the two largest countries in Europe because of the Russian invasion of Ukraine.
Flogging a dead horse, as I do every year, and even in the current year -- a year in which activity from the two largest countries in Europe was greatly diminished -- on 160m more than 60% of QSOs in this "world wide DX" contest were between two European entrants, even in the more DX-friendly mode. On SSB, about three quarters of all QSOs were between two European entrants.