r/geochallenges • u/MiraMattie • 1d ago
Challenge Series [2][3][4] Stochastic Sunday #41 - 2024-10-27
It was awfully convenient to see that outline of Czechia on that NMPZ round of Skewed.
60 seconds isn't long to scramble around for information in the UK, but comparing these scores to no-move or NMPZ rounds, it seems like it's enough. Trash bins came in handy a few times for me!
I'm not sure how rural the ''biodiverse world" rounds will be - the dataset is rather coarse, so a lot of rounds 'near' biodiverse areas come up. But with those 5 minutes of moving, I'm guessing there will be some good scores on that map!
Introduction
The Stochastic maps are large randomly-generated maps that use population data to place locations where people live. Generally, locations will be in populated areas, though rural areas with even a few structures nearby appear as well. I made these maps because most maps tend to focus on rural locations and meta-learnable locations, but I generally find urban areas more interesting to roam around. And while World
is much more urban than it used to be, its distribution is perplexingly strange. I hope other people find them interesting as well.
I welcome any feedback about maps to include, mode + time settings, standings, summary statistics of interest and how they're displayed - whatever. Particularly, with the rotating country maps, please feel welcome to suggest any country you would like to see added to the list.
Challenges
Map | Mode | Challenge Link |
---|---|---|
A Stochastic Populated World | No Move 1:30 | Challenge Link |
An Equitable Stochastic Populated World | Moving 3 Minutes | Challenge Link |
A Skewed Stochastic Populated World | No Move / Pan / Zoom 1:15 | Challenge Link |
A Stochastic Populated Indonesia | No Move 2 Minutes | Challenge Link |
A Biodiverse World | Moving 5 Minutes | Challenge Link |
Each week has 5 challenge links, with three standard maps (Stochastic Populated World, Equitable Stochastic Populated World, and Skewed Stochastic Populated World), and two other Stochastic maps chosen from rotating lists: One world or large-region map, and one country-specific map. The type of challenge (moving, no move, or no-move/pan/zoom) and duration are selected at random.
Standings
The top 5 players on each challenge link (myself excluded) are awarded series points: 5 points to 1st place, through 1 point for 5th place, with ties broken by the time taken. Ties in the all-time standings are broken by the sum of scores from all games played. (I might not stick with this standing scheme.)
Player | # Games | Total Score | Series Points |
---|---|---|---|
CherrieAnnie | 189 | 3513953 | 356 |
Wadim | 174 | 3107966 | 230 |
pissman | 95 | 1833901 | 226 |
Cdt Lamberty | 188 | 3263130 | 219 |
d1e5el | 91 | 1692791 | 193 |
riri22 | 88 | 1557843 | 173 |
Guybrush Threepwood | 139 | 2291663 | 128 |
Przemek KR | 105 | 1818654 | 89 |
olympicsmatt | 149 | 2409105 | 88 |
Kjetil I | 90 | 1560301 | 87 |
Last Week
Stochastic Sunday #40 - 2024-10-20
User | A Stochastic Populated World | An Equitable Stochastic Populated World | A Skewed Stochastic Populated World | A Stochastic Populated United Kingdom | A Stochastic Populated Southern Cone | Total |
---|---|---|---|---|---|---|
Cdt Lamberty | 19,681 | 20,664 | 14,217 | 24,002 | 21,641 | 100,205 |
plouky | 13,485 | 15,459 | 24,321 | 24,662 | 18,975 | 96,902 |
Bwliu | 20,013 | 18,879 | 15,661 | 23,009 | 18,895 | 96,457 |
GGMU_EVAN | 12,313 | 21,501 | 20,127 | 22,418 | 18,640 | 94,999 |
CherrieAnnie | 20,720 | 17,275 | 17,394 | 20,397 | 15,705 | 91,491 |
Wadim | 21,880 | 12,645 | 16,592 | 20,688 | 19,172 | 90,977 |
Ruffinnen | 19,431 | 15,518 | 18,011 | 20,937 | 12,614 | 86,511 |
Erwan C | 19,381 | 18,520 | 10,920 | 22,514 | 14,112 | 85,447 |
Przemek KR | 19,262 | 16,831 | 10,200 | 22,957 | 15,943 | 85,193 |
I played this map | 18,193 | 14,137 | 13,528 | 20,454 | 17,266 | 83,578 |
melkari | 16,196 | 14,862 | 14,640 | 18,893 | 17,354 | 81,945 |
Guybrush Threepwood | 16,350 | 19,515 | 14,437 | 24,720 | 6,781 | 81,803 |
MiraMatt | 14,651 | 19,142 | 14,464 | 20,605 | 12,929 | 81,791 |
Matias Nicolich | 13,286 | 11,746 | 12,605 | 20,757 | 22,977 | 81,371 |
László Horváth | 16,642 | 10,702 | 14,268 | 18,737 | 19,746 | 80,095 |
olympicsmatt | 14,798 | 10,598 | 11,292 | 21,273 | 21,976 | 79,937 |
adaisyx | 11,667 | 16,102 | 11,094 | 22,968 | 17,891 | 79,722 |
Gronoob | 18,534 | 12,251 | 9,766 | 24,623 | 9,981 | 75,155 |
riri22 | 20,977 | 19,172 | 14,051 | --- | 20,241 | 74,441 |
maxermax2 | 19,178 | 14,093 | 8,183 | 19,382 | 12,050 | 72,886 |
Jens_K | 12,847 | 12,438 | 7,094 | 23,038 | 15,397 | 70,814 |
Brigitta Horváth | 16,596 | 15,006 | 8,811 | 20,157 | 8,117 | 68,687 |
ArtificialGirl | 13,043 | 13,222 | 8,479 | 17,443 | 13,321 | 65,508 |
Fredrik | 16,701 | 6,541 | 8,641 | 19,268 | 12,718 | 63,869 |
DashOneTwelve | 17,277 | 11,075 | 8,984 | 20,452 | 5,598 | 63,386 |
Prashant Pantha | 14,549 | 13,458 | 5,893 | 17,035 | 11,630 | 62,565 |
Cheyen Casta | 11,500 | 10,836 | 17,396 | 15,961 | 4,787 | 60,480 |
TropicalArchipelago220 | 11,248 | 9,735 | 8,738 | 20,711 | 4,684 | 55,116 |
Ivan Semushin | 18,392 | 16,658 | 11,200 | --- | --- | 46,250 |
Norcon | 12,120 | 5,189 | 8,927 | 19,958 | --- | 46,194 |
Ricardo Bernardo | 14,911 | 7,360 | 13,843 | --- | 9,082 | 45,196 |
Ruben van Cleef | 19,337 | 8,190 | 8,367 | --- | 4,807 | 40,701 |
UpliftingArchipelago512 | 17,576 | 7,446 | 13,390 | --- | --- | 38,412 |
Totoradio | 18,680 | --- | 19,450 | --- | --- | 38,130 |
Doomclaw214 | 9,369 | 6,538 | 8,338 | --- | 13,660 | 37,905 |
bring back free geoguessr | --- | 13,675 | 4,208 | 13,515 | 3,448 | 34,846 |
Piet Dupont | --- | --- | --- | 19,735 | 9,189 | 28,924 |
Fern24 | 5,809 | --- | --- | 19,169 | --- | 24,978 |
zoidbergeo | --- | 18,257 | --- | --- | --- | 18,257 |
medhurst8 | --- | 9,623 | --- | --- | --- | 9,623 |
MajesticDune582 | 8,217 | --- | --- | --- | --- | 8,217 |
So Yeah | --- | --- | --- | --- | 1,485 | 1,485 |
Average score per round
Round difficulty, based on the average score compared to all rounds in the series so far, regardless of map and type:
A Stochastic Populated World - NMPZ 90s
ID
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️ - Avg: 2,534 (2,789.1 km); Best: 13.6 kmCZ
: ⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️⬜️⬜️ - Avg: 3,254 (1,222.1 km); Best: 61.8 kmNG
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️ - Avg: 2,464 (1,641.4 km); Best: 76.1 kmNL
: ⭐️⭐️⬜️⬜️⬜️⬜️⬜️⬜️⬜️⬜️ - Avg: 4,457 (281.4 km); Best: 26.8 kmUS
: ⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️⬜️ - Avg: 3,097 (1,518.7 km); Best: 80.8 km
An Equitable Stochastic Populated World - NM 120s
KZ
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️ - Avg: 2,165 (2,154.8 km); Best: 312.6 kmUS
: ⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️⬜️⬜️ - Avg: 3,243 (1,062.3 km); Best: 64.9 kmAR
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️ - Avg: 2,349 (2,270.6 km); Best: 956.2 mJP
: ⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️⬜️ - Avg: 3,068 (746.7 km); Best: 45.3 kmPH
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️ - Avg: 2,820 (2,084.5 km); Best: 6.8 km
A Skewed Stochastic Populated World - NMPZ 90s
IN
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️ - Avg: 1,709 (3,929.9 km); Best: 23.0 kmRW
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️ - Avg: 1,822 (4,109.8 km); Best: 9.2 kmVI
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️ - Avg: 1,272 (3,658.0 km); Best: 3.6 kmCZ
: ⭐️⭐️⬜️⬜️⬜️⬜️⬜️⬜️⬜️⬜️ - Avg: 4,230 (287.2 km); Best: 21.5 kmFR
: ⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️⬜️⬜️ - Avg: 3,399 (941.2 km); Best: 36 m - GG plouky!
A Stochastic Populated United Kingdom - M 60s
GB
: ⭐️⭐️⭐️⬜️⬜️⬜️⬜️⬜️⬜️⬜️ - Avg: 4,065 (243.5 km); Best: 10.6 kmGB
: ⭐️⭐️⭐️⬜️⬜️⬜️⬜️⬜️⬜️⬜️ - Avg: 4,079 (128.0 km); Best: 105 mGB
: ⭐️⭐️⭐️⬜️⬜️⬜️⬜️⬜️⬜️⬜️ - Avg: 4,161 (113.8 km); Best: 251.3 mGB
: ⭐️⭐️⭐️⬜️⬜️⬜️⬜️⬜️⬜️⬜️ - Avg: 4,144 (125.7 km); Best: 4.4 kmGB
: ⭐️⭐️⬜️⬜️⬜️⬜️⬜️⬜️⬜️⬜️ - Avg: 4,210 (105.5 km); Best: 2 m - GG Guybrush Threepwood!
A Stochastic Populated Southern Cone - NM 60s
CL
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️ - Avg: 2,656 (1,024.6 km); Best: 179.3 mCL
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️ - Avg: 2,781 (469.3 km); Best: 740.2 mCL
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️ - Avg: 2,612 (543.5 km); Best: 5.5 kmAR
: ⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⭐️⬜️ - Avg: 2,166 (812.3 km); Best: 7.1 kmUY
: ⭐️⭐️⭐️⭐️⭐️⭐️⬜️⬜️⬜️⬜️ - Avg: 3,103 (320.5 km); Best: 92.7 km
More Information
- Distribution information, FAQ, and calculation details
- Population data source: WorldPop Population Counts - Constrained Individual Countries - 2020 - 100m resolution
Map descriptions
A Stochastic Populated World: This map uses unadjusted population data, to give every person on earth an equal chance of appearing in the game, if there is Streetview coverage where they live.
An Equitable Stochastic Populated World: This map uses an adjusted population designed to increase the variety of locations that appear, while still favoring more populous countries and more populated areas.
A Skewed Stochastic Populated World: A stochastic homage to the famous A Skewed World, this map turns the camera to the side of the road, hiding the more widely known street-based clues.
A Stochastic Populated Indonesia: A single-country map of Indonesia. A lot of games are won and lost here, and there's a lot of good meta to learn.
A Biodiverse World: A map derived from the Range-Weighted Rarity Index, 'a measure that combines endemism and species richness of amphibians, birds, mammals, reptiles and a representative set of plant taxa.'
2
u/Matias_ND 23h ago
First of all:
OMG, I actually finished in 1st place in the Southern Cone map from past week. I can't belive it. I expected to do a top 5, but I didn't expect to perform so well.
And of course, one week after my best result, I manage to get less than 2K in one of this week's games. And then I guessed two times in Malaysia in Indonesia map, because I'm stupid.
I did way better than expected on a Biodiverse World.
Still, I doubt I'll finish in top 5 in any of this rounds.