What Bands are in Both MS and MA?

Just a quick note here.  Its something like 2k+ bands that are on MS but not MA.  Some of these are just spelling mistakes and I don’t care enough to go through the whole list, but its probably somewhat close.  After looking through a random assortment to test, its probably a good guess.  Probably.  A lot of these are going to be either not metal, core bands, or other non-MA kosher bands.

I had thought perhaps I was on to something with similar artists and that I would find that all of the bands in MA that had similar artists listed would be bands on MS and thus MS has mostly more popular bands.  BUT, that’s not the case.  Only about half of the bands in MS show up on the MA SA list.

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Similar Artists and the Quest for Relevance.

As I mull around the idea of a cool way to plot interconnections from similar artists, I’ve noticed something.  There are only about 14k bands that actually have info on similar artists.  Of those ~2k of them haven’t released a full length album.  At first I thought that I had captured the data wrong, but sure enough each band I check in the list don’t have any similar artists.  Also, keep in mind that references do not show up until there are at least 3 votes.

What’s more, this may be another metric by which to judge “relevance, value, success, etc.” because the more people listen to a band, the more likely they are to enter in data on similar artists.  Anecdotally, I looked at my own stash and I find that almost all of the band I listen to are included in this 14k list.  The ones that are not are really out there, random,  or demo-y or ep-y bands that probably aren’t that “successful”.  Bands I thought somewhat obscure turn out to have plenty of hits in sim arts.  Turns out I’m just some un-kvlt surface dweller I guess?

Taking this info, what is the most linked to band?  Here are the top 10:

Band # Links
Testament 321
Kreator 250
Exodus 242
Sodom 216
Iron Maiden 210
Slayer 210
Death 206
Bathory 197
Judas Priest 197
Morbid Angel 194

What does this mean?  I’m not sure exactly.  I would not call this “most influential bands” or “most emulated bands” necessarily.  Perhaps it tells a story of the pervasiveness of the sound these bands represent: older and thrashier, and how it relates to the user base of the website.

Now, what about number of ratings given to a band?

Band # of votes
Black Sabbath 4798
Venom 4675
Death 4674
Judas Priest 4479
Slayer 4467
Kreator 4464
Bathory 4415
Sodom 4322
Testament 4220
Exodus 4163

This looks more like it could be a “popularity” index for MA.  Then again, bands that have more similar bands listed may pull in more votes overall if people just go “yup, yup, yup” down the line when they agree, compounding the scale.

So, what if I take this list and use it again to look at bands per capita?  Before you go look at this massive table that you should copy and filter yourself, here are top tens given different setups:

Rank All/All/All Full/Active/All All/All/SA Full/Active/SA
1 Finland Finland Finland Finland
2 Sweden Iceland Sweden Sweden
3 Iceland Liechtenstein Iceland Liechtenstein
4 Norway Sweden Norway Iceland
5 Liechtenstein Norway Liechtenstein Norway
6 Greece Malta Monaco Andorra
7 Monaco Greece Andorra Greece
8 Denmark Estonia Denmark Malta
9 Malta Czech Republic Greece Denmark
10 Estonia Slovenia Austria Austria

The big take away here is no matter how you slice it, Finland wins out per capita.  Sweden, Iceland, Norway, and Liechtenstein then trade the next 4 slots with norway typically at 3/4 and Sweden almost always 2nd.  The last 5 slots are a bit of a mish-mash with bands coming in and out of the ranking, Greece being the only mainstay.

Here’s all the daters:

Country Population Total Band Count Bands/100k Full Active Bands Bands/100k Total SimArts Bands/100k Full Active SimArts Bands/100k
Faeroe Islands 2912 13 446.43 8 274.73 4 137.36 3.00 103.02
Finland 5523904 3566 64.56 1023 18.52 637 11.53 371.00 6.72
Sweden 9851852 4273 43.37 1234 12.53 1016 10.31 560.00 5.68
Liechtenstein 37776 11 29.12 5 13.24 3 7.94 2.00 5.29
Iceland 331778 117 35.26 44 13.26 29 8.74 17.00 5.12
Norway 5271958 1575 29.88 541 10.26 428 8.12 243.00 4.61
Aland Islands 29013 6 20.68 2 6.89 2 6.89 1.00 3.45
Andorra 69165 4 5.78 2 2.89 2 2.89 2.00 2.89
Greece 10919459 1863 17.06 672 6.15 275 2.52 195.00 1.79
Malta 419615 62 14.78 28 6.67 7 1.67 7.00 1.67
Denmark 5690750 901 15.83 214 3.76 163 2.86 82.00 1.44
Austria 8569633 1100 12.84 370 4.32 156 1.82 86.00 1.00
Netherlands 16979729 2193 12.92 530 3.12 275 1.62 158.00 0.93
Australia 24309330 2284 9.40 738 3.04 371 1.53 217.00 0.89
Czech Republic 10548058 1351 12.81 562 5.33 132 1.25 87.00 0.82
Slovenia 2069362 259 12.52 99 4.78 23 1.11 17.00 0.82
Canada 36286378 3591 9.90 1246 3.43 498 1.37 295.00 0.81
Switzerland 8379477 960 11.46 354 4.22 108 1.29 65.00 0.78
Germany 80682351 10189 12.63 3083 3.82 1004 1.24 617.00 0.76
Estonia 1309104 192 14.67 77 5.88 11 0.84 10.00 0.76
United Kingdom 65111143 4611 7.08 1368 2.10 755 1.16 426.00 0.65
Portugal 10304434 1229 11.93 312 3.03 101 0.98 67.00 0.65
Italy 59801004 6035 10.09 2124 3.55 537 0.90 385.00 0.64
Curaçao 158635 1 0.63 1 0.63 1 0.63 1.00 0.63
Chile 18131850 1913 10.55 614 3.39 187 1.03 114.00 0.63
United States 324118787 24246 7.48 7904 2.44 3623 1.12 1,997.00 0.62
Belgium 11371928 1171 10.30 318 2.80 121 1.06 68.00 0.60
Poland 38593161 3199 8.29 888 2.30 330 0.86 210.00 0.54
Hungary 9821318 1065 10.84 301 3.06 78 0.79 53.00 0.54
Ireland 4713993 379 8.04 93 1.97 37 0.78 25.00 0.53
New Zealand 4565185 354 7.75 112 2.45 39 0.85 24.00 0.53
Luxembourg 576243 82 14.23 22 3.82 5 0.87 3.00 0.52
Latvia 1955742 105 5.37 55 2.81 13 0.66 10.00 0.51
Cyprus 1176598 67 5.69 27 2.29 8 0.68 6.00 0.51
Slovakia 5429418 540 9.95 194 3.57 39 0.72 27.00 0.50
Croatia 4225001 392 9.28 120 2.84 32 0.76 20.00 0.47
Lithuania 2850030 168 5.89 60 2.11 15 0.53 12.00 0.42
Spain 46064604 3258 7.07 1244 2.70 298 0.65 193.00 0.42
France 64668129 4707 7.28 1412 2.18 412 0.64 255.00 0.39
Israel 8192463 255 3.11 84 1.03 35 0.43 24.00 0.29
Serbia 8812705 382 4.33 155 1.76 40 0.45 25.00 0.28
Belarus 9481521 364 3.84 172 1.81 32 0.34 25.00 0.26
Bulgaria 7097796 365 5.14 122 1.72 26 0.37 17.00 0.24
Bosnia and Herzegovina 3802134 120 3.16 32 0.84 13 0.34 9.00 0.24
Singapore 5696506 247 4.34 75 1.32 19 0.33 13.00 0.23
Botswana 2303820 9 0.39 7 0.30 5 0.22 5.00 0.22
Bahrain 1396829 12 0.86 4 0.29 4 0.29 3.00 0.21
Uruguay 3444071 182 5.28 56 1.63 12 0.35 7.00 0.20
Armenia 3026048 18 0.59 11 0.36 6 0.20 6.00 0.20
Russian Federation 143439832 3490 2.43 1729 1.21 349 0.24 251.00 0.17
Colombia 48654392 1379 2.83 522 1.07 122 0.25 83.00 0.17
Costa Rica 4857218 204 4.20 74 1.52 9 0.19 8.00 0.16
Puerto Rico 3680772 147 3.99 43 1.17 11 0.30 6.00 0.16
Ukraine 44624373 886 1.99 431 0.97 111 0.25 68.00 0.15
Argentina 43847277 1901 4.34 712 1.62 110 0.25 62.00 0.14
Japan 126323715 1756 1.39 651 0.52 276 0.22 165.00 0.13
Brazil 209567920 5444 2.60 1510 0.72 436 0.21 261.00 0.12
Mexico 128632004 2428 1.89 904 0.70 236 0.18 156.00 0.12
Georgia 3979781 22 0.55 15 0.38 5 0.13 4.00 0.10
Jordan 7747800 30 0.39 13 0.17 7 0.09 7.00 0.09
Ecuador 16385450 334 2.04 139 0.85 18 0.11 14.00 0.09
Mauritius 1277459 2 0.16 1 0.08 1 0.08 1.00 0.08
Paraguay 6725430 145 2.16 43 0.64 6 0.09 5.00 0.07
Romania 19372734 363 1.87 148 0.76 19 0.10 14.00 0.07
Taiwan 23395600 67 0.29 37 0.16 22 0.09 16.00 0.07
Bolivia 10888402 228 2.09 77 0.71 9 0.08 7.00 0.06
Peru 31774225 452 1.42 136 0.43 34 0.11 19.00 0.06
Lebanon 5988153 45 0.75 19 0.32 6 0.10 3.00 0.05
Nicaragua 6150035 24 0.39 10 0.16 5 0.08 3.00 0.05
Macedonia 2081012 98 4.71 39 1.87 3 0.14 1.00 0.05
Venezuela 31518855 384 1.22 150 0.48 20 0.06 15.00 0.05
Albania 2896679 10 0.35 4 0.14 3 0.10 1.00 0.03
Mongolia 3006444 6 0.20 4 0.13 1 0.03 1.00 0.03
Malaysia 30751602 574 1.87 115 0.37 17 0.06 10.00 0.03
Republic of Korea 50503933 227 0.45 75 0.15 27 0.05 16.00 0.03
Syria 18563595 31 0.17 14 0.08 6 0.03 5.00 0.03
Turkey 79622062 488 0.61 128 0.16 30 0.04 21.00 0.03
Panama 3990406 71 1.78 15 0.38 2 0.05 1.00 0.03
United Arab Emirates 9266971 25 0.27 5 0.05 2 0.02 2.00 0.02
Tunisia 11375220 23 0.20 13 0.11 3 0.03 2.00 0.02
Kyrgyzstan 6033769 7 0.12 3 0.05 1 0.02 1.00 0.02
El Salvador 6146419 137 2.23 34 0.55 3 0.05 1.00 0.02
South Africa 54978907 194 0.35 70 0.13 14 0.03 8.00 0.01
Lao PDR 6918367 5 0.07 1 0.01 1 0.01 1.00 0.01
Nepal 28850717 22 0.08 12 0.04 4 0.01 3.00 0.01
Azerbaijan 9868447 8 0.08 6 0.06 1 0.01 1.00 0.01
Dominican Republic 10648613 30 0.28 9 0.08 1 0.01 1.00 0.01
Saudi Arabia 32157974 12 0.04 7 0.02 3 0.01 3.00 0.01
Indonesia 260581100 1548 0.59 551 0.21 33 0.01 24.00 0.01
Cuba 11392889 78 0.68 21 0.18 1 0.01 1.00 0.01
Iraq 37547686 9 0.02 6 0.02 4 0.01 3.00 0.01
Iran 80043146 71 0.09 44 0.05 10 0.01 6.00 0.01
Philippines 102250133 240 0.23 67 0.07 8 0.01 7.00 0.01
Egypt 93383574 33 0.04 20 0.02 9 0.01 6.00 0.01
Guatemala 16672956 134 0.80 41 0.25 1 0.01 1.00 0.01
Thailand 68146609 168 0.25 47 0.07 7 0.01 4.00 0.01
Kazakhstan 17855384 49 0.27 22 0.12 1 0.01 1.00 0.01
Sri Lanka 20810816 33 0.16 5 0.02 4 0.02 1.00 0.00
Bangladesh 162910864 64 0.04 27 0.02 15 0.01 5.00 0.00
Algeria 40375954 23 0.06 6 0.01 2 0.00 1.00 0.00
Kenya 47251449 4 0.01 1 0.00 2 0.00 1.00 0.00
China 1382323332 283 0.02 127 0.01 40 0.00 26.00 0.00
Pakistan 192826502 49 0.03 10 0.01 5 0.00 3.00 0.00
India 1326801579 185 0.01 61 0.00 14 0.00 8.00 0.00
Monaco 37863 6 15.85 1 2.64 2 5.28 0 0.00
Barbados 285006 2 0.70 0 0.00 1 0.35 0 0.00
Belize 366942 6 1.64 3 0.82 1 0.27 0 0.00
Jamaica 2803362 1 0.04 0 0.00 1 0.04 0 0.00
Oman 4654471 2 0.04 1 0.02 1 0.02 0 0.00
Morocco 34817065 22 0.06 7 0.02 1 0.00 0 0.00
Svalbard 2667 2 74.99 1 37.50 0 0.00 0 0.00
Guernsey 63026 13 20.63 8 12.69 0 0.00 0 0.00
Greenland 56196 5 8.90 3 5.34 0 0.00 0 0.00
San Marino 31950 2 6.26 1 3.13 0 0.00 0 0.00
Maldives 369812 8 2.16 5 1.35 0 0.00 0 0.00
New Caledonia 266431 6 2.25 2 0.75 0 0.00 0 0.00
Brunei Darussalam 428874 20 4.66 3 0.70 0 0.00 0 0.00
Montenegro 626101 10 1.60 4 0.64 0 0.00 0 0.00
Suriname 547610 2 0.37 2 0.37 0 0.00 0 0.00
Moldova 4062862 31 0.76 13 0.32 0 0.00 0 0.00
Honduras 8189501 44 0.54 23 0.28 0 0.00 0 0.00
Trinidad and Tobago 1364973 7 0.51 2 0.15 0 0.00 0 0.00
Kuwait 4007146 6 0.15 5 0.12 0 0.00 0 0.00
Turkmenistan 5438670 3 0.06 2 0.04 0 0.00 0 0.00
Madagascar 24915822 9 0.04 5 0.02 0 0.00 0 0.00
Uzbekistan 30300446 7 0.02 5 0.02 0 0.00 0 0.00
Tajikistan 8669464 5 0.06 1 0.01 0 0.00 0 0.00
Vietnam 94444200 39 0.04 7 0.01 0 0.00 0 0.00
Qatar 22913668 2 0.01 1 0.00 0 0.00 0 0.00
Angola 25830958 3 0.01 1 0.00 0 0.00 0 0.00
Afghanistan 33369945 1 0.00 1 0.00 0 0 0 0.00
Uganda 40322768 2 0.00 1 0.00 0 0.00 0 0.00
Guam 172094 5 2.91 0 0.00 0 0.00 0 0.00
Isle of Man 88421 2 2.26 0 0.00 0 0.00 0 0.00
Aruba 104263 1 0.96 0 0.00 0 0.00 0 0.00
French Polynesia 275688 1 0.36 0 0.00 0 0.00 0 0.00
Guyana 770910 2 0.26 0 0.00 0 0.00 0 0.00
Namibia 2513981 2 0.08 0 0.00 0 0.00 0 0.00
Libya 6330159 3 0.05 0 0.00 0 0.00 0 0.00
Cambodia 15827241 2 0.01 0 0.00 0 0.00 0 0.00
Mozambique 28751362 2 0.01 0 0.00 0 0.00 0 0.00
Zambia 16717332 1 0.01 0 0.00 0 0.00 0 0.00
Myanmar 54363426 3 0.01 0 0.00 0 0.00 0 0.00
Ethiopia 101853268 1 0.00 0 0.00 0 0.00 0 0.00
Gibraltar 0 4 0.00 2 0.00 1 0.00 1.00 0.00
Jersey 0 5 0.00 4 0.00 2 0.00 2.00 0.00
Unknown 0 48 0.00 14 0.00 11 0.00 4.00 0.00
International 0 611 0.00 298 0.00 173 0.00 113.00 0.00
Reunion 0 6 0.00 3 0.00 0 0.00 0 0.00

Population Schmopulation

I think I’ve mentioned before how plotting the number of bands per capita is a bit misleading and I’ve finally gotten around to taking a closer look.

Take for example sports teams.  You don’t see people walking around saying “X state is the best state for Y sport”, or at least they shouldn’t.  It is very common for different “dynasties” to emerge and dominate sports for a period of time.  But why would you look over all time with changing players, teams, coaches, etc. for given states to make determinations on “whose the best”?

Likewise, why would you want to compare ALL BANDS EVER on MA to POPULATION STATS NOW???  What it should be is a time series of bands that are “active” versus population for a given year.  By year since bands usually don’t release more than one album a year and that is the least significant time step we have available.  Also, and on my todo list, instead of looking at bands shouldn’t I look at albums?  (Update: I did, it’s very similar.  Look at my previous post on releases)  Perhaps there are lots of bands for a given country but they all sat on their asses for a couple years whilst being “active”.

If none of that makes sense…yes, yes I’m sure it doesn’t make sense.  Anyway, here’s some data.

These plot depicts counts per 2016 capita for all bands and then for bands that have released full length albums that are designated “Active” on MA from the first quarter of 2016.

All Bands:

Map_World_BandsPerCapita_All_NowMap_Europe_BandsPerCapita_All_Now

Only Full, Active Bands:Map_World_BandsPerCapita_Full_Active_Now

Map_Europe_BandsPerCapita_Full_Active_Now

Yeah, it looks the same essentially to what’s already out there.  And yeah, differences are hard to see on the map.  But take a look at the actual numbers.  Differences are somewhat minor, but still things ARE different.  

Right now I have it sorted by most full active bands per 100k.  You take it and sort it other ways on your own.  I still have to figure out better tables.

So, what are the differences really?  What countries fair better now and when you remove demo clutter?  Not including over seas territories and micronations:

  1. Movement up in central Europe, Austria, Czechia, Slovenia, Switzerland, Slovakia
  2.  Big move down for Denmark, Belgium, Portugal, the Netherlands, Ireland
  3. Other boosts for Canada, Italy, Latvia
  4. Finland is still on top, along with the rest of the north.
Country Population Total Band Count Bands/100k Full Active Bands Bands/100k
Faeroe Islands 2912 13 446.43 8 274.73
Svalbard 2667 2 74.99 1 37.50
Finland 5523904 3566 64.56 1023 18.52
Iceland 331778 117 35.26 44 13.26
Liechtenstein 37776 11 29.12 5 13.24
Guernsey 63026 13 20.63 8 12.69
Sweden 9851852 4273 43.37 1234 12.53
Norway 5271958 1575 29.88 541 10.26
Aland Islands 29013 6 20.68 2 6.89
Malta 419615 62 14.78 28 6.67
Greece 10919459 1863 17.06 672 6.15
Estonia 1309104 192 14.67 77 5.88
Greenland 56196 5 8.90 3 5.34
Czech Republic 10548058 1351 12.81 562 5.33
Slovenia 2069362 259 12.52 99 4.78
Austria 8569633 1100 12.84 370 4.32
Switzerland 8379477 960 11.46 354 4.22
Germany 80682351 10189 12.63 3083 3.82
Luxembourg 576243 82 14.23 22 3.82
Denmark 5690750 901 15.83 214 3.76
Slovakia 5429418 540 9.95 194 3.57
Italy 59801004 6035 10.09 2124 3.55
Canada 36286378 3591 9.90 1246 3.43
Chile 18131850 1913 10.55 614 3.39
San Marino 31950 2 6.26 1 3.13
Netherlands 16979729 2193 12.92 530 3.12
Hungary 9821318 1065 10.84 301 3.06
Australia 24309330 2284 9.40 738 3.04
Portugal 10304434 1229 11.93 312 3.03
Andorra 69165 4 5.78 2 2.89
Croatia 4225001 392 9.28 120 2.84
Latvia 1955742 105 5.37 55 2.81
Belgium 11371928 1171 10.30 318 2.80
Spain 46064604 3258 7.07 1244 2.70
Monaco 37863 6 15.85 1 2.64
New Zealand 4565185 354 7.75 112 2.45
United States 324118787 24246 7.48 7904 2.44
Poland 38593161 3199 8.29 888 2.30
Cyprus 1176598 67 5.69 27 2.29
France 64668129 4707 7.28 1412 2.18
Lithuania 2850030 168 5.89 60 2.11
United Kingdom 65111143 4611 7.08 1368 2.10
Ireland 4713993 379 8.04 93 1.97
Macedonia 2081012 98 4.71 39 1.87
Belarus 9481521 364 3.84 172 1.81
Serbia 8812705 382 4.33 155 1.76
Bulgaria 7097796 365 5.14 122 1.72
Uruguay 3444071 182 5.28 56 1.63
Argentina 43847277 1901 4.34 712 1.62
Costa Rica 4857218 204 4.20 74 1.52
Maldives 369812 8 2.16 5 1.35
Singapore 5696506 247 4.34 75 1.32
Russian Federation 143439832 3490 2.43 1729 1.21
Puerto Rico 3680772 147 3.99 43 1.17
Colombia 48654392 1379 2.83 522 1.07
Israel 8192463 255 3.11 84 1.03
Ukraine 44624373 886 1.99 431 0.97
Ecuador 16385450 334 2.04 139 0.85
Bosnia and Herzegovina 3802134 120 3.16 32 0.84
Belize 366942 6 1.64 3 0.82
Romania 19372734 363 1.87 148 0.76
New Caledonia 266431 6 2.25 2 0.75
Brazil 209567920 5444 2.60 1510 0.72
Bolivia 10888402 228 2.09 77 0.71
Mexico 128632004 2428 1.89 904 0.70
Brunei Darussalam 428874 20 4.66 3 0.70
Paraguay 6725430 145 2.16 43 0.64
Montenegro 626101 10 1.60 4 0.64
Curaçao 158635 1 0.63 1 0.63
El Salvador 6146419 137 2.23 34 0.55
Japan 126323715 1756 1.39 651 0.52
Venezuela 31518855 384 1.22 150 0.48
Peru 31774225 452 1.42 136 0.43
Georgia 3979781 22 0.55 15 0.38
Panama 3990406 71 1.78 15 0.38
Malaysia 30751602 574 1.87 115 0.37
Suriname 547610 2 0.37 2 0.37
Armenia 3026048 18 0.59 11 0.36
Moldova 4062862 31 0.76 13 0.32
Lebanon 5988153 45 0.75 19 0.32
Botswana 2303820 9 0.39 7 0.30
Bahrain 1396829 12 0.86 4 0.29
Honduras 8189501 44 0.54 23 0.28
Guatemala 16672956 134 0.80 41 0.25
Indonesia 260581100 1548 0.59 551 0.21
Cuba 11392889 78 0.68 21 0.18
Jordan 7747800 30 0.39 13 0.17
Nicaragua 6150035 24 0.39 10 0.16
Turkey 79622062 488 0.61 128 0.16
Taiwan 23395600 67 0.29 37 0.16
Republic of Korea 50503933 227 0.45 75 0.15
Trinidad and Tobago 1364973 7 0.51 2 0.15
Albania 2896679 10 0.35 4 0.14
Mongolia 3006444 6 0.20 4 0.13
South Africa 54978907 194 0.35 70 0.13
Kuwait 4007146 6 0.15 5 0.12
Kazakhstan 17855384 49 0.27 22 0.12
Tunisia 11375220 23 0.20 13 0.11
Dominican Republic 10648613 30 0.28 9 0.08
Mauritius 1277459 2 0.16 1 0.08
Syria 18563595 31 0.17 14 0.08
Thailand 68146609 168 0.25 47 0.07
Philippines 102250133 240 0.23 67 0.07
Azerbaijan 9868447 8 0.08 6 0.06
Iran 80043146 71 0.09 44 0.05
United Arab Emirates 9266971 25 0.27 5 0.05
Kyrgyzstan 6033769 7 0.12 3 0.05
Nepal 28850717 22 0.08 12 0.04
Turkmenistan 5438670 3 0.06 2 0.04
Sri Lanka 20810816 33 0.16 5 0.02
Saudi Arabia 32157974 12 0.04 7 0.02
Oman 4654471 2 0.04 1 0.02
Egypt 93383574 33 0.04 20 0.02
Morocco 34817065 22 0.06 7 0.02
Madagascar 24915822 9 0.04 5 0.02
Bangladesh 162910864 64 0.04 27 0.02
Uzbekistan 30300446 7 0.02 5 0.02
Iraq 37547686 9 0.02 6 0.02
Algeria 40375954 23 0.06 6 0.01
Lao PDR 6918367 5 0.07 1 0.01
Tajikistan 8669464 5 0.06 1 0.01
China 1382323332 283 0.02 127 0.01
Vietnam 94444200 39 0.04 7 0.01
Pakistan 192826502 49 0.03 10 0.01
India 1326801579 185 0.01 61 0.00
Qatar 22913668 2 0.01 1 0.00
Angola 25830958 3 0.01 1 0.00
Afghanistan 33369945 1 0.00 1 0.00
Uganda 40322768 2 0.00 1 0.00
Kenya 47251449 4 0.01 1 0.00
Gibraltar 0 4 0.00 2 0.00
International 0 611 0.00 298 0.00
Jersey 0 5 0.00 4 0.00
Reunion 0 6 0.00 3 0.00
Unknown 0 48 0.00 14 0.00
Guam 172094 5 2.91 0 0.00
Isle of Man 88421 2 2.26 0 0.00
Aruba 104263 1 0.96 0 0.00
Barbados 285006 2 0.70 0 0.00
French Polynesia 275688 1 0.36 0 0.00
Guyana 770910 2 0.26 0 0.00
Namibia 2513981 2 0.08 0 0.00
Libya 6330159 3 0.05 0 0.00
Jamaica 2803362 1 0.04 0 0.00
Cambodia 15827241 2 0.01 0 0.00
Mozambique 28751362 2 0.01 0 0.00
Zambia 16717332 1 0.01 0 0.00
Myanmar 54363426 3 0.01 0 0.00
Ethiopia 101853268 1 0.00 0 0.00

Band Release Activity

I’ve made some attempts to figure out what is going on with band activity and album releases to see if I can figure out why it looks like metal is dying and people aren’t forming new bands.  I’ve also included some interesting plots I thought up on my way.

Just to reiterate the point, here is band formation over time:

Bar_Formation_year

This next plot depicts the number of bands whose first album is before and last album is after the given year.  This is an attempt to show the number of “active” bands in a given year based solely on when they are releasing full-length albums.  What is really telling here is the similar drop-off as you approach the present to band formation.  This is due to the fact that bands don’t release stuff every year, and time between albums can be upwards of a decade in many cases.

Bar_BandRelease_Activity

Next I thought it may be interesting to see the opposing force at work.  How many bands are “inactive” in a given year.  Specifically, this plot shows how many bands in a given year haven’t released an album since before that year.  Keep in mind this graph is showing a compounding effect.  Essentially, as you reach the present you will approach the point at which no one has released anything (because its now).

Bar_BandCount_Inactivity

Almost arriving at an answer I thought to take a look at how many bands had produced their last album (last not here meaning last ever) in a given year.  Interesting to note here is that if I poll the DB I get something south of 40k bands that are listed as “Active”.  In order to arrive at that result we have to add up the bars back to at least 2010 in this graph.  Like I said, a lot of the time there is a large gap between releases (smells like another histogram at some point).

Bar_YearOfLastAlbum

Finally, I think I have an answer.  If I look at when a band releases their first album I get a much more optomistic looking graph.  This shows the continued growth and prosperity one would hope to find.  Maybe things are plateauing a bit as they did in the recession, but that’s better than cratering.  I think this is a much better indicator of bands coming on the market, which is perhaps what we really wanted to know in the first place from “formation” date.

Bar_Bandcount_firstRelease

So what gives?  Why the discrepancy?  Well, if I now make up a histogram showing time difference from “Formation date” and first release, we see that it does take some finite amount of time to produce.  Given that we reach the tail of this time around 5-10 years, this I feel explains rather well the issue.  The shape seems to fit that negative space.

Hist_TimeFromFormationToFirstAlbum

Some other oddities:

  1. Bands depicted as “-10”: bands with no given formation date.  All albums have release dates though, so another point for using that metric instead
  2. Time traveling bands: There are a few bands that actually do have a negative time difference between formation and first album.  I’m assuming this is just user error
  3. Winner?: You may notice the tail of the graph goes pretty far.  Call it dedication, but the prize for longest time between formation and first Full length goes to Orient.

 

 

Troubling

Another project I came across while researching this project had done a decent job of doing some plots very similar to, and in many cases inspiring, things I’ve been plotting.

At some point reading along this posting I saw a plot that seemed to indicate that new band formations are dropping off at an alarming rate from the metal genre.  I had thought maybe there was an error here or perhaps he was looking too broadly at all bands.  Well, I’ve plotted it now as well with only bands that have released Full-lengths and I get a similar result.

Bar_Formation_year

Releases again:

Bar_ReleaseCount_Year

He later goes on to surmise that at least the shear number of bands isn’t dwindling.  But how can it be that the number of releases is linearly increasing each year and the number of new bands is decreasing exponentially?

  1. Delayed response:  it could be that in time we will see a drop off in albums made.  As bands start to split up, with no one to replace them, metal will feel the pain
  2. Market Saturation:  Perhaps the market is so flooded with bands that are still around from the 80’s or even 70’s (remember how I said people just aren’t dying?) new bands are not able to make headway.  We may see releases saturate and band formations re-surge.
  3. Retro Nostalgia:  Bands from 20+ years ago getting back together and releasing new material.  There are a ton of people doing this even outside of metal.  Just look at movies!
  4. Delayed discovery:  Perhaps there is a delay in bands being entered into the MA database.  The graph peaks around 2005, just a few years off of when the website was first created.  This could only be seen over a larger period of time to see if the DB plays catch up.  But if this is the case, there would be WAAAAAAY more releases at an exponential rate.  Given the gradual increase over time contrasted with sharp decay,  I have a feeling this is most likely.

Also of note: there are roughly 5000+ bands with no given formation year.

 

Full-length Releases Over Time

Plotting Full-length releases shows an ever increasing fracas of music coming out each year.

If I squint, maybe I see a few eras:

  1. 1960’s-1980: A handful of releases here and there up to 1980, many of which may have arguable “metal-ness” or are Black Sabbath.
  2. 1980-1985: “Explosion” of metal as NWOHM, Hair Metal, Thrash, Etc. take the stage.
  3. 1985-1990: Things slow down a bit as an era ends
  4. 1990-2002: a period of modest growth, Black/Death metal start growing
  5. 2003-2008: The internets and file sharing shows us what real music sounds like
  6. 2008-2010: Global recession, damn…
  7. 2011-Present: Return to post internet pace

Bar_ReleaseCount_Year.png

Just What Kinds of Releases are in This Thing?

I keep harping on about only doing analysis with Full-length releases, and in case you were wondering just what effect and how numerous the other types are, here you go.

Pie_Releases_Types

Because that’s why.  You see that?  A third of the whole DB is flippin’ DEMOS.

Below is counts of everything in case you’re curious.  I was expecting more live albums to be honest.

Type Count
Demo 104626
Full-length 102746
EP 50091
Single 22178
Split 15060
Compilation 10347
Live album 4909
Video 3082
Boxed set 737
Collaboration 315
Split video 129

 

Test Gif

I made a gif out of some maps.  It is not perfect (white space, you’re killin’ me!), but its something.  The resolution hurts, and I’m sorry for that (just zoom in or open in a new tab, pfft)

Keep in mind this is full-lengths only and non-cumulative.

Webp.net-gifmaker (2)