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  Clan Information

Statistics Summary
Clan: TAMBOFF-WOLF
Home Page: tamboff-wolf.ru
Activity: 74.20%
Members: 29 active members (75 total)
Avg. Member Points: 11,661
Total Kills: 347,648
Total Deaths: 298,998
Avg. Kills: 11,988
Kills per Death: 1.16
Kills per Minute: 0.62
Total Connection Time: 388d 20:13:25h
Avg. Connection Time: 13d 09:48:02h
Favorite Server:* ~TAMBOFF-WOLF [NIGHT VIP] PUBLIC NOSTEAM~
Favorite Map:* de_dust2
Favorite Weapon:* Kalashnikov AK-47
Player Locations

  Members

Rank Name Rank Points sort-descending.gif Activity Time Kills Clan Kills % Deaths Kpd
1  Russian federation⋙-☭3,14✖@ЉI4-►㋛™ elorank 33,787 46d 21:12:43h 69,011 19.85% 31,407 2.20
2  Israel«★»GℛΣﮒℍ₦iK«★» elorank 19,346 7d 17:10:25h 10,776 3.10% 5,572 1.93
3  Russian federationdoc76 elorank 18,822 38d 01:42:25h 24,921 7.17% 24,192 1.03
4  Russian federationубивашка 62 elorank 17,280 5d 19:56:38h 7,000 2.01% 4,701 1.49
5  Russian federationSTRELOK elorank 14,649 15d 08:36:59h 11,558 3.32% 10,412 1.11
6  Russian federationDiM4iK elorank 14,639 16d 11:27:36h 19,248 5.54% 12,180 1.58
7  Russian federationKAZANTIP elorank 13,090 50d 00:37:50h 42,148 12.12% 38,705 1.09
8  Russian federationOrel57RUSVOVAN elorank 13,050 5d 02:04:46h 4,277 1.23% 3,263 1.31
9  Russian federationИлья190RUS elorank 12,777 3d 20:42:14h 4,029 1.16% 3,507 1.15
10  PolandПопугайчик Тоша elorank 12,655 2d 02:06:13h 3,109 0.89% 1,465 2.12
11  Russian federationAnapskiy elorank 11,935 19d 05:13:30h 17,550 5.05% 15,207 1.15
12  Russian federationStanislav752 elorank 10,855 15d 16:23:09h 12,956 3.73% 12,340 1.05
13  Ukrainerimuru elorank 10,538 14d 04:56:12h 13,863 3.99% 13,411 1.03
14  Germany«★»Andy«★» elorank 10,521 2d 20:55:52h 2,916 0.84% 2,272 1.28
15  Russian federationубивашка 62 elorank 10,447 22d 05:26:20h 23,507 6.76% 15,929 1.48
16  Russian federationSlovoPetuxa!-KashtanomPoOsvaltu elorank 10,194 3d 14:42:30h 3,449 0.99% 3,630 0.95
17  Russian federationShalfeYka elorank 10,155 2d 02:47:21h 1,861 0.54% 1,855 1.00
18  Russian federationBISON elorank 10,077 8d 16:25:29h 5,721 1.65% 8,611 0.66
19  Russian federationavpvovan elorank 9,850 5d 20:54:08h 4,459 1.28% 5,044 0.88
20  Russian federationSprut elorank 9,466 2d 05:32:07h 1,786 0.51% 2,281 0.78


Page: 1 2




  Player Actions *

Rank Action Achieved Points Bonus sort-descending.gif
1 Plant the Bomb 4,737 times 47,370
2 Pick up the Bomb 22,569 times 45,138
3 Headshot 26,657 times 26,657
4 Domination 3,293 times 16,465
5 Double Kill (2 kills) 10,639 times 10,639
6 Triple Kill (3 kills) 2,550 times 5,100
7 Revenge 1,648 times 4,944
8 Defuse the Bomb 490 times 4,900
9 Domination (4 kills) 446 times 1,338
10 Rampage (5 kills) 47 times 188
11 Mega Kill (6 kills) 4 times 20
12 Rescue a Hostage 1 times 5
13 Touch a Hostage 4 times 0
14 Start Defusing the Bomb Without a Defuse Kit 65 times 0
15 Start Defusing the Bomb With a Defuse Kit 667 times 0
16 Round MVP 16,765 times 0
17 Kill a Hostage 18 times -270
18 Drop the Bomb 12,414 times -24828




  Victims of Player-Player Actions *

Rank Action Times Victimized Points Bonus sort-ascending.gif
1 Domination 2,635 times -13175
2 Revenge 1,930 times -5790




  Team Selection *

Rank Team Joined sort-descending.gif Percentage of Times %
1 Terrorist 3,089 times 28.08%
2 Counter-Terrorist 2,359 times 21.44%




  Weapon Usage *

Rank Weapon Points Modifier Kills sort-descending.gif Percentage of Kills % Headshots Percentage of Headshots % Hpk
1 Kalashnikov AK-47 1.00 18,943 5.45% 9,603 7.29% 0.51
2 Colt M4A1 Carbine 1.00 11,421 3.29% 5,186 3.94% 0.45
3 Desert Eagle .50AE 1.20 6,501 1.87% 3,631 2.76% 0.56
4 Steyr Scout 1.10 5,989 1.72% 3,777 2.87% 0.63
5 High Explosive Grenade 1.80 2,492 0.72% 0 0.00% 0.00
6 Arctic Warfare Magnum (Police) 1.00 2,391 0.69% 397 0.30% 0.17
7 M249 PARA Light Machine Gun 1.20 2,226 0.64% 1,074 0.82% 0.48
8 Bundeswehr Advanced Combat Knife 2.00 1,612 0.46% 2 0.00% 0.00
9 FN P90 1.20 1,560 0.45% 693 0.53% 0.44
10 Sig Sauer P-228 1.50 1,232 0.35% 524 0.40% 0.43
11 Sig Sauer SG-552 Commando 1.00 961 0.28% 427 0.32% 0.44
12 Benelli M3 Super 90 Combat 1.20 639 0.18% 268 0.20% 0.42
13 Dual Beretta 96G Elite 1.40 224 0.06% 102 0.08% 0.46
14 H&K USP .45 Tactical 1.40 136 0.04% 71 0.05% 0.52
15 Galil 1.10 120 0.03% 50 0.04% 0.42
16 Ingram MAC-10 1.50 114 0.03% 55 0.04% 0.48
17 H&K MP5-Navy 1.20 105 0.03% 46 0.03% 0.44
18 Glock 18 Select Fire 1.40 105 0.03% 51 0.04% 0.49
19 Benelli/H&K M4 Super 90 XM1014 1.10 75 0.02% 28 0.02% 0.37
20 Steyr Aug 1.00 73 0.02% 36 0.03% 0.49
21 FN Five-Seven 1.50 63 0.02% 32 0.02% 0.51
22 Steyr Tactical Machine Pistol 1.50 61 0.02% 30 0.02% 0.49
23 Fusil Automatique 1.00 48 0.01% 23 0.02% 0.48
24 H&K UMP45 1.20 34 0.01% 16 0.01% 0.47
25 H&K G3/SG1 Sniper Rifle 0.80 1 0.00% 0 0.00% 0.00




  Weapon Stats *

Rank Weapon Shots Hits Damage Headshots Kills sort-descending.gif Kills per Death Accuracy Damage per Hit Shots per Kill
1 Kalashnikov AK-47 572,143 68,729 2,717,790 10,030 19,471 9.4291 12.0% 39.5 29.4
2 Colt M4A1 Carbine 394,150 50,436 1,605,345 5,183 11,418 11.1613 12.8% 31.8 34.5
3 Desert Eagle .50AE 70,790 18,263 949,672 3,665 6,541 4.3375 25.8% 52.0 10.8
4 Steyr Scout 47,977 14,422 1,379,346 3,770 5,983 2.3780 30.1% 95.6 8.0
5 Arctic Warfare Magnum (Police) 9,974 3,456 464,750 404 2,399 5.0294 34.7% 134.5 4.2
6 M249 PARA Light Machine Gun 116,043 8,599 322,201 1,126 2,284 12.0211 7.4% 37.5 50.8
7 FN P90 77,039 8,821 206,815 693 1,560 10.1961 11.5% 23.4 49.4
8 Sig Sauer P-228 33,362 5,168 159,164 524 1,232 22.4000 15.5% 30.8 27.1
9 Sig Sauer SG-552 Commando 74,004 4,956 143,497 440 977 37.5769 6.7% 29.0 75.7
10 Benelli M3 Super 90 Combat 2,885 5,814 83,850 268 639 2.1515 201.5% 14.4 4.5
11 Bundeswehr Advanced Combat Knife 11,847 1,123 58,043 2 386 1.6856 9.5% 51.7 30.7
12 Dual Beretta 96G Elite 5,633 1,119 30,927 102 224 74.6667 19.9% 27.6 25.1
13 H&K USP .45 Tactical 5,140 933 19,211 70 135 10.3846 18.2% 20.6 38.1
14 Galil 3,416 500 16,691 50 120 60.0000 14.6% 33.4 28.5
15 Ingram MAC-10 4,901 823 14,828 54 111 27.7500 16.8% 18.0 44.2
16 H&K MP5-Navy 4,929 900 15,098 45 103 11.4444 18.3% 16.8 47.9
17 Glock 18 Select Fire 5,215 903 15,870 50 103 6.8667 17.3% 17.6 50.6
18 Benelli/H&K M4 Super 90 XM1014 1,344 924 10,916 28 75 15.0000 68.8% 11.8 17.9
19 Steyr Aug 2,907 396 11,724 37 74 10.5714 13.6% 29.6 39.3
20 FN Five-Seven 1,406 344 9,281 33 64 32.0000 24.5% 27.0 22.0
21 Steyr Tactical Machine Pistol 4,096 508 9,055 29 60 60.0000 12.4% 17.8 68.3
22 Fusil Automatique 1,188 214 6,712 22 46 46.0000 18.0% 31.4 25.8
23 H&K UMP45 2,080 269 5,346 16 33 16.5000 12.9% 19.9 63.0
24 H&K G3/SG1 Sniper Rifle 30 10 1,742 6 7 7.0000 33.3% 174.2 4.3
25 Sig SG-550 Sniper 6 3 301 1 2 2.0000 50.0% 100.3 3.0




  Weapon Targets *

Rank Weapon Hits Left sort-descending.gif Middle Right
1 Arctic Warfare Magnum (Police) 3,456 32.5% 57.6% 9.9%
2 Benelli M3 Super 90 Combat 5,814 29.6% 57.3% 13.1%
3 Sig Sauer SG-552 Commando 4,956 28.8% 55.9% 15.3%
4 Galil 500 28.8% 55.6% 15.6%
5 Sig Sauer P-228 5,168 28.7% 57.7% 13.6%
6 H&K MP5-Navy 900 28.4% 56.8% 14.8%
7 M249 PARA Light Machine Gun 8,599 28.4% 57.0% 14.7%
8 FN P90 8,821 27.9% 56.5% 15.6%
9 Colt M4A1 Carbine 50,436 27.8% 59.2% 13.0%
10 Steyr Aug 396 27.5% 56.8% 15.7%
11 Kalashnikov AK-47 68,729 27.1% 59.1% 13.8%
12 Ingram MAC-10 823 26.7% 58.0% 15.3%
13 Benelli/H&K M4 Super 90 XM1014 924 26.6% 56.9% 16.5%
14 H&K UMP45 269 26.4% 53.5% 20.1%
15 Steyr Scout 14,397 26.4% 65.0% 8.7%
16 Glock 18 Select Fire 903 26.4% 62.3% 11.3%
17 Desert Eagle .50AE 18,263 26.2% 61.6% 12.2%
18 Steyr Tactical Machine Pistol 508 26.0% 63.0% 11.0%
19 Dual Beretta 96G Elite 1,119 24.9% 61.6% 13.5%
20 H&K USP .45 Tactical 933 24.8% 62.5% 12.8%
21 Bundeswehr Advanced Combat Knife 50 24.0% 68.0% 8.0%
22 FN Five-Seven 344 23.3% 62.5% 14.2%
23 Fusil Automatique 214 22.0% 63.6% 14.5%
24 H&K G3/SG1 Sniper Rifle 10 20.0% 80.0% 0.0%
25 Sig SG-550 Sniper 3 0.0% 100.0% 0.0%


Targets
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ERROR
Database Error

Server Address: localhost
Server Username: hlstatsxce

Error Diagnostic:
Bad query.

Server Error: (1052) Column 'map' in order clause is ambiguous

Last SQL Query:
		SELECT *, 
			IFNULL(kills/deaths, '-') AS kpd,
			IFNULL(headshots / kills, '-') AS hpk,
			ROUND(kills / 347648 * 100, 2) AS kpercent,
			ROUND(headshots / 131775 * 100, 2) AS hpercent
		FROM
			tmp_clan_kills, tmp_clan_deaths
		WHERE
			tmp_clan_kills.map = tmp_clan_deaths.map
		ORDER BY
			map desc,
			kills desc