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  Clan Information

Statistics Summary
Clan: TAMBOFF-WOLF
Home Page: tamboff-wolf.ru
Activity: 74.55%
Members: 29 active members (75 total)
Avg. Member Points: 11,662
Total Kills: 347,466
Total Deaths: 298,839
Avg. Kills: 11,982
Kills per Death: 1.16
Kills per Minute: 0.62
Total Connection Time: 388d 15:20:40h
Avg. Connection Time: 13d 09:37:57h
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 19.86% 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 17,454 5d 17:37:59h 6,872 1.98% 4,611 1.49
5  Russian federationSTRELOK elorank 14,649 15d 08:36:59h 11,558 3.33% 10,412 1.11
6  Russian federationDiM4iK elorank 14,639 16d 11:27:36h 19,248 5.54% 12,180 1.58
7  Russian federationOrel57RUSVOVAN elorank 13,050 5d 02:04:46h 4,277 1.23% 3,263 1.31
8  Russian federationKAZANTIP elorank 13,013 50d 00:05:11h 42,123 12.12% 38,689 1.09
9  Russian federationИлья190RUS elorank 12,780 3d 20:39:35h 4,029 1.16% 3,506 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 10,877 15d 15:15:18h 12,951 3.73% 12,314 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 6.77% 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 9,997 8d 15:34:32h 5,697 1.64% 8,585 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 sort-ascending.gif Points Bonus
1 Rescue a Hostage 1 times 5
2 Mega Kill (6 kills) 4 times 20
3 Touch a Hostage 4 times 0
4 Kill a Hostage 18 times -270
5 Rampage (5 kills) 48 times 192
6 Start Defusing the Bomb Without a Defuse Kit 67 times 0
7 Domination (4 kills) 446 times 1,338
8 Defuse the Bomb 498 times 4,980
9 Start Defusing the Bomb With a Defuse Kit 678 times 0
10 Revenge 1,650 times 4,950
11 Triple Kill (3 kills) 2,554 times 5,108
12 Domination 3,293 times 16,465
13 Plant the Bomb 4,733 times 47,330
14 Double Kill (2 kills) 10,653 times 10,653
15 Drop the Bomb 12,457 times -24914
16 Round MVP 16,818 times 0
17 Pick up the Bomb 22,599 times 45,198
18 Headshot 26,680 times 26,680




  Victims of Player-Player Actions *

Rank Action Times Victimized sort-descending.gif Points Bonus
1 Domination 2,646 times -13230
2 Revenge 1,932 times -5796




  Team Selection *

Rank Team sort-descending.gif Joined Percentage of Times %
1 Terrorist 3,101 times 28.01%
2 Counter-Terrorist 2,375 times 21.45%




  Weapon Usage *

Rank Weapon Points Modifier Kills sort-descending.gif Percentage of Kills % Headshots Percentage of Headshots % Hpk
1 Kalashnikov AK-47 1.00 18,977 5.46% 9,613 7.30% 0.51
2 Colt M4A1 Carbine 1.00 11,540 3.32% 5,213 3.96% 0.45
3 Desert Eagle .50AE 1.20 6,505 1.87% 3,633 2.76% 0.56
4 Steyr Scout 1.10 5,945 1.71% 3,742 2.84% 0.63
5 High Explosive Grenade 1.80 2,488 0.72% 0 0.00% 0.00
6 Arctic Warfare Magnum (Police) 1.00 2,407 0.69% 401 0.30% 0.17
7 M249 PARA Light Machine Gun 1.20 2,239 0.64% 1,080 0.82% 0.48
8 Bundeswehr Advanced Combat Knife 2.00 1,631 0.47% 2 0.00% 0.00
9 FN P90 1.20 1,562 0.45% 694 0.53% 0.44
10 Sig Sauer P-228 1.50 1,243 0.36% 529 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 1.20 640 0.18% 269 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 1.50 117 0.03% 57 0.04% 0.49
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 59 0.02% 30 0.02% 0.51
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-47 572,668 68,848 2,722,522 10,041 19,506 9.4050 12.0% 39.5 29.4
2 Colt M4A1 Carbine 403,238 51,028 1,621,079 5,210 11,537 11.1254 12.7% 31.8 35.0
3 Desert Eagle .50AE 70,742 18,264 950,174 3,667 6,545 4.3662 25.8% 52.0 10.8
4 Steyr Scout 47,733 14,347 1,370,083 3,735 5,939 2.3794 30.1% 95.5 8.0
5 Arctic Warfare Magnum (Police) 10,011 3,474 467,780 408 2,415 5.0735 34.7% 134.7 4.1
6 M249 PARA Light Machine Gun 116,378 8,655 324,385 1,132 2,297 12.0895 7.4% 37.5 50.7
7 FN P90 77,064 8,833 207,064 694 1,562 10.2092 11.5% 23.4 49.3
8 Sig Sauer P-228 33,592 5,203 160,260 529 1,243 22.6000 15.5% 30.8 27.0
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 2,890 5,817 83,982 269 640 2.1405 201.3% 14.4 4.5
11 Bundeswehr Advanced Combat Knife 11,951 1,134 58,982 2 391 1.6926 9.5% 52.0 30.6
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 5,162 942 19,343 70 135 10.3846 18.2% 20.5 38.2
14 Galil 3,416 500 16,691 50 120 60.0000 14.6% 33.4 28.5
15 Ingram MAC-10 5,006 839 15,200 56 114 28.5000 16.8% 18.1 43.9
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 5,240 905 15,932 50 103 6.8667 17.3% 17.6 50.9
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 4,010 502 8,977 29 58 58.0000 12.5% 17.9 69.1
22 Fusil Automatique 1,191 214 6,712 22 46 46.0000 18.0% 31.4 25.9
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 Middle Right sort-descending.gif
1 H&K UMP45 269 26.4% 53.5% 20.1%
2 Benelli/H&K M4 Super 90 XM1014 924 26.6% 56.9% 16.5%
3 Steyr Aug 396 27.5% 56.8% 15.7%
4 FN P90 8,833 27.9% 56.5% 15.6%
5 Galil 500 28.8% 55.6% 15.6%
6 Sig Sauer SG-552 Commando 4,956 28.8% 55.9% 15.3%
7 Ingram MAC-10 839 26.3% 58.4% 15.3%
8 H&K MP5-Navy 900 28.4% 56.8% 14.8%
9 M249 PARA Light Machine Gun 8,655 28.4% 57.0% 14.6%
10 Fusil Automatique 214 22.0% 63.6% 14.5%
11 FN Five-Seven 344 23.3% 62.5% 14.2%
12 Kalashnikov AK-47 68,848 27.1% 59.1% 13.8%
13 Sig Sauer P-228 5,203 28.6% 57.7% 13.7%
14 Dual Beretta 96G Elite 1,119 24.9% 61.6% 13.5%
15 Benelli M3 Super 90 Combat 5,817 29.6% 57.3% 13.1%
16 Colt M4A1 Carbine 51,028 27.8% 59.1% 13.0%
17 H&K USP .45 Tactical 942 24.8% 62.4% 12.7%
18 Desert Eagle .50AE 18,264 26.2% 61.7% 12.2%
19 Glock 18 Select Fire 905 26.4% 62.3% 11.3%
20 Steyr Tactical Machine Pistol 502 25.7% 63.1% 11.2%
21 Arctic Warfare Magnum (Police) 3,474 32.5% 57.7% 9.8%
22 Steyr Scout 14,322 26.4% 64.9% 8.7%
23 Bundeswehr Advanced Combat Knife 50 24.0% 68.0% 8.0%
24 Sig SG-550 Sniper 3 0.0% 100.0% 0.0%
25 H&K G3/SG1 Sniper Rifle 10 20.0% 80.0% 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 / 347466 * 100, 2) AS kpercent,
			ROUND(headshots / 131665 * 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