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  Clan Information

Statistics Summary
Clan: TAMBOFF-WOLF
Home Page: tamboff-wolf.ru
Activity: 73.89%
Members: 29 active members (75 total)
Avg. Member Points: 11,668
Total Kills: 347,556
Total Deaths: 298,888
Avg. Kills: 11,985
Kills per Death: 1.16
Kills per Minute: 0.62
Total Connection Time: 388d 16:45:36h
Avg. Connection Time: 13d 09:40:52h
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 17,615 5d 18:56:36h 6,962 2.00% 4,660 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 15:21:37h 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 6.76% 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 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 sort-descending.gif Achieved Points Bonus
1 Triple Kill (3 kills) 2,546 times 5,092
2 Touch a Hostage 4 times 0
3 Start Defusing the Bomb Without a Defuse Kit 65 times 0
4 Start Defusing the Bomb With a Defuse Kit 667 times 0
5 Round MVP 16,747 times 0
6 Revenge 1,642 times 4,926
7 Rescue a Hostage 1 times 5
8 Rampage (5 kills) 47 times 188
9 Plant the Bomb 4,732 times 47,320
10 Pick up the Bomb 22,537 times 45,074
11 Mega Kill (6 kills) 4 times 20
12 Kill a Hostage 18 times -270
13 Headshot 26,603 times 26,603
14 Drop the Bomb 12,398 times -24796
15 Double Kill (2 kills) 10,620 times 10,620
16 Domination (4 kills) 445 times 1,335
17 Domination 3,288 times 16,440
18 Defuse the Bomb 490 times 4,900




  Victims of Player-Player Actions *

Rank Action Times Victimized Points Bonus sort-descending.gif
1 Revenge 1,928 times -5784
2 Domination 2,628 times -13140




  Team Selection *

Rank Team Joined sort-descending.gif Percentage of Times %
1 Terrorist 3,083 times 28.09%
2 Counter-Terrorist 2,354 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 18,917 5.44% 9,588 7.28% 0.51
2 Colt M4A1 Carbine 1.00 11,407 3.28% 5,178 3.93% 0.45
3 Desert Eagle .50AE 1.20 6,493 1.87% 3,625 2.75% 0.56
4 Steyr Scout 1.10 5,959 1.71% 3,756 2.85% 0.63
5 High Explosive Grenade 1.80 2,487 0.72% 0 0.00% 0.00
6 Arctic Warfare Magnum (Police) 1.00 2,385 0.69% 394 0.30% 0.17
7 M249 PARA Light Machine Gun 1.20 2,225 0.64% 1,073 0.81% 0.48
8 Bundeswehr Advanced Combat Knife 2.00 1,611 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 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-47 569,134 68,619 2,714,020 10,016 19,446 9.4306 12.1% 39.6 29.3
2 Colt M4A1 Carbine 393,319 50,337 1,602,411 5,175 11,404 11.1476 12.8% 31.8 34.5
3 Desert Eagle .50AE 70,614 18,243 948,351 3,659 6,533 4.3553 25.8% 52.0 10.8
4 Steyr Scout 47,798 14,368 1,373,306 3,749 5,953 2.3822 30.1% 95.6 8.0
5 Arctic Warfare Magnum (Police) 9,953 3,449 463,213 401 2,393 5.0379 34.7% 134.3 4.2
6 M249 PARA Light Machine Gun 115,947 8,597 322,121 1,125 2,283 12.0158 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 11,846 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 5,188 903 15,870 50 103 6.8667 17.4% 17.6 50.4
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 1,188 214 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 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 8,821 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-10 823 26.7% 58.0% 15.3%
8 H&K MP5-Navy 900 28.4% 56.8% 14.8%
9 M249 PARA Light Machine Gun 8,597 28.4% 57.0% 14.7%
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 68,619 27.1% 59.1% 13.8%
13 Sig Sauer P-228 5,168 28.7% 57.7% 13.6%
14 Dual Beretta 96G Elite 1,119 24.9% 61.6% 13.5%
15 Benelli M3 Super 90 Combat 5,814 29.6% 57.3% 13.1%
16 Colt M4A1 Carbine 50,337 27.8% 59.2% 13.0%
17 H&K USP .45 Tactical 933 24.8% 62.5% 12.8%
18 Desert Eagle .50AE 18,243 26.2% 61.6% 12.2%
19 Glock 18 Select Fire 903 26.4% 62.3% 11.3%
20 Steyr Tactical Machine Pistol 502 25.7% 63.1% 11.2%
21 Arctic Warfare Magnum (Police) 3,449 32.6% 57.6% 9.8%
22 Steyr Scout 14,343 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 / 347556 * 100, 2) AS kpercent,
			ROUND(headshots / 131722 * 100, 2) AS hpercent
		FROM
			tmp_clan_kills, tmp_clan_deaths
		WHERE
			tmp_clan_kills.map = tmp_clan_deaths.map
		ORDER BY
			map asc,
			kills asc