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Gulls

GP: 79 | W: 55 | L: 18 | OTL: 6 | P: 116
GF: 410 | GA: 193 | PP%: 25.79% | PK%: 82.76%
DG: Olivier | Morale : 50 | Moyenne d'Équipe : 63
Prochain matchs #1241 vs Stars
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Ryan DonatoX100.00543693707377746956676864666564050660
2Sam BennettXX100.00826966707673846977686663686567050660
3Sonny MilanoXX100.00563792687370726652636958726563050640
4Aleksi SaarelaX100.00523593636193916263586355636562050620
5Valentin ZykovXX100.00704078647866596352616258656764050620
6Emil PetterssonX100.00553789607392885967615456576965050610
7Spencer FooX100.00583787597293905862575658576965050610
8Joseph BlandisiX100.00554079597076685862605758556965050600
9Joshua Ho-SangX100.00523691606985695962615758536563050600
10Givani SmithX100.00684275548192895355525456536163050590
11Trent FredericX100.00624579568178685563545657536163050590
12Jan RuttaX100.00583882658379626430726374527769050660
13Olli JuoleviX100.00603594617779716030665158476163065610
14Brendan GuhleX100.00633788607984675930615458466362050600
Rayé
MOYENNE D'ÉQUIPE100.0060408562758175615462595958666405162
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Kaapo Kahkonen100.0078777585777678777678776569050670
2Eric Comrie100.0079696772787779787779786771050660
Rayé
1Vitek Vanecek100.0077787674767577767577766569050650
2Felix Sandstrom100.0074646279737274737274736367050640
3Tyler Parsons100.0071727074706971706971706367050620
MOYENNE D'ÉQUIPE100.007672707775747675747675656905065
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Sam BennettGulls (ANA)C/LW78526812086761034021847913535210.86%17167021.42512174712600081266265.88%157700031.44380028118
2Jan RuttaGulls (ANA)D792589114675001431372036813812.32%133184623.3791322671360111128300.00%000031.2300000448
3Sonny MilanoGulls (ANA)LW/RW7944581028160261144441312909.91%12145718.4541014421280006698259.54%13100031.4024000843
4Ryan DonatoGulls (ANA)C6161391006114108619441212532414.81%23136322.35671327961015986357.49%157600081.47160021055
5Aleksi SaarelaGulls (ANA)LW7928578566160891133211042388.72%8145218.3854920840002355058.78%13100001.1701000343
6Brendan GuhleGulls (ANA)D791461758129513267123439511.38%117166021.01145331200001141400.00%000000.9000001361
7Valentin ZykovGulls (ANA)LW/RW61284573643001501143041062219.21%19128221.0229112810320241156155.59%29500001.1414000464
8Spencer FooGulls (ANA)RW792644708020089742348319111.11%24142218.00145261160000173155.56%14400010.9800000314
9Joshua Ho-SangGulls (ANA)RW7420426250607095263951717.60%19122916.611121554000005057.83%8300001.0100000222
10Emil PetterssonGulls (ANA)C791941606412071151265631937.17%36134216.99000010000185063.89%99700000.8900000033
11Olli JuoleviGulls (ANA)D6794958721201044775394612.00%63152122.71088221140111133000.00%100000.7600000021
12Givani SmithGulls (ANA)LW4919203934155127651294010114.73%2683016.9500000000092157.14%7700000.9400100221
13Joseph BlandisiGulls (ANA)C741021312520323411227818.93%165096.89000130000110060.64%9400011.2200000121
14Trent FredericGulls (ANA)C54279194042716132112.50%163185.90011121000131069.23%1300000.5600000000
Stats d'équipe Total ou en Moyenne992357641998850292301501143033801072246210.56%5291790518.053473107329110832529908541061.32%5119000191.11723105485244
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Kaapo KahkonenGulls (ANA)79551860.9192.36469910818522970410.70634790444
2Eric ComrieGulls (ANA)30000.9661.3092002580000.0000079000
Stats d'équipe Total ou en Moyenne82551860.9212.34479110818723550410.706347979444


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Aleksi SaarelaGulls (ANA)LW211997-01-07No198 Lbs5 ft1NoNoNo2Pro & Farm902,500$0$0$No902,500$Lien / Lien NHL
Brendan GuhleGulls (ANA)D211997-07-29No196 Lbs6 ft2NoNoNo2Pro & Farm888,333$0$0$No888,333$Lien / Lien NHL
Emil PetterssonGulls (ANA)C241994-01-14No164 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Eric ComrieGulls (ANA)G231995-07-06No175 Lbs6 ft1NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Felix SandstromGulls (ANA)G211997-01-12No191 Lbs6 ft2NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien / Lien NHL
Givani SmithGulls (ANA)LW201998-02-27No204 Lbs6 ft2NoNoNo3Pro & Farm913,333$0$0$No913,333$913,333$Lien / Lien NHL
Jan RuttaGulls (ANA)D281990-07-29No200 Lbs6 ft3NoNoNo1Pro & Farm2,300,000$0$0$NoLien / Lien NHL
Joseph BlandisiGulls (ANA)C241994-07-18No187 Lbs5 ft11NoNoNo1Pro & Farm680,000$0$0$NoLien / Lien NHL
Joshua Ho-SangGulls (ANA)RW221996-01-22No173 Lbs6 ft0NoNoNo1Pro & Farm1,075,833$0$0$NoLien / Lien NHL
Kaapo KahkonenGulls (ANA)G221996-08-16No222 Lbs6 ft2NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Olli JuoleviGulls (ANA)D201998-05-05No182 Lbs6 ft2NoNoNo3Pro & Farm1,913,333$0$0$No1,913,333$1,913,333$Lien / Lien NHL
Ryan DonatoGulls (ANA)C221996-04-09No193 Lbs6 ft0NoNoNo1Pro & Farm1,350,000$0$0$NoLien / Lien NHL
Sam BennettGulls (ANA)C/LW221996-06-20No195 Lbs6 ft1NoNoNo1Pro & Farm1,950,000$0$0$NoLien / Lien NHL
Sonny MilanoGulls (ANA)LW/RW221996-05-12No195 Lbs6 ft0NoNoNo1Pro & Farm1,263,333$0$0$NoLien / Lien NHL
Spencer FooGulls (ANA)RW241994-05-19No190 Lbs6 ft0NoNoNo1Pro & Farm1,775,000$0$0$NoLien / Lien NHL
Trent FredericGulls (ANA)C201998-02-11No203 Lbs6 ft2NoNoNo3Pro & Farm1,137,500$0$0$No1,137,500$1,137,500$Lien / Lien NHL
Tyler ParsonsGulls (ANA)G211997-09-18No185 Lbs6 ft1NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Valentin ZykovGulls (ANA)LW/RW231995-05-15No220 Lbs6 ft0NoNoNo2Pro & Farm675,000$0$0$No675,000$Lien / Lien NHL
Vitek VanecekGulls (ANA)G221996-01-09No181 Lbs6 ft1NoNoNo1Pro & Farm863,333$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1922.21192 Lbs6 ft01.681,159,868$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sonny MilanoSam BennettSpencer Foo30122
2Aleksi SaarelaRyan DonatoJoshua Ho-Sang30122
3Givani SmithEmil PetterssonJoseph Blandisi25122
4Sam BennettJoseph BlandisiRyan Donato15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jan RuttaOlli Juolevi30122
2Brendan GuhleTrent Frederic30122
325122
4Jan RuttaOlli Juolevi15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sonny MilanoSam BennettSpencer Foo60122
2Aleksi SaarelaRyan DonatoJoshua Ho-Sang40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jan RuttaOlli Juolevi60122
2Brendan GuhleTrent Frederic40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Sam BennettRyan Donato60122
2Sonny MilanoAleksi Saarela40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jan RuttaOlli Juolevi60122
2Brendan Guhle40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Sam Bennett60122Jan RuttaOlli Juolevi60122
2Ryan Donato40122Brendan Guhle40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Sam BennettRyan Donato60122
2Sonny MilanoAleksi Saarela40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jan RuttaOlli Juolevi60122
2Brendan Guhle40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sonny MilanoSam BennettSpencer FooJan RuttaOlli Juolevi
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sonny MilanoSam BennettSpencer FooJan RuttaOlli Juolevi
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Emil Pettersson, Givani Smith, Spencer FooEmil Pettersson, Givani SmithSpencer Foo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brendan Guhle, Jan Rutta, Olli JuoleviBrendan GuhleJan Rutta, Olli Juolevi
Tirs de Pénalité
Sam Bennett, Ryan Donato, Sonny Milano, Aleksi Saarela, Emil Pettersson
Gardien
#1 : Kaapo Kahkonen, #2 : Eric Comrie


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Admirals33000000175121100000071622000000104661.000173148001841141051218812771301131357801716735240.00%80100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
2Americans21100000770110000004131010000036-320.500711180018411410512731277130113135771201250200.00%60100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
3Barracuda30100101712-52000010157-21010000025-320.33371421001841141051211312771301131357112232467900.00%12283.33%01977321061.59%1414244057.95%824136660.32%234217881525473926500
4Bears2110000056-11010000024-21100000032120.50059140018411410512641277130113135770331655200.00%8275.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
5Bruins2010000124-21010000012-11000000112-110.2502350018411410512731277130113135756211547200.00%5180.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
6Checkers210010001055100010004311100000062441.000101828001841141051289127713011313575714656100.00%220.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
7Comets44000000398312200000020317220000001951481.00039751140018411410512332127713011313579432211086116.67%80100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
8Condors44000000362342200000015015220000002121981.00036641000218411410512357127713011313571021912982150.00%60100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
9Crunch2020000037-41010000024-21010000013-200.00034700184114105126512771301131357752710423133.33%5180.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
10Devils2200000022220110000001211111000000101941.0002241630018411410512165127713011313574011124411100.00%6183.33%01977321061.59%1414244057.95%824136660.32%234217881525473926500
11Eagles31101000871100010004312110000044040.667812200118411410512104127713011313571044318859333.33%8187.50%01977321061.59%1414244057.95%824136660.32%234217881525473926500
12Griffins21100000990110000005321010000046-220.5009152400184114105128312771301131357641918525120.00%9455.56%01977321061.59%1414244057.95%824136660.32%234217881525473926500
13Heat44000000424382200000018315220000002412381.00042741160118411410512351127713011313579926121046466.67%50100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
14IceHogs31100010131301100000043120100010910-140.667132134101841141051297127713011313571033222738450.00%10460.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
15Marlies2020000057-21010000023-11010000034-100.00051015001841141051276127713011313575910447300.00%2150.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
16Monsters21000010725110000004041000001032141.0007815011841141051261127713011313576121843300.00%20100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
17Moose330000002591622000000166101100000093661.0002549740018411410512170127713011313578018155433100.00%50100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
18Penguins2200000018414110000009181100000093641.00018335100184114105121181277130113135772246394250.00%30100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
19Phantoms220000001156110000006331100000052341.0001119300018411410512821277130113135765201254200.00%6183.33%01977321061.59%1414244057.95%824136660.32%234217881525473926500
20Rampage3210000011101110000005322110000067-140.66711213200184114105121121277130113135796358678112.50%40100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
21Reign402010011315-2201010008802010000157-230.3751322350018411410512137127713011313571354689712216.67%4175.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
22Roadrunners42100001101002010000146-22200000064250.62510182800184114105121211277130113135713132127211218.18%5180.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
23Rocket21000010945110000005141000001043141.0009152400184114105121061277130113135748710427114.29%5180.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
24Senators220000001531211000000122101100000031241.00015284300184114105121491277130113135745182454250.00%000.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
25Sound Tigers22000000725110000004041100000032141.000713200118411410512621277130113135746176469111.11%30100.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
26Stars2200000018612110000009361100000093641.000183553001841141051215212771301131357622010385240.00%5180.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
27Thunderbirds210000101147100000104311100000071641.0001119300018411410512111127713011313575915438200.00%2150.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
Total7948180314541019321739238031132088712140251000032202106961160.73441073811481818411410512391412771301131357235669939618311594125.79%1743082.76%11977321061.59%1414244057.95%824136660.32%234217881525473926500
29Wild30300000512-72020000037-41010000025-300.000591400184114105121081277130113135797291666600.00%8275.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
30Wolf Pack220000001129110000007071100000042241.00011223301184114105127312771301131357621914416466.67%70100.00%11977321061.59%1414244057.95%824136660.32%234217881525473926500
31Wolves430000011477210000017342200000074370.87514253901184114105121221277130113135711131478813323.08%15380.00%01977321061.59%1414244057.95%824136660.32%234217881525473926500
_Since Last GM Reset7948180314541019321739238031132088712140251000032202106961160.73441073811481818411410512391412771301131357235669939618311594125.79%1743082.76%11977321061.59%1414244057.95%824136660.32%234217881525473926500
_Vs Conference472711021242351231122313402103114565824147000211216754670.7132354186531618411410512227612771301131357143741124610771052826.67%1061982.08%01977321061.59%1414244057.95%824136660.32%234217881525473926500
_Vs Division201350210397623595202102482622118300001493613340.85097178275111841141051293112771301131357622194105456441534.09%48883.33%01977321061.59%1414244057.95%824136660.32%234217881525473926500

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
79116W5410738114839142356699396183118
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7948183145410193
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
39238311320887
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4025100032202106
Derniers 10 Matchs
WLOTWOTL SOWSOL
730000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1594125.79%1743082.76%1
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
1277130113135718411410512
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
1977321061.59%1414244057.95%824136660.32%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
234217881525473926500


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
2 - 2019-10-0312Roadrunners2Gulls1LSommaire du Match
4 - 2019-10-0528Barracuda3Gulls2LXXSommaire du Match
7 - 2019-10-0840Gulls4Griffins6LSommaire du Match
9 - 2019-10-1050Gulls9Penguins3WSommaire du Match
10 - 2019-10-1159Gulls3Monsters2WXXSommaire du Match
13 - 2019-10-1478Gulls1Bruins2LXXSommaire du Match
15 - 2019-10-1696Americans1Gulls4WSommaire du Match
17 - 2019-10-18112Checkers3Gulls4WXSommaire du Match
19 - 2019-10-20128Heat2Gulls9WSommaire du Match
21 - 2019-10-22138Gulls3Admirals1WSommaire du Match
23 - 2019-10-24152Gulls9Stars3WSommaire du Match
25 - 2019-10-26168Gulls0Eagles4LSommaire du Match
26 - 2019-10-27176Gulls4Wolves3WSommaire du Match
28 - 2019-10-29187Moose3Gulls9WSommaire du Match
31 - 2019-11-01202Comets1Gulls9WSommaire du Match
33 - 2019-11-03219IceHogs3Gulls4WSommaire du Match
35 - 2019-11-05233Wild3Gulls2LSommaire du Match
40 - 2019-11-10269Condors0Gulls8WSommaire du Match
42 - 2019-11-12278Griffins3Gulls5WSommaire du Match
44 - 2019-11-14292Barracuda4Gulls3LXSommaire du Match
46 - 2019-11-16309Gulls2Rampage4LSommaire du Match
48 - 2019-11-18316Gulls3Bears2WSommaire du Match
51 - 2019-11-21334Gulls7Thunderbirds1WSommaire du Match
53 - 2019-11-23355Gulls1Crunch3LSommaire du Match
55 - 2019-11-25372Sound Tigers0Gulls4WSommaire du Match
57 - 2019-11-27386Gulls2Roadrunners1WSommaire du Match
59 - 2019-11-29392Moose3Gulls7WSommaire du Match
62 - 2019-12-02423Reign4Gulls5WXSommaire du Match
66 - 2019-12-06451Bears4Gulls2LSommaire du Match
68 - 2019-12-08463Gulls9Moose3WSommaire du Match
70 - 2019-12-10476Gulls2Wild5LSommaire du Match
72 - 2019-12-12497Reign4Gulls3LSommaire du Match
74 - 2019-12-14503Wolf Pack0Gulls7WSommaire du Match
77 - 2019-12-17528Gulls5Phantoms2WSommaire du Match
78 - 2019-12-18535Gulls10Devils1WSommaire du Match
81 - 2019-12-21553Gulls3Sound Tigers2WSommaire du Match
82 - 2019-12-22565Gulls4Wolf Pack2WSommaire du Match
87 - 2019-12-27591Wolves3Gulls2LXXSommaire du Match
89 - 2019-12-29610Phantoms3Gulls6WSommaire du Match
91 - 2019-12-31615Gulls3Wolves1WSommaire du Match
93 - 2020-01-02636Gulls4Roadrunners3WSommaire du Match
96 - 2020-01-05658Admirals1Gulls7WSommaire du Match
98 - 2020-01-07674Monsters0Gulls4WSommaire du Match
100 - 2020-01-09687Stars3Gulls9WSommaire du Match
102 - 2020-01-11699Gulls5IceHogs4WXXSommaire du Match
104 - 2020-01-13713Gulls4Rampage3WSommaire du Match
107 - 2020-01-16735Gulls7Admirals3WSommaire du Match
108 - 2020-01-17741Gulls6Checkers2WSommaire du Match
118 - 2020-01-27773Gulls2Barracuda5LSommaire du Match
120 - 2020-01-29778Roadrunners4Gulls3LXXSommaire du Match
122 - 2020-01-31791Crunch4Gulls2LSommaire du Match
123 - 2020-02-01804Gulls3Reign4LXXSommaire du Match
126 - 2020-02-04819Gulls3Senators1WSommaire du Match
128 - 2020-02-06828Gulls4Rocket3WXXSommaire du Match
129 - 2020-02-07839Gulls3Marlies4LSommaire du Match
131 - 2020-02-09856Gulls3Americans6LSommaire du Match
133 - 2020-02-11876Rampage3Gulls5WSommaire du Match
135 - 2020-02-13890Heat1Gulls9WSommaire du Match
138 - 2020-02-16909Gulls11Comets2WSommaire du Match
139 - 2020-02-17916Gulls13Heat1WSommaire du Match
141 - 2020-02-19930Thunderbirds3Gulls4WXXSommaire du Match
143 - 2020-02-21947Eagles3Gulls4WXSommaire du Match
145 - 2020-02-23965Wolves0Gulls5WSommaire du Match
147 - 2020-02-25980Condors0Gulls7WSommaire du Match
150 - 2020-02-28998Penguins1Gulls9WSommaire du Match
152 - 2020-03-011015Devils1Gulls12WSommaire du Match
154 - 2020-03-031025Gulls4IceHogs6LSommaire du Match
155 - 2020-03-041031Gulls4Eagles0WSommaire du Match
157 - 2020-03-061048Marlies3Gulls2LSommaire du Match
159 - 2020-03-081063Wild4Gulls1LSommaire du Match
161 - 2020-03-101078Senators2Gulls12WSommaire du Match
165 - 2020-03-141099Gulls2Reign3LSommaire du Match
166 - 2020-03-151112Rocket1Gulls5WSommaire du Match
169 - 2020-03-181136Bruins2Gulls1LSommaire du Match
171 - 2020-03-201151Comets2Gulls11WSommaire du Match
174 - 2020-03-231174Gulls11Condors1WSommaire du Match
176 - 2020-03-251187Gulls11Heat0WSommaire du Match
179 - 2020-03-281215Gulls8Comets3WSommaire du Match
180 - 2020-03-291221Gulls10Condors1WSommaire du Match
183 - 2020-04-011241Stars-Gulls-
185 - 2020-04-031256Reign-Gulls-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
186 - 2020-04-041271Gulls-Barracuda-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,397,680$ 2,203,748$ 2,203,748$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 2,397,680$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 7 11,785$ 82,495$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
Saison Régulière
282244207333216293-7741161802131112140-284182405202104153-49482163675832178785012223275574470351312891481215033295917.93%2965880.41%0924239438.60%1114319034.92%496132437.46%1675111522616421035479
382195301144183316-13341122301131101153-52417300001382163-81381833114943167545772458795784868433951116564215253315416.31%2505179.60%2793241732.81%1135367830.86%423123234.33%14859882502633976429
482363102256212194184123110112312192294113200113391102-1172212370582346965711323837447848277126047991394200254510118.53%6008685.67%51341286246.86%1441326944.08%517118943.48%1977131819756481035516
582125901226181329-148415300020490164-74417290102291165-74241813034843179504982393760779824644181121728318301813217.68%1263373.81%0734222233.03%1005354828.33%387127730.31%147810432574569915391
682442603144334234100412113020321791225741231301112155112438833459693014137999111382212561280126159270582246821312075325.60%1933780.83%32023347958.15%1499278353.86%733131755.66%2196159117505471024539
78243280133432124081412115001131611214041221301221160119418632156688711128108815379111611283132050265873650920242183917.89%2194479.91%32063337461.14%1544281754.81%765134257.00%2231163617175411015535
879481803145410193217392380311320887121402510000322021069611641073811481818411410512391412771301131357235669939618311594125.79%1743082.76%11977321061.59%1414244057.95%824136660.32%234217881525473926500
Total Saison Régulière57122625701813253218571799582851211180971317972879932861051390961215885920-3547218573251510814207425685046820993674869557116395215836352450412846197037919.24%185833981.75%1498551995849.38%91522172542.13%4145904745.82%13387948114307405569293393
Séries
41257000002526-15230000011101734000001416-2102545700168101286758710915413124245315981515.31%971584.54%112140330.02%19051037.25%6816940.24%27017032610616277
6514000001324-1120200000610-431200000714-721320330052511544751421425373281351218.33%13284.62%16817040.00%9022839.47%348540.00%10770147396732
725169000008171101275000003934513940000042375328115123210292624286627727629023912270196729711318.31%951287.37%047695549.84%494106946.21%20340949.63%615420624195334168
Total Séries42222000000119121-2199100000056542231310000006367-444119216335114036394130639941444152157846746911791812916.02%2052985.85%2665152843.52%774180742.83%30566346.00%9936611097342564277