Sound Tigers
GP: 80 | W: 33 | L: 38 | OTL: 9 | P: 75
GF: 323 | GA: 359 | PP%: 21.13% | PK%: 79.27%
DG: François Touzin | Morale : 19 | Moyenne d'Équipe : 63
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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 SPÂgeContratSalaire
1Andrew Shaw (R)X100.007731717577738077727669616967624418710242950,000$
2Brian Ferlin (R)X100.008546787576627369597172696555534231690231400,000$
3James SheppardX100.007127807072727772696378677054492739690272900,000$
4Garret Ross (R)X100.007644767074607576556866586048474235660233950,000$
5James Livingstone (R)X100.005927786774756564737169666247473631660253950,000$
6Jayson Megna (R)X100.008173576481567963656365616159603344650251500,000$
7Borna Rendulic (R)X100.008343686671657368696366616745454439650231850,000$
8Ben Thomson (R)X100.007045615978576769557370565744464739640222550,000$
9Joe Labate (R)X100.006731696868626168676271606444444339640222425,000$
10Ryan Bourque (R)X100.007031766958556365636962576246463528620241400,000$
11Pavel Kraskovsky (R)X100.005724736753585365667162465041416237590191500,000$
12Tyrell Goulbourne (R)X100.007436657270536359455451536145434639580212550,000$
13Brad Ross (R)X100.006138605567526863556555515345453425570231300,000$
14Ben Johnson (R)X100.006537596260576358486357375443434930550211250,000$
15Blake Speers (R)X100.005629614764524954505869385040407425530182500,000$
16David Broll (R)X100.007454604282497548484346304344444125490222275,000$
17Connor Murphy (R)X100.006336807971797571527073716659444830700222600,000$
18Dylan McIlrath (R)X100.008256716284558070476651665251454019680231500,000$
19Julian Melchiori (R)X100.006534747072706967526860716560523420670241300,000$
20Cade FairchildX100.006924747666666566536857735351493119670261500,000$
21Joey Laleggia (R)X100.00644188695857666638695676595146379660232500,000$
22Slater Koekkoek (R)X100.006821866459717265496062685945435127640211550,000$
23Gabriel Carlsson (R)X100.005336866063516455226439754540408014610182500,000$
24Alexander Yelesin (R)X100.006533575058604545195840494441435213530192500,000$
Rayé
MOYENNE D'ÉQUIPE100.00693771656961686454656159584947452863
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
1Leland Irving100.00746977666972746366757355512439690
2Sean Maguire100.00656859585661625859697046453830600
Rayé
1Chris Driedger100.00716069525374626349765343435119600
MOYENNE D'ÉQUIPE100.0070666859596966615873654846382963
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rick Tocchet71647369344958CAN471250,000$


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
1Andrew ShawSound Tigers (NYI)RW614156973600111642777615814.80%26125820.641118294521210141243257.04%2915027011.5437000832
2Brian FerlinSound Tigers (NYI)RW80504191-2152101321182678916918.73%49161720.2217122947267404142853446.28%1217532011.12270021043
3James SheppardSound Tigers (NYI)LW80444488-15440144922458414017.96%29161820.231710274829900071292242.28%1494228001.0928000439
4Zac DalpeIslandersC58285886-75001211442227414912.61%32136123.48722295322601151763352.93%17574121001.2607000563
5Connor MurphySound Tigers (NYI)D80115465-153359615421284745.19%114216027.0051015423350229291130.00%08068100.6001001152
6Garret RossSound Tigers (NYI)LW77233962-13355116741854611412.43%18115014.9461319272170005511251.72%294614111.0813000264
7Jayson MegnaSound Tigers (NYI)C80163753-21511518510781325719.75%35134016.761101152070111901147.79%1377835000.7900102143
8Joe LabateSound Tigers (NYI)C80202747-73609479118377016.95%1498012.25371051080000170046.96%5601915000.9600000004
9Ben ThomsonSound Tigers (NYI)LW80182644178013761139399712.95%1696312.051012250002364041.94%312312000.9100000013
10James LivingstoneSound Tigers (NYI)RW68191736-71404863132456414.39%3085612.593476580000343141.18%343217000.8411000003
11Borna RendulicSound Tigers (NYI)RW80141832-13608755132388510.61%227889.86000010000002047.06%171915010.8112000121
12Julian MelchioriSound Tigers (NYI)D7542630-12600871149429344.26%102157220.96156131740113224100.00%01556000.3800000101
13Ryan BourqueSound Tigers (NYI)C66121426-6200655989275513.48%126449.77000032023533047.80%295166000.8100000020
14Cade FairchildSound Tigers (NYI)D4832023-1439555706023315.00%57100921.0316791490003153000.00%01836000.4600000020
15Joey LaleggiaSound Tigers (NYI)D743172012036915827295.17%80117615.9015631040112142110.00%0931000.3400000010
16Gabriel CarlssonSound Tigers (NYI)D6911516-510023724414322.27%68109615.9001171280221137000.00%0235100.2900000000
17Dylan McIlrathSound Tigers (NYI)D5831114-125010110756922374.35%80139023.97123101730002175000.00%01344000.2000110100
18Pavel KraskovskySound Tigers (NYI)C794913-440289609376.67%33594.5500007000010043.36%11382000.7200000000
19Tyrell GoulbourneSound Tigers (NYI)LW803710-1424063262541912.00%85777.2100000000001060.00%1057000.3500000000
20Slater KoekkoekSound Tigers (NYI)D5714518039563112163.23%3677313.56011036000146100.00%0922000.1300000000
21Brad RossSound Tigers (NYI)LW6523558023692622.22%62103.230111130110790080.00%502000.4800000000
22Alexander YelesinSound Tigers (NYI)D51044-226030227350.00%144899.6000007000017000.00%0012000.1600000000
23Ben JohnsonSound Tigers (NYI)C70000-2401260210.00%01091.56000040000640035.71%4210000.0000000000
24Blake SpeersSound Tigers (NYI)C65000-200530010.00%0390.60000000000260028.57%1400000.0000000000
25David BrollSound Tigers (NYI)LW65000000000000.00%0100.1500000000070050.00%200000.0000000000
Stats d'équipe Total ou en Moyenne1746320547867-15084450184716202556818148012.52%8512355313.497512720232327717916622368301949.64%4847531537340.741036215343938
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
1Leland IrvingSound Tigers (NYI)63202670.8654.313328212391769898320.629355723201
2Sean MaguireSound Tigers (NYI)28111020.8624.2412870091659347210.00001944100
3Chris DriedgerSound Tigers (NYI)52200.8155.24229002010856000.0000413000
Stats d'équipe Total ou en Moyenne96333890.8624.3348452135025361301530.600358080301


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 Salaire RestantCap 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
Alexander YelesinSound Tigers (NYI)D191996-01-01Yes195 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Andrew ShawSound Tigers (NYI)RW241991-01-01Yes179 Lbs5 ft11NoNoNo2Pro & Farm950,000$0$0$No1,100,000$
Ben JohnsonSound Tigers (NYI)C211994-01-01Yes188 Lbs5 ft11NoNoNo1Pro & Farm250,000$0$0$No
Ben ThomsonSound Tigers (NYI)LW221993-01-01Yes205 Lbs6 ft3NoNoNo2Pro & Farm550,000$0$0$No800,000$
Blake SpeersSound Tigers (NYI)C181997-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Borna RendulicSound Tigers (NYI)RW231992-01-01Yes200 Lbs6 ft2NoNoNo1Pro & Farm850,000$0$0$No
Brad RossSound Tigers (NYI)LW231992-01-01Yes175 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$No
Brian FerlinSound Tigers (NYI)RW231992-01-01Yes207 Lbs6 ft2NoNoNo1Pro & Farm400,000$0$0$No
Cade FairchildSound Tigers (NYI)D261989-01-01No186 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Chris DriedgerSound Tigers (NYI)G211994-01-01No187 Lbs6 ft2NoNoNo2Pro & Farm400,000$0$0$No400,000$
Connor MurphySound Tigers (NYI)D221993-01-01Yes212 Lbs6 ft4NoNoNo2Pro & Farm600,000$0$0$No600,000$
David BrollSound Tigers (NYI)LW221993-01-01Yes235 Lbs6 ft2NoNoNo2Pro & Farm275,000$0$0$No275,000$
Dylan McIlrathSound Tigers (NYI)D231992-01-01Yes220 Lbs6 ft5NoNoNo1Pro & Farm500,000$0$0$No
Gabriel CarlssonSound Tigers (NYI)D181997-01-01Yes192 Lbs6 ft5NoNoNo2Pro & Farm500,000$0$0$No500,000$
Garret RossSound Tigers (NYI)LW231992-01-01Yes169 Lbs5 ft11NoNoNo3Pro & Farm950,000$0$0$No950,000$950,000$
James LivingstoneSound Tigers (NYI)RW251990-01-01Yes215 Lbs6 ft1NoNoNo3Pro & Farm950,000$0$0$No950,000$950,000$
James SheppardSound Tigers (NYI)LW271988-01-01No210 Lbs6 ft2NoNoNo2Pro & Farm900,000$0$0$No900,000$
Jayson MegnaSound Tigers (NYI)C251990-01-01Yes195 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
Joe LabateSound Tigers (NYI)C221993-01-01Yes190 Lbs6 ft4NoNoNo2Pro & Farm425,000$0$0$No425,000$
Joey LaleggiaSound Tigers (NYI)D231992-01-01Yes182 Lbs5 ft9NoNoNo2Pro & Farm500,000$0$0$No500,000$
Julian MelchioriSound Tigers (NYI)D241991-01-01Yes190 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$No
Leland IrvingSound Tigers (NYI)G271988-01-01No177 Lbs6 ft0NoNoNo1Pro & Farm800,000$0$0$No
Pavel KraskovskySound Tigers (NYI)C191996-01-01Yes194 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$No
Ryan BourqueSound Tigers (NYI)C241991-01-01Yes185 Lbs5 ft9NoNoNo1Pro & Farm400,000$0$0$No
Sean MaguireSound Tigers (NYI)G221993-01-01No193 Lbs6 ft1NoNoNo2Pro & Farm250,000$0$0$No250,000$
Slater KoekkoekSound Tigers (NYI)D211994-01-01Yes184 Lbs6 ft1NoNoNo1Pro & Farm550,000$0$0$No
Tyrell GoulbourneSound Tigers (NYI)LW211994-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm550,000$0$0$No550,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2722.52194 Lbs6 ft11.63542,593$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1James SheppardJayson MegnaAndrew Shaw40122
2Ben ThomsonJoe LabateBrian Ferlin30122
3Tyrell GoulbourneRyan BourqueJames Livingstone20122
4Brad RossPavel KraskovskyBorna Rendulic10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Connor MurphyDylan McIlrath40122
2Julian MelchioriJoey Laleggia30122
3Gabriel CarlssonAlexander Yelesin20122
4Connor MurphyDylan McIlrath10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1James SheppardJayson MegnaAndrew Shaw60122
2Ben ThomsonJoe LabateBrian Ferlin40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Connor MurphyDylan McIlrath60122
2Julian MelchioriJoey Laleggia40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Andrew ShawBrian Ferlin60122
2James SheppardJames Livingstone40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Connor MurphyDylan McIlrath60122
2Julian MelchioriJoey Laleggia40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Andrew Shaw60122Connor MurphyDylan McIlrath60122
2Brian Ferlin40122Julian MelchioriJoey Laleggia40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Andrew ShawBrian Ferlin60122
2James SheppardJames Livingstone40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Connor MurphyDylan McIlrath60122
2Julian MelchioriJoey Laleggia40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
James SheppardJayson MegnaAndrew ShawConnor MurphyDylan McIlrath
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
James SheppardJayson MegnaAndrew ShawConnor MurphyDylan McIlrath
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ben Johnson, Blake Speers, David BrollBen Johnson, Blake SpeersDavid Broll
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Gabriel Carlsson, Alexander Yelesin, Julian MelchioriGabriel CarlssonAlexander Yelesin, Julian Melchiori
Tirs de Pénalité
Andrew Shaw, Brian Ferlin, James Sheppard, James Livingstone, Jayson Megna
Gardien
#1 : Leland Irving, #2 : Sean Maguire


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
1Admirals31200000916-720200000311-81100000065120.3339142300851201141193835872838471103120671500.00%10370.00%0880175950.03%867179248.38%659129650.85%166989017027831478731
2Barracuda32100000171341010000035-222000000148640.6671730470085120114111108358728384710542286614642.86%14657.14%0880175950.03%867179248.38%659129650.85%166989017027831478731
3Bears65100000251783210000012111330000001367100.83325426701851201141120283587283847144597614521419.05%28678.57%2880175950.03%867179248.38%659129650.85%166989017027831478731
4Checkers2110000078-11010000025-31100000053220.5007121900851201141157835872838476022144110220.00%7185.71%0880175950.03%867179248.38%659129650.85%166989017027831478731
5Comets311001001314-120100100810-21100000054130.5001323360085120114111028358728384710035358510330.00%12375.00%1880175950.03%867179248.38%659129650.85%166989017027831478731
6Condors311000011617-11000000145-1211000001212030.500162743008512011411103835872838479838167611436.36%8187.50%0880175950.03%867179248.38%659129650.85%166989017027831478731
7Crunch320001001613311000000321210001001311250.833163046008512011411111835872838478726275414428.57%11372.73%0880175950.03%867179248.38%659129650.85%166989017027831478731
8Devils220000001183110000007521100000043141.000111728008512011411618358728384767341669800.00%8450.00%0880175950.03%867179248.38%659129650.85%166989017027831478731
9Eagles22000000187111100000085311000000102841.0001833510085120114117283587283847522224558112.50%7271.43%1880175950.03%867179248.38%659129650.85%166989017027831478731
10Griffins30300000817-920200000411-71010000046-200.000813211085120114118783587283847952038551616.25%19478.95%1880175950.03%867179248.38%659129650.85%166989017027831478731
11Heat2010010059-41010000036-31000010023-110.250510150085120114115783587283847761828398337.50%140100.00%0880175950.03%867179248.38%659129650.85%166989017027831478731
12IceHogs615000001727-102110000088040400000919-1020.1671730470085120114111888358728384719061401472314.35%20575.00%1880175950.03%867179248.38%659129650.85%166989017027831478731
13Influenza6300001225187320000011596310000111091100.83325436800851201141118683587283847176477213548918.75%35391.43%1880175950.03%867179248.38%659129650.85%166989017027831478731
14Little Stars21100000910-1110000006511010000035-220.50091524008512011411628358728384776181843400.00%9366.67%0880175950.03%867179248.38%659129650.85%166989017027831478731
15Monsters31200000910-1211000007521010000025-320.33391120008512011411928358728384710730567018422.22%28292.86%0880175950.03%867179248.38%659129650.85%166989017027831478731
16Moose312000001016-620200000815-71100000021120.33310162600851201141190835872838477233467312433.33%23578.26%0880175950.03%867179248.38%659129650.85%166989017027831478731
17Penguins30200010719-121010000027-520100010512-720.333781500851201141177835872838471043356739222.22%18666.67%0880175950.03%867179248.38%659129650.85%166989017027831478731
18Phantoms412000011420-620100001813-52110000067-130.37514233700851201141112783587283847110444110315320.00%18383.33%0880175950.03%867179248.38%659129650.85%166989017027831478731
19Punishers201010008801010000023-11000100065120.50081321008512011411798358728384766251241400.00%6183.33%0880175950.03%867179248.38%659129650.85%166989017027831478731
20Rampage20100010880100000104311010000045-120.50081220008512011411628358728384778271446900.00%7185.71%0880175950.03%867179248.38%659129650.85%166989017027831478731
21Reign623000012126-531100001812-4312000001314-150.417213758108512011411180835872838471917452141321031.25%26580.77%0880175950.03%867179248.38%659129650.85%166989017027831478731
22Rocket412000011918121100000116520100001812-430.3751934530085120114111218358728384712742388221628.57%19478.95%0880175950.03%867179248.38%659129650.85%166989017027831478731
23Senators20200000711-41010000035-21010000046-200.000713200085120114116883587283847681733302150.00%11281.82%0880175950.03%867179248.38%659129650.85%166989017027831478731
24Thunderbirds2110000010100110000006511010000045-120.50010192900851201141164835872838477521204110330.00%10370.00%0880175950.03%867179248.38%659129650.85%166989017027831478731
25Wolfpack303000001419-520200000912-31010000057-200.0001422361085120114111058358728384710532267013430.77%13376.92%0880175950.03%867179248.38%659129650.85%166989017027831478731
Total80293801336323359-3640132100114154184-3040161701222169175-6750.469323547870318512011411255683587283847253985184618473557521.13%3817979.27%7880175950.03%867179248.38%659129650.85%166989017027831478731
_Since Last GM Reset80293801336323359-3640132100114154184-3040161701222169175-6750.469323547870318512011411255683587283847253985184618473557521.13%3817979.27%7880175950.03%867179248.38%659129650.85%166989017027831478731
_Vs Conference50192400016190215-25258130000491111-202511110001299104-5460.460190320510218512011411157983587283847152552152311602465221.14%2484781.05%5880175950.03%867179248.38%659129650.85%166989017027831478731
_Vs Division181040001371611095200002353239520001136297250.69471122193118512011411568835872838475111802004211012322.77%891484.27%3880175950.03%867179248.38%659129650.85%166989017027831478731

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8075OTL132354787025562539851846184731
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8029381336323359
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4013210114154184
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4016171222169175
Derniers 10 Matchs
WLOTWOTL SOWSOL
160201
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3557521.13%3817979.27%7
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
835872838478512011411
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
880175950.03%867179248.38%659129650.85%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
166989017027831478731


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
1 - 2020-10-094Influenza3Sound Tigers5WSommaire du Match
5 - 2020-10-1325Sound Tigers3Influenza2WSommaire du Match
6 - 2020-10-1434Sound Tigers3IceHogs4LSommaire du Match
9 - 2020-10-1745Bears0Sound Tigers4WSommaire du Match
11 - 2020-10-1957Sound Tigers5Bears2WSommaire du Match
13 - 2020-10-2167Reign3Sound Tigers2LXXSommaire du Match
16 - 2020-10-2488Sound Tigers2Reign3LSommaire du Match
17 - 2020-10-2597Reign3Sound Tigers4WSommaire du Match
20 - 2020-10-28109Sound Tigers1IceHogs5LSommaire du Match
23 - 2020-10-31125Bears7Sound Tigers2LSommaire du Match
25 - 2020-11-02136Sound Tigers1Phantoms3LSommaire du Match
27 - 2020-11-04147Monsters4Sound Tigers3LR2Sommaire du Match
29 - 2020-11-06159Sound Tigers2IceHogs4LSommaire du Match
31 - 2020-11-08170Admirals5Sound Tigers2LSommaire du Match
33 - 2020-11-10181Sound Tigers4Bears2WSommaire du Match
35 - 2020-11-12189Sound Tigers9Condors7WSommaire du Match
38 - 2020-11-15205Griffins7Sound Tigers2LR1Sommaire du Match
41 - 2020-11-18222Sound Tigers1Penguins9LR1Sommaire du Match
43 - 2020-11-20232Griffins4Sound Tigers2LSommaire du Match
45 - 2020-11-22247Phantoms6Sound Tigers5LXXSommaire du Match
50 - 2020-11-27270Rocket5Sound Tigers4LSommaire du Match
52 - 2020-11-29278Sound Tigers5Comets4WSommaire du Match
54 - 2020-12-01293Rocket1Sound Tigers7WSommaire du Match
56 - 2020-12-03304Sound Tigers4Influenza3WXXSommaire du Match
58 - 2020-12-05314Sound Tigers6Punishers5WXSommaire du Match
60 - 2020-12-07320Sound Tigers4Devils3WSommaire du Match
61 - 2020-12-08330Admirals6Sound Tigers1LSommaire du Match
64 - 2020-12-11346Sound Tigers3IceHogs6LSommaire du Match
66 - 2020-12-13357Moose9Sound Tigers5LSommaire du Match
68 - 2020-12-15363Sound Tigers4Bears2WSommaire du Match
72 - 2020-12-19384Eagles5Sound Tigers8WSommaire du Match
74 - 2020-12-21394Sound Tigers2Moose1WSommaire du Match
76 - 2020-12-23405Sound Tigers2Heat3LXSommaire du Match
78 - 2020-12-25413Devils5Sound Tigers7WSommaire du Match
82 - 2020-12-29436Influenza5Sound Tigers4LXXSommaire du Match
84 - 2020-12-31444Sound Tigers9Barracuda5WSommaire du Match
86 - 2021-01-02455Sound Tigers6Admirals5WSommaire du Match
88 - 2021-01-04467Rampage3Sound Tigers4WXXSommaire du Match
90 - 2021-01-06477Sound Tigers4Griffins6LR1Sommaire du Match
93 - 2021-01-09491Reign6Sound Tigers2LSommaire du Match
95 - 2021-01-11506Sound Tigers5Reign3WSommaire du Match
97 - 2021-01-13512Sound Tigers10Eagles2WSommaire du Match
98 - 2021-01-14519Punishers3Sound Tigers2LSommaire du Match
101 - 2021-01-17530Sound Tigers3Little Stars5LSommaire du Match
104 - 2021-01-20541Sound Tigers2Monsters5LR2Sommaire du Match
105 - 2021-01-21546Thunderbirds5Sound Tigers6WSommaire du Match
108 - 2021-01-24562Sound Tigers6Reign8LSommaire du Match
110 - 2021-01-26572Penguins7Sound Tigers2LR1Sommaire du Match
112 - 2021-01-28586Sound Tigers5Checkers3WSommaire du Match
114 - 2021-01-30594Sound Tigers4Rampage5LSommaire du Match
115 - 2021-01-31600Bears4Sound Tigers6WSommaire du Match
119 - 2021-02-04623Little Stars5Sound Tigers6WSommaire du Match
123 - 2021-02-08644Sound Tigers3Condors5LSommaire du Match
124 - 2021-02-09649Crunch2Sound Tigers3WSommaire du Match
127 - 2021-02-12669Sound Tigers5Phantoms4WSommaire du Match
129 - 2021-02-14674Monsters1Sound Tigers4WR2Sommaire du Match
131 - 2021-02-16685Sound Tigers4Penguins3WXXSommaire du Match
134 - 2021-02-19700Sound Tigers5Barracuda3WSommaire du Match
135 - 2021-02-20702Moose6Sound Tigers3LSommaire du Match
139 - 2021-02-24726Phantoms7Sound Tigers3LSommaire du Match
141 - 2021-02-26736Sound Tigers3Influenza4LXXSommaire du Match
144 - 2021-03-01753Checkers5Sound Tigers2LSommaire du Match
147 - 2021-03-04766Sound Tigers5Wolfpack7LSommaire du Match
149 - 2021-03-06777IceHogs5Sound Tigers4LSommaire du Match
151 - 2021-03-08786Sound Tigers6Rocket7LXXSommaire du Match
156 - 2021-03-13803Sound Tigers4Senators6LSommaire du Match
157 - 2021-03-14807Influenza1Sound Tigers6WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
161 - 2021-03-18830IceHogs3Sound Tigers4WSommaire du Match
166 - 2021-03-23856Heat6Sound Tigers3LSommaire du Match
169 - 2021-03-26871Sound Tigers2Rocket5LSommaire du Match
171 - 2021-03-28883Senators5Sound Tigers3LSommaire du Match
176 - 2021-04-02907Condors5Sound Tigers4LXXSommaire du Match
180 - 2021-04-06928Comets5Sound Tigers4LXSommaire du Match
186 - 2021-04-12949Comets5Sound Tigers4LSommaire du Match
188 - 2021-04-14965Sound Tigers4Thunderbirds5LSommaire du Match
190 - 2021-04-16974Barracuda5Sound Tigers3LSommaire du Match
194 - 2021-04-20995Sound Tigers6Crunch3WSommaire du Match
195 - 2021-04-211000Wolfpack6Sound Tigers4LSommaire du Match
199 - 2021-04-251023Wolfpack6Sound Tigers5LSommaire du Match
203 - 2021-04-291037Sound Tigers7Crunch8LXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets4020
Assistance54,44827,317
Assistance PCT68.06%68.29%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
0 2044 - 68.14% 71,512$2,860,473$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,735,124$ 1,465,000$ 1,412,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
7,146$ 1,464,015$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 8,366$ 0$




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