Sound Tigers

GP: 76 | W: 40 | L: 24 | OTL: 12 | P: 92
GF: 171 | GA: 132 | PP%: 16.76% | PK%: 91.60%
DG: Pascal Labarre | Morale : 52 | Moyenne d'Équipe : 62
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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
1Harry ZolnierczykX100.005337886168949358696256585980725371620
2Chris ConnerX100.005336926164949360686256545986764957620
3Spencer FooX100.005837875972939058625756585769656072610
4Turner ElsonX100.006040795973949358615756585773675862610
5Matthew HighmoreX100.005637886370726861706256585465636271600
6Markus HannikainenX100.007835925977655758525760625971674271600
7Maxim Letunov (R)XXX100.006236905881918657615655585665636271600
8Adam JohnsonX100.005636926069777159576156595569655161590
9Cody McLeodX100.009279495883605656515758545385752572590
10Alex KrushelnyskiX100.005436925370807452545151524877695661560
11Daniel CiampiniX100.006138805670626154555251565768655254550
12Dmitry KulikovX100.007848766278837361306856745277696873670
13Brandon ManningX100.008257706678775264307165705377693624660
14Eric GrybaX100.006841775991846657305653684579715239640
15Nick DeSimoneX100.006237896378928961306256594969656064640
16Aaron NessX100.005237876167949260306751564777696171630
17Evan McEnenyX100.006638855881918757305953584769656271630
18Ryan StantonX100.006340785577928954305552574578705563620
19Joel HanleyX100.005836906070846959305754604675684771610
20Niko MikkolaX100.006537875483939153305251564865636271610
21Nelson NogierX100.005736915779817356305453564565636171600
22Jake Bean (R)X100.005536916175787160305855574761638570600
Rayé
1Radel FazleevX100.005635955473756953555350515265636266550
2Ryan KuffnerX100.005335955276695851575250535465634836540
MOYENNE D'ÉQUIPE100.00624085597582765746585558527267556361
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
1Dustin Tokarski100.00777371757675777675777678844866740
2Harri Sateri100.00747775787372747372747378844365730
Rayé
1Matthew O'Connor100.00716462937069717069717073774620700
2Kevin Lankinen100.00737068777271737271737267715220690
3Eddie Lack100.00666563846564666564666579854220670
MOYENNE D'ÉQUIPE100.0072706881717072717072717580463871
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Todd Richards75808569787371USA525100,000$


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
1Harry ZolnierczykSound Tigers (NYI)LW76213455-3280561412107015610.00%18206327.16515204729200041036155.39%66800000.5313000664
2Aaron NessSound Tigers (NYI)D76143246-84405410498375814.29%109217828.66101020712840220190310.00%000100.4200000234
3Spencer FooSound Tigers (NYI)RW76241943-24151181242013413811.94%14216328.4669153727810132133351.61%15500020.4001001513
4Turner ElsonSound Tigers (NYI)C761627435852510898205531207.80%12181923.94219214427610121394450.62%80400000.4718113234
5Markus HannikainenSound Tigers (NYI)LW76162440-154016280167501009.58%5153120.1551318282050000132049.72%35800000.5216000453
6Joel HanleySound Tigers (NYI)D76112435138058102107445510.28%81205327.038917612690111186300.00%000000.3400000026
7Ryan StantonSound Tigers (NYI)D7662935-18020129769227516.52%88200726.4241115602940111170110.00%000000.3500031101
8Evan McEnenySound Tigers (NYI)D76102131-4400775311235808.93%47139518.361081882319000027010.00%000000.4400000012
9Dmitry KulikovSound Tigers (NYI)D77525301110810142668431495.95%59142418.504711582230111235200.00%000000.4200011042
10Jake BeanSound Tigers (NYI)D736212712160332560183510.00%146478.88471141132000030000.00%000000.8300000201
11Maxim LetunovSound Tigers (NYI)C/LW/RW7662127-846075116141451334.26%6122416.11291126185000011056.17%101300000.4401000010
12Chris ConnerSound Tigers (NYI)RW68131326310024115106359112.26%11119717.61538241651012945155.49%79300000.4304000352
13Matthew HighmoreSound Tigers (NYI)LW7610142411602310914036937.14%6112314.780005231014811056.97%84600000.4300000112
14Radel FazleevSound Tigers (NYI)C6861016-26027456216449.68%5117017.213252528001131034053.28%25900000.2716000121
15Brandon ManningSound Tigers (NYI)D3731013914034132041315.00%183679.93101629000128100.00%000000.7100000112
16Eric GrybaSound Tigers (NYI)D5109971610202110580.00%172424.75011412011030000.00%000000.7400110010
17Adam JohnsonSound Tigers (NYI)C46268280213278157.41%02365.140223260001431053.66%16400000.6800000001
18Nick DeSimoneSound Tigers (NYI)D7215603153044129118.33%206068.420002000006000.00%000000.2000010000
19Daniel CiampiniSound Tigers (NYI)RW65134-30015613377.69%11852.85000122000001085.71%700000.4300000000
20Nelson NogierSound Tigers (NYI)D761230807640425.00%192813.701014210220184000.00%200000.2100000000
21Alex KrushelnyskiSound Tigers (NYI)LW461012002451220.00%2972.1200004000001050.00%200000.2100000000
22Cody McLeodSound Tigers (NYI)LW76000075100010.00%0110.150000100000000.00%000000.0000001000
23Niko MikkolaSound Tigers (NYI)D76000-100101000.00%0120.160000200000000.00%000000.0000000000
24Ryan KuffnerSound Tigers (NYI)LW42000000000000.00%000.010000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1633173349522306868011981361187756112649.22%5522404114.727012519562933514913231888391254.41%507100120.43429277283638
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
1Dustin TokarskiSound Tigers (NYI)764024120.9281.604615121412317120410.567307601246
2Harri SateriSound Tigers (NYI)10001.0000.001400050000.0000070000
Stats d'équipe Total ou en Moyenne774024120.9281.594629121412317170410.5673076701246


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
Aaron NessSound Tigers (NYI)D291990-05-18No184 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Adam JohnsonSound Tigers (NYI)C251994-06-22No174 Lbs6 ft0NoNoNo1Pro & Farm0$0$NoLien
Alex KrushelnyskiSound Tigers (NYI)LW281990-11-14No180 Lbs6 ft0NoNoNo1Pro & Farm0$0$NoLien
Brandon ManningSound Tigers (NYI)D291990-06-04No205 Lbs6 ft1NoNoNo3Pro & Farm1,849,068$0$0$No1,849,068$1,849,068$Lien
Chris ConnerSound Tigers (NYI)RW351983-12-23No181 Lbs5 ft7NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Cody McLeodSound Tigers (NYI)LW351984-06-26No204 Lbs6 ft2NoNoNo3Pro & Farm498,000$0$0$No498,000$498,000$Lien
Daniel CiampiniSound Tigers (NYI)RW281990-11-25No185 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Dmitry KulikovSound Tigers (NYI)D281990-10-29No204 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Dustin TokarskiSound Tigers (NYI)G291989-09-16No204 Lbs6 ft0NoNoNo3Pro & Farm750,000$0$0$No750,000$750,000$Lien
Eddie LackSound Tigers (NYI)G311988-01-05No187 Lbs6 ft4NoNoNo2Pro & Farm499,996$0$0$No499,996$Lien
Eric GrybaSound Tigers (NYI)D311988-04-14No222 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Evan McEnenySound Tigers (NYI)D251994-05-22No203 Lbs6 ft2NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Harri SateriSound Tigers (NYI)G291989-12-29No205 Lbs6 ft1NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Harry ZolnierczykSound Tigers (NYI)LW311987-09-01No180 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Jake BeanSound Tigers (NYI)D211998-06-09Yes186 Lbs6 ft1NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Joel HanleySound Tigers (NYI)D281991-06-08No190 Lbs5 ft11NoNoNo1Pro & Farm300,000$0$0$NoLien
Kevin LankinenSound Tigers (NYI)G241995-04-28No185 Lbs6 ft2NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$Lien
Markus HannikainenSound Tigers (NYI)LW261993-03-26No200 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$NoLien
Matthew HighmoreSound Tigers (NYI)LW231996-02-27No188 Lbs5 ft11NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Matthew O'ConnorSound Tigers (NYI)G271992-02-14No205 Lbs6 ft6NoNoNo1Pro & Farm300,000$0$0$NoLien
Maxim LetunovSound Tigers (NYI)C/LW/RW231996-02-20Yes175 Lbs6 ft4NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Nelson NogierSound Tigers (NYI)D231996-05-27No191 Lbs6 ft2NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Nick DeSimoneSound Tigers (NYI)D241994-11-21No190 Lbs6 ft2NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Niko MikkolaSound Tigers (NYI)D231996-04-27No185 Lbs6 ft4NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Radel FazleevSound Tigers (NYI)C231996-01-07No176 Lbs6 ft1NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Ryan KuffnerSound Tigers (NYI)LW231996-06-12No195 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Ryan StantonSound Tigers (NYI)D291989-07-20No200 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Spencer FooSound Tigers (NYI)RW251994-05-19No190 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Turner ElsonSound Tigers (NYI)C261992-09-13No195 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2926.93192 Lbs6 ft12.45446,450$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Spencer FooMaxim LetunovHarry Zolnierczyk40122
2Turner ElsonMatthew HighmoreMarkus Hannikainen30122
3Spencer FooHarry ZolnierczykTurner Elson20122
4Chris ConnerHarry ZolnierczykSpencer Foo10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joel HanleyRyan Stanton40122
2Evan McEnenyAaron Ness30122
3Aaron NessJoel Hanley20122
4Joel HanleyRyan Stanton10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Maxim LetunovMarkus HannikainenSpencer Foo60122
2Chris ConnerTurner ElsonHarry Zolnierczyk40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Aaron NessJoel Hanley60122
2Ryan StantonEvan McEneny40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Turner ElsonSpencer Foo60122
2Markus HannikainenHarry Zolnierczyk40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joel HanleyRyan Stanton60122
2Aaron NessNelson Nogier40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Harry Zolnierczyk60122Aaron NessEvan McEneny60122
2Spencer Foo40122Joel HanleyRyan Stanton40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Turner ElsonMarkus Hannikainen60122
2Harry ZolnierczykSpencer Foo40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan StantonJoel Hanley60122
2Evan McEnenyAaron Ness40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Turner ElsonHarry ZolnierczykSpencer FooAaron NessJoel Hanley
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Turner ElsonHarry ZolnierczykSpencer FooAaron NessJoel Hanley
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Spencer Foo, Harry Zolnierczyk, Turner ElsonSpencer Foo, Harry ZolnierczykSpencer Foo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Aaron Ness, Ryan Stanton, Joel HanleyJoel HanleyAaron Ness, Joel Hanley
Tirs de Pénalité
Markus Hannikainen, Turner Elson, Maxim Letunov, Harry Zolnierczyk, Spencer Foo
Gardien
#1 : Dustin Tokarski, #2 : Harri Sateri


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
1Americans42101000734211000001102100100062460.7507142102536745987580618577619125405522313.64%19194.74%01271224256.69%1152220152.34%573103455.42%195913861728535947498
2Bears60101202711-43010010125-33000110156-160.500712190053674591605806185776116049389326415.38%18288.89%01271224256.69%1152220152.34%573103455.42%195913861728535947498
3Bruins1247010001622-662301000712-562400000910-1100.417162743035367459248580618577612798410718749612.24%40490.00%11271224256.69%1152220152.34%573103455.42%195913861728535947498
4Checkers8710000043113243100000215164400000022616140.8754382125025367459336580618577611423734129371745.95%14378.57%01271224256.69%1152220152.34%573103455.42%195913861728535947498
5Comets21100000532110000004041010000013-220.500591401536745941580618577614111102414321.43%50100.00%01271224256.69%1152220152.34%573103455.42%195913861728535947498
6Crunch21000001440110000002111000000123-130.7504711005367459375806185776158158329222.22%30100.00%01271224256.69%1152220152.34%573103455.42%195913861728535947498
7Devils22000000624110000002111100000041341.0006101600536745943580618577613614103013215.38%40100.00%01271224256.69%1152220152.34%573103455.42%195913861728535947498
8Marlies2200000012111110000007161100000050541.00012233501536745981580618577612466297114.29%30100.00%01271224256.69%1152220152.34%573103455.42%195913861728535947498
9Penguins8400011214122430000109544100010257-2130.81314223602536745916258061857761165467911854712.96%31293.55%01271224256.69%1152220152.34%573103455.42%195913861728535947498
10Phantoms622000021015-53110000159-43110000156-160.5001018280053674591135806185776114333716531412.90%27292.59%11271224256.69%1152220152.34%573103455.42%195913861728535947498
11Rocket21100000550110000002021010000035-220.500510150153674595258061857761419192914214.29%70100.00%01271224256.69%1152220152.34%573103455.42%195913861728535947498
12Senators22000000725110000003121100000041341.0007121900536745956580618577613812252512325.00%40100.00%01271224256.69%1152220152.34%573103455.42%195913861728535947498
13Thunderbirds1016020011624-8512010011114-350401000510-570.35016324810536745920458061857761253818814140512.50%29389.66%21271224256.69%1152220152.34%573103455.42%195913861728535947498
Total76342405418171132393820110211387632438141303305846915920.6051713144851135367459180558061857761171848762411023766316.76%2382091.60%41271224256.69%1152220152.34%573103455.42%195913861728535947498
15Wolf Pack105400100191725320000011835220010089-1110.5501936550153674591855806185776124765891454848.33%34391.18%01271224256.69%1152220152.34%573103455.42%195913861728535947498
_Since Last GM Reset76342405418171132393820110211387632438141303305846915920.6051713144851135367459180558061857761171848762411023766316.76%2382091.60%41271224256.69%1152220152.34%573103455.42%195913861728535947498
_Vs Conference482014024178385-224127011124142-12487013054243-1570.5948314422706536745910045806185776111263184276952423213.22%1611391.93%21271224256.69%1152220152.34%573103455.42%195913861728535947498
_Vs Division349600102676161753000013330317430010134313210.30967125192175367459765580618577617842322934981532214.38%105892.38%31271224256.69%1152220152.34%573103455.42%195913861728535947498

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7692SOL1171314485180517184876241102113
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7634245418171132
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
38201121138763
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38141333058469
Derniers 10 Matchs
WLOTWOTL SOWSOL
530002
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3766316.76%2382091.60%4
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
580618577615367459
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
1271224256.69%1152220152.34%573103455.42%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
195913861728535947498


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
4 - 2019-09-0513Sound Tigers1Phantoms3LSommaire du Match
5 - 2019-09-0626Sound Tigers1Bears2LXXSommaire du Match
11 - 2019-09-1243Americans1Sound Tigers0LSommaire du Match
12 - 2019-09-1358Americans0Sound Tigers1WSommaire du Match
17 - 2019-09-1869Bruins2Sound Tigers3WSommaire du Match
18 - 2019-09-1988Sound Tigers2Bruins4LSommaire du Match
19 - 2019-09-2096Phantoms2Sound Tigers3WSommaire du Match
25 - 2019-09-26126Sound Tigers2Wolf Pack0WSommaire du Match
26 - 2019-09-27131Sound Tigers4Bruins1WSommaire du Match
31 - 2019-10-02144Sound Tigers1Thunderbirds2LSommaire du Match
32 - 2019-10-03155Thunderbirds1Sound Tigers2WSommaire du Match
33 - 2019-10-04167Penguins1Sound Tigers2WSommaire du Match
36 - 2019-10-07173Devils1Sound Tigers2WSommaire du Match
39 - 2019-10-10194Bruins0Sound Tigers1WSommaire du Match
40 - 2019-10-11205Checkers0Sound Tigers8WSommaire du Match
43 - 2019-10-14215Sound Tigers1Wolf Pack2LXSommaire du Match
45 - 2019-10-16230Sound Tigers3Rocket5LSommaire du Match
46 - 2019-10-17236Sound Tigers4Senators1WSommaire du Match
52 - 2019-10-23264Wolf Pack1Sound Tigers3WSommaire du Match
53 - 2019-10-24285Sound Tigers1Wolf Pack3LSommaire du Match
54 - 2019-10-25291Thunderbirds4Sound Tigers3LXXSommaire du Match
57 - 2019-10-28303Sound Tigers1Thunderbirds3LSommaire du Match
60 - 2019-10-31322Bruins3Sound Tigers1LSommaire du Match
61 - 2019-11-01333Sound Tigers3Thunderbirds2WXSommaire du Match
64 - 2019-11-04340Wolf Pack2Sound Tigers0LSommaire du Match
67 - 2019-11-07362Sound Tigers1Penguins2LXSommaire du Match
73 - 2019-11-13393Sound Tigers1Bruins0WSommaire du Match
74 - 2019-11-14403Thunderbirds4Sound Tigers2LSommaire du Match
75 - 2019-11-15416Penguins2Sound Tigers3WXXSommaire du Match
78 - 2019-11-18428Sound Tigers1Penguins0WSommaire du Match
80 - 2019-11-20435Sound Tigers6Checkers1WSommaire du Match
81 - 2019-11-21454Sound Tigers5Checkers3WSommaire du Match
86 - 2019-11-26471Wolf Pack3Sound Tigers2LSommaire du Match
87 - 2019-11-27480Sound Tigers0Thunderbirds1LSommaire du Match
88 - 2019-11-28487Sound Tigers2Wolf Pack1WSommaire du Match
92 - 2019-12-02512Sound Tigers3Americans2WXSommaire du Match
94 - 2019-12-04518Sound Tigers2Crunch3LXXSommaire du Match
95 - 2019-12-05538Sound Tigers4Devils1WSommaire du Match
101 - 2019-12-11562Sound Tigers1Comets3LSommaire du Match
102 - 2019-12-12576Wolf Pack1Sound Tigers3WSommaire du Match
105 - 2019-12-15594Sound Tigers6Checkers0WSommaire du Match
106 - 2019-12-16595Sound Tigers5Checkers2WSommaire du Match
109 - 2019-12-19620Bruins0Sound Tigers1WXSommaire du Match
110 - 2019-12-20632Bears1Sound Tigers0LSommaire du Match
113 - 2019-12-23645Penguins0Sound Tigers1WSommaire du Match
116 - 2019-12-26671Phantoms5Sound Tigers1LSommaire du Match
122 - 2020-01-01683Phantoms2Sound Tigers1LXXSommaire du Match
123 - 2020-01-02703Sound Tigers1Penguins2LXXSommaire du Match
126 - 2020-01-05712Sound Tigers2Wolf Pack3LSommaire du Match
129 - 2020-01-08724Sound Tigers1Bruins2LSommaire du Match
130 - 2020-01-09736Bruins4Sound Tigers1LSommaire du Match
131 - 2020-01-10748Comets0Sound Tigers4WSommaire du Match
136 - 2020-01-15771Sound Tigers4Phantoms2WSommaire du Match
137 - 2020-01-16780Wolf Pack1Sound Tigers3WSommaire du Match
138 - 2020-01-17794Checkers2Sound Tigers1LSommaire du Match
143 - 2020-01-22821Sound Tigers0Bruins1LSommaire du Match
144 - 2020-01-23831Thunderbirds1Sound Tigers2WXSommaire du Match
145 - 2020-01-24840Bears1Sound Tigers0LXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
151 - 2020-01-30870Sound Tigers2Bears1WXSommaire du Match
152 - 2020-01-31883Sound Tigers0Phantoms1LXXSommaire du Match
157 - 2020-02-05904Sound Tigers3Americans0WSommaire du Match
159 - 2020-02-07927Sound Tigers5Marlies0WSommaire du Match
165 - 2020-02-13956Sound Tigers2Bears3LXSommaire du Match
166 - 2020-02-14969Thunderbirds4Sound Tigers2LSommaire du Match
169 - 2020-02-17977Marlies1Sound Tigers7WSommaire du Match
172 - 2020-02-201002Senators1Sound Tigers3WSommaire du Match
173 - 2020-02-211013Crunch1Sound Tigers2WSommaire du Match
176 - 2020-02-241018Checkers2Sound Tigers7WSommaire du Match
179 - 2020-02-271039Checkers1Sound Tigers5WSommaire du Match
180 - 2020-02-281054Bears3Sound Tigers2LXXSommaire du Match
182 - 2020-03-011058Penguins2Sound Tigers3WSommaire du Match
185 - 2020-03-041075Sound Tigers1Bruins2LSommaire du Match
186 - 2020-03-051087Bruins3Sound Tigers0LSommaire du Match
190 - 2020-03-091107Rocket0Sound Tigers2WSommaire du Match
192 - 2020-03-111120Sound Tigers0Thunderbirds2LSommaire du Match
193 - 2020-03-121134Sound Tigers2Penguins3LXXSommaire du Match



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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
211,547$ 129,471$ 57,880$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 111,535$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 1,183$ 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
1476342405418171132393820110211387632438141303305846915921713144851135367459180558061857761171848762411023766316.76%2382091.60%41271224256.69%1152220152.34%573103455.42%195913861728535947498
Total Saison Régulière76342405418171132393820110211387632438141303305846915921713144851135367459180558061857761171848762411023766316.76%2382091.60%41271224256.69%1152220152.34%573103455.42%195913861728535947498