Sound Tigers

GP: 26 | W: 13 | L: 9 | OTL: 4 | P: 30
GF: 54 | GA: 48 | PP%: 13.22% | PK%: 93.18%
DG: Pascal Labarre | Morale : 48 | Moyenne d'Équipe : 62
Prochain matchs #393 vs Bruins
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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 ZolnierczykX100.005337886168949358696256585980725355620
2Chris ConnerX100.005336926164949360686256545986764955620
3Turner ElsonX100.006040795973949358615756585773675857610
4Spencer FooX100.005837875972939058625756585769656056600
5Markus HannikainenX100.007835925977655758525760625971674255600
6Maxim Letunov (R)XXX100.006236905881918657615655585665636255600
7Matthew HighmoreX100.005637886370726861706256585465636255590
8Cody McLeodX100.009279495883605656515758545385752555580
9Radel FazleevX100.005635955473756953555350515265636255550
10Daniel CiampiniX100.006138805670626154555251565768655255550
11Ryan KuffnerX100.005335955276695851575250535465634851540
12Nick DeSimoneX100.006237896378928961306256594969656052640
13Aaron NessX100.005237876167949260306751564777696155630
14Evan McEnenyX100.006638855881918757305953584769656255630
15Ryan StantonX100.006340785577928954305552574578705552620
16Joel HanleyX100.005836906070846959305754604675684755610
17Niko MikkolaX100.006537875483939153305251564865636255610
18Nelson NogierX100.005736915779817356305453564565636155590
Rayé
MOYENNE D'ÉQUIPE100.00613986587583795748575457527267555560
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 Tokarski100.00777371757675777675777678844855740
2Harri Sateri100.00747775787372747372747378844355730
Rayé
1Matthew O'Connor100.00716462937069717069717073774624700
2Kevin Lankinen100.00737068777271737271737267715224690
3Eddie Lack100.00666563846564666564666579854224670
MOYENNE D'ÉQUIPE100.0072706881717072717072717580463671
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'ÉquipePOS GP 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)LW2661521-260122755234810.91%065525.22268181030001291053.60%12500000.6401000131
2Chris ConnerSound Tigers (NYI)RW267815-180158063184011.11%773628.3223512961012833154.52%66400000.4102000132
3Matt MartinNew York IslandersLW/RW18871524210692842122919.05%538221.261341063000062048.21%39200000.7801101231
4Spencer FooSound Tigers (NYI)RW2695141115354866114013.64%773828.4231413931012802254.24%5900010.3800001201
5Aaron NessSound Tigers (NYI)D2631013-1180183329151410.34%4573728.382132390011074000.00%000100.3500000002
6Turner ElsonSound Tigers (NYI)C2639122161029285616325.36%550619.481561683000051150.54%18600000.4701002101
7Ryan StantonSound Tigers (NYI)D26189-339537252912133.45%3568326.2812320104011057000.00%000000.2600010001
8Markus HannikainenSound Tigers (NYI)LW26538-1240482048183510.42%147318.22011226000001047.17%5300000.3400000020
9Evan McEnenySound Tigers (NYI)D26358-12011428102210.71%62479.5233626121000018000.00%000000.6500000000
10Joel HanleySound Tigers (NYI)D26167-512021352613173.85%3069726.830331284011065000.00%000000.2000000001
11Matthew HighmoreSound Tigers (NYI)LW26336400252011415.00%01746.720002151013310033.33%1800000.6900000000
12Nick DeSimoneSound Tigers (NYI)D2615612352837116109.09%1552320.140002000005000.00%000000.2300010000
13Eric GrybaNew York IslandersD1705559514118430.00%91518.8900036011019000.00%000000.6600010000
14Radel FazleevSound Tigers (NYI)C26235-24010192061710.00%044016.9411281070110492050.00%12000000.2302000100
15Daniel CiampiniSound Tigers (NYI)RW26112-2006480312.50%1813.14000160000010100.00%300000.4900000000
16Maxim LetunovSound Tigers (NYI)C/LW/RW26112-760819209175.00%32067.9400016000000046.77%18600000.1900000000
17Nelson NogierSound Tigers (NYI)D26011120122010.00%71023.9600029011069000.00%200000.1900000000
18Cody McLeodSound Tigers (NYI)LW26000020100000.00%060.250000000000000.00%000000.0000000000
19Niko MikkolaSound Tigers (NYI)D26000000000000.00%000.030000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne4775495149-92244036542553117435510.17%176754715.821629451711022369859713451.16%180800110.390713481110
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)2613940.9251.71157964456010210.7508260501
Stats d'équipe Total ou en Moyenne2613940.9251.71157964456010210.7508260501


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Aaron NessSound Tigers (NYI)D291990-05-18No184 Lbs5 ft10NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Chris ConnerSound Tigers (NYI)RW351983-12-23No181 Lbs5 ft7NoNoNo3Sans RestrictionPro & Farm300,000$0$0$NoLien
Cody McLeodSound Tigers (NYI)LW351984-06-26No204 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm498,000$0$0$NoLien
Daniel CiampiniSound Tigers (NYI)RW281990-11-25No185 Lbs5 ft10NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Dustin TokarskiSound Tigers (NYI)G291989-09-16No204 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm750,000$0$0$NoLien
Eddie LackSound Tigers (NYI)G311988-01-05No187 Lbs6 ft4NoNoNo2Sans RestrictionPro & Farm499,996$0$0$NoLien
Evan McEnenySound Tigers (NYI)D251994-05-22No203 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Harri SateriSound Tigers (NYI)G291989-12-29No205 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm750,000$0$0$NoLien
Harry ZolnierczykSound Tigers (NYI)LW311987-09-01No180 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Joel HanleySound Tigers (NYI)D281991-06-08No190 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Kevin LankinenSound Tigers (NYI)G241995-04-28No185 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Markus HannikainenSound Tigers (NYI)LW261993-03-26No200 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Matthew HighmoreSound Tigers (NYI)LW231996-02-27No188 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Matthew O'ConnorSound Tigers (NYI)G271992-02-14No205 Lbs6 ft6NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Maxim LetunovSound Tigers (NYI)C/LW/RW231996-02-20Yes175 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
Nelson NogierSound Tigers (NYI)D231996-05-27No191 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Nick DeSimoneSound Tigers (NYI)D241994-11-21No190 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Niko MikkolaSound Tigers (NYI)D231996-04-27No185 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Radel FazleevSound Tigers (NYI)C231996-01-07No176 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Ryan KuffnerSound Tigers (NYI)LW231996-06-12No195 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Ryan StantonSound Tigers (NYI)D291989-07-20No200 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Spencer FooSound Tigers (NYI)RW251994-05-19No190 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Turner ElsonSound Tigers (NYI)C261992-09-13No195 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2326.91191 Lbs6 ft12.52399,913$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Spencer FooMaxim LetunovHarry Zolnierczyk40122
2Turner ElsonChris ConnerMarkus Hannikainen30122
3Spencer FooHarry ZolnierczykChris Conner20122
4Radel FazleevChris ConnerSpencer Foo10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joel HanleyRyan Stanton40122
2Nick DeSimoneAaron Ness30122
3Aaron NessJoel Hanley20122
4Joel HanleyRyan Stanton10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris ConnerMarkus HannikainenSpencer Foo60122
2Radel FazleevTurner ElsonHarry Zolnierczyk40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Aaron NessJoel Hanley60122
2Ryan StantonEvan McEneny40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Chris ConnerSpencer Foo60122
2Radel FazleevHarry 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
1Chris Conner60122Aaron NessNick DeSimone60122
2Spencer Foo40122Joel HanleyRyan Stanton40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Chris ConnerRadel Fazleev60122
2Harry ZolnierczykSpencer Foo40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan StantonJoel Hanley60122
2Evan McEnenyAaron Ness40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris ConnerHarry ZolnierczykSpencer FooAaron NessJoel Hanley
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris ConnerHarry ZolnierczykSpencer FooAaron NessJoel Hanley
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Spencer Foo, Chris Conner, Radel FazleevSpencer Foo, Radel FazleevSpencer Foo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Aaron Ness, Ryan Stanton, Joel HanleyJoel HanleyAaron Ness, Joel Hanley
Tirs de Pénalité
Chris Conner, Turner Elson, Radel Fazleev, 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
1Americans21100000110211000001100000000000020.500123011720161441691981831240102228900.00%110100.00%040874554.77%38278648.60%18334752.74%626431628192325164
2Bears1000000112-1000000000001000000112-110.50012300172016127169198183122392156116.67%10100.00%040874554.77%38278648.60%18334752.74%626431628192325164
3Bruins5320000011101321000005502110000065160.6001120310117201611041691981831212339436922418.18%19384.21%140874554.77%38278648.60%18334752.74%626431628192325164
4Checkers11000000808110000008080000000000021.0008152301172016139169198183121154184250.00%20100.00%040874554.77%38278648.60%18334752.74%626431628192325164
5Devils11000000211110000002110000000000021.00023500172016116169198183121574156116.67%10100.00%040874554.77%38278648.60%18334752.74%626431628192325164
6Penguins21000100330110000002111000010012-130.750358001720161341691981831243612291218.33%6183.33%040874554.77%38278648.60%18334752.74%626431628192325164
7Phantoms2110000045-1110000003211010000013-220.500461000172016126169198183124115332113215.38%80100.00%140874554.77%38278648.60%18334752.74%626431628192325164
8Rocket1010000035-2000000000001010000035-200.00036900172016130169198183122558167114.29%40100.00%040874554.77%38278648.60%18334752.74%626431628192325164
9Senators11000000413000000000001100000041321.000461000172016127169198183121636125120.00%20100.00%040874554.77%38278648.60%18334752.74%626431628192325164
10Thunderbirds512010011012-2210000015503020100057-250.500102030101720161112169198183121314039702129.52%140100.00%140874554.77%38278648.60%18334752.74%626431628192325164
Total2612901202544861393000012918111336012012530-5300.5775498152141720161554169198183126021792303681211613.22%88693.18%340874554.77%38278648.60%18334752.74%626431628192325164
12Wolf Pack5220010078-1211000003303110010045-150.5007132001172016195169198183121344057751616.25%20290.00%040874554.77%38278648.60%18334752.74%626431628192325164
_Since Last GM Reset2612901202544861393000012918111336012012530-5300.5775498152141720161554169198183126021792303681211613.22%88693.18%340874554.77%38278648.60%18334752.74%626431628192325164
_Vs Conference179500201323028620000015123933002011718-1210.61832558702172016132916919818312395119157236801113.75%57689.47%240874554.77%38278648.60%18334752.74%626431628192325164
_Vs Division144300100292907310000011110712001001818090.321295483121720161317169198183123359711819564812.50%50394.00%240874554.77%38278648.60%18334752.74%626431628192325164

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2630OTL1549815255460217923036814
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2612912025448
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
139300012918
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
133612012530
Derniers 10 Matchs
WLOTWOTL SOWSOL
251101
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1211613.22%88693.18%3
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
169198183121720161
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
40874554.77%38278648.60%18334752.74%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
626431628192325164


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 Tigers-Bruins-
74 - 2019-11-14403Thunderbirds-Sound Tigers-
75 - 2019-11-15416Penguins-Sound Tigers-
78 - 2019-11-18428Sound Tigers-Penguins-
80 - 2019-11-20435Sound Tigers-Checkers-
81 - 2019-11-21454Sound Tigers-Checkers-
86 - 2019-11-26471Wolf Pack-Sound Tigers-
87 - 2019-11-27480Sound Tigers-Thunderbirds-
88 - 2019-11-28487Sound Tigers-Wolf Pack-
92 - 2019-12-02512Sound Tigers-Americans-
94 - 2019-12-04518Sound Tigers-Crunch-
95 - 2019-12-05538Sound Tigers-Devils-
101 - 2019-12-11562Sound Tigers-Comets-
102 - 2019-12-12576Wolf Pack-Sound Tigers-
105 - 2019-12-15594Sound Tigers-Checkers-
106 - 2019-12-16595Sound Tigers-Checkers-
109 - 2019-12-19620Bruins-Sound Tigers-
110 - 2019-12-20632Bears-Sound Tigers-
113 - 2019-12-23645Penguins-Sound Tigers-
116 - 2019-12-26671Phantoms-Sound Tigers-
122 - 2020-01-01683Phantoms-Sound Tigers-
123 - 2020-01-02703Sound Tigers-Penguins-
126 - 2020-01-05712Sound Tigers-Wolf Pack-
129 - 2020-01-08724Sound Tigers-Bruins-
130 - 2020-01-09736Bruins-Sound Tigers-
131 - 2020-01-10748Comets-Sound Tigers-
136 - 2020-01-15771Sound Tigers-Phantoms-
137 - 2020-01-16780Wolf Pack-Sound Tigers-
138 - 2020-01-17794Checkers-Sound Tigers-
143 - 2020-01-22821Sound Tigers-Bruins-
144 - 2020-01-23831Thunderbirds-Sound Tigers-
145 - 2020-01-24840Bears-Sound Tigers-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
151 - 2020-01-30870Sound Tigers-Bears-
152 - 2020-01-31883Sound Tigers-Phantoms-
157 - 2020-02-05904Sound Tigers-Americans-
159 - 2020-02-07927Sound Tigers-Marlies-
165 - 2020-02-13956Sound Tigers-Bears-
166 - 2020-02-14969Thunderbirds-Sound Tigers-
169 - 2020-02-17977Marlies-Sound Tigers-
172 - 2020-02-201002Senators-Sound Tigers-
173 - 2020-02-211013Crunch-Sound Tigers-
176 - 2020-02-241018Checkers-Sound Tigers-
179 - 2020-02-271039Checkers-Sound Tigers-
180 - 2020-02-281054Bears-Sound Tigers-
182 - 2020-03-011058Penguins-Sound Tigers-
185 - 2020-03-041075Sound Tigers-Bruins-
186 - 2020-03-051087Bruins-Sound Tigers-
190 - 2020-03-091107Rocket-Sound Tigers-
192 - 2020-03-111120Sound Tigers-Thunderbirds-
193 - 2020-03-121134Sound Tigers-Penguins-



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
25 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
73,897$ 91,980$ 42,930$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 36,790$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 990$ 120,780$




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
142612901202544861393000012918111336012012530-5305498152141720161554169198183126021792303681211613.22%88693.18%340874554.77%38278648.60%18334752.74%626431628192325164
Total Saison Régulière2612901202544861393000012918111336012012530-5305498152141720161554169198183126021792303681211613.22%88693.18%340874554.77%38278648.60%18334752.74%626431628192325164