Phantoms

GP: 5 | W: 1 | L: 4 | OTL: 0 | P: 2
GF: 10 | GA: 12 | PP%: 7.14% | PK%: 80.43%
DG: Kriss Cardenas | Morale : 84 | Moyenne d'Équipe : 60
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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
1Chris ThorburnXX100.00875559698180686864656170557476185660
2David BoothXX100.00805571756769706750626662558273185650
3Iiro PakarinenXX100.00825565797975746750626370555656184650
4Tomas HykaX100.00635581726169686450626262555050184610
5Mike BlundenX100.00605569688078716050606060555859185610
6Landon FerraroX100.00685573707064686050596060555354181600
7Adam TambelliniXX100.00665566646561726050585955557372180590
8Bryce Van BrabantXX100.00585558627974635550555557557173184580
9Alex FriesenXX100.00595567606662715550555558557071181570
10Paul BissonnetteX100.00595556618582545550555555556263184570
11Scott KosmachukX100.00605569606863705750565755555050159560
12Marco RoyX100.00725566626963625550555555555050123550
13Oscar Fantenberg (R)X100.00785579757375587525666373557067184680
14Yohann AuvituX100.00705587826474667425656772555353180670
15Matt TennysonX100.00695565717882627125606069557070180660
16Griffin ReinhartX100.00625568798865746225606059557053183640
17Clayton StonerX100.00555555605555795525555555558583177580
18Jakub KindlX100.00555558605858705825585858556970129570
19Cameron GaunceX100.00555555605555655525555555557272135560
Rayé
1Brandon MashinterX100.00565555555758595550555555557574120550
2Rene BourqueXX100.00565555555555555550555555557273120540
3Colin McDonaldX100.00565555555757575550555555557472120540
4Sergey KalininXXX100.00555555555555555550555555555858120530
5Chris CarlisleX100.00555555605555725525555555555353120540
6Andrew CampbellX100.00555555605555735525555555555353120540
7Mattias BackmanX100.00555555605555655525555555555353120540
8Kirill Gotovets (R)X100.00555555605555655525555555555555120540
9Adam ComrieX100.00555555605555595525555555555353120530
10Patrick McNallyX100.00555555605555595525555555555353120530
11Brian Cooper (R)X100.00555555605555585525555555555353120530
MOYENNE D'ÉQUIPE100.0062556264656465593958585955636215358
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
1Peter Budaj100.0080757771807577727577558787131740
2Niklas Svedberg100.0068707370776974787874556060167700
Rayé
1Anthony Stolarz100.0069798687686870646969556566119690
2Mike McKenna100.0064808578656567646963557069120670
MOYENNE D'ÉQUIPE100.007076807773697270737155717113470
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rick Kowalsky70786682735878CAN463100,000$


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
1Tomas HykaPhantoms (Phi)RW5134420181041010.00%05310.640000000000000.00%000001.5000000100
2Alex FriesenPhantoms (Phi)C/LW51234752370114.29%15210.43000000000000100.00%200001.1500001000
3Bryce Van BrabantPhantoms (Phi)C/LW52134606651540.00%16813.62000000000140042.86%4900000.8800000011
4Yohann AuvituPhantoms (Phi)D503301007410780.00%212124.34011930000031000.00%000000.4900000000
5Matt TennysonPhantoms (Phi)D52021100127152813.33%810922.001011031000126000.00%000000.3600000001
6Clayton StonerPhantoms (Phi)D5022280410110.00%16613.250110200006000.00%000000.6000000000
7Chris ThorburnPhantoms (Phi)LW/RW51120401216103810.00%612725.401017320000350053.06%9800000.3100000100
8Landon FerraroPhantoms (Phi)C5022-100085350.00%06913.93022131000030053.85%10400000.5700000000
9Oscar FantenbergPhantoms (Phi)D51120120182102910.00%212124.39101930000029000.00%000000.3300000010
10Adam TambelliniPhantoms (Phi)C/LW5011000664110.00%07815.62011228000010055.88%10200000.2600000000
11David BoothPhantoms (Phi)LW/RW501108010917170.00%110320.730007290000230040.00%2500000.1900000000
12Griffin ReinhartPhantoms (Phi)D50112408183100.00%010621.20000528000026000.00%000000.1900000000
13Iiro PakarinenPhantoms (Phi)LW/RW5101-110066661416.67%110721.540002320000361028.57%700000.1900000000
14Scott KosmachukPhantoms (Phi)RW51011000050120.00%0224.490000000000000.00%200000.8900000000
15Cameron GauncePhantoms (Phi)D50003120702120.00%27114.3900000000015000.00%000000.0000000000
16Paul BissonnettePhantoms (Phi)LW5000140200010.00%0224.48000000000000100.00%100000.0000000000
17Mike BlundenPhantoms (Phi)RW5000020637130.00%110120.300003290000190014.29%700000.0000000000
Stats d'équipe Total ou en Moyenne85101828209951078012136948.26%26140316.523585530900012691050.88%39700000.4000001222
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
1Peter BudajPhantoms (Phi)51400.8952.4229800121140000.000050000
Stats d'équipe Total ou en Moyenne51400.8952.4229800121140000.000050000


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
Adam ComriePhantoms (Phi)D261990-07-30No220 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Adam TambelliniPhantoms (Phi)C/LW221994-11-01No169 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$No
Alex FriesenPhantoms (Phi)C/LW251991-01-29No185 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Andrew CampbellPhantoms (Phi)D281988-02-03No206 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Anthony StolarzPhantoms (Phi)G221994-01-19No210 Lbs6 ft6NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Brandon MashinterPhantoms (Phi)LW281988-09-19No212 Lbs6 ft4NoNoNo4Sans RestrictionPro & Farm500,000$0$0$No
Brian CooperPhantoms (Phi)D231993-10-31Yes197 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Bryce Van BrabantPhantoms (Phi)C/LW251991-11-12No205 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Cameron GauncePhantoms (Phi)D261990-03-19No210 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Chris CarlislePhantoms (Phi)D221994-12-16No174 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Chris ThorburnPhantoms (Phi)LW/RW331983-06-03No235 Lbs6 ft3NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Clayton StonerPhantoms (Phi)D311985-02-19No216 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm925,000$0$0$No
Colin McDonaldPhantoms (Phi)RW321984-09-30No219 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
David BoothPhantoms (Phi)LW/RW321984-11-24No212 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Griffin ReinhartPhantoms (Phi)D221994-01-24No217 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Iiro PakarinenPhantoms (Phi)LW/RW251991-08-25No215 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jakub KindlPhantoms (Phi)D291987-02-10No199 Lbs6 ft3NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Kirill GotovetsPhantoms (Phi)D251991-06-25Yes175 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Landon FerraroPhantoms (Phi)C251991-08-08No186 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Marco RoyPhantoms (Phi)C221994-11-05No183 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Matt TennysonPhantoms (Phi)D261990-04-22No205 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Mattias BackmanPhantoms (Phi)D241992-10-02No181 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Mike BlundenPhantoms (Phi)RW301986-12-14No216 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Mike McKennaPhantoms (Phi)G331983-04-10No190 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm500,000$0$0$No
Niklas SvedbergPhantoms (Phi)G271989-09-03No176 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Oscar FantenbergPhantoms (Phi)D251991-10-07Yes203 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Patrick McNallyPhantoms (Phi)D251991-12-04No181 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Paul BissonnettePhantoms (Phi)LW311985-03-10No216 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Peter BudajPhantoms (Phi)G341982-09-17No192 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm1,920,000$0$0$No
Rene BourquePhantoms (Phi)LW/RW351981-12-09No214 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Scott KosmachukPhantoms (Phi)RW221994-01-23No185 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Sergey KalininPhantoms (Phi)C/LW/RW251991-03-17No190 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No
Tomas HykaPhantoms (Phi)RW231993-03-23No168 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Yohann AuvituPhantoms (Phi)D271989-07-27No198 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3426.76199 Lbs6 ft21.97477,794$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris ThorburnLandon FerraroIiro Pakarinen40122
2David BoothAdam TambelliniMike Blunden30122
3Alex FriesenBryce Van BrabantTomas Hyka20122
4Paul BissonnetteChris ThorburnScott Kosmachuk10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergYohann Auvitu40122
2Matt TennysonGriffin Reinhart30122
3Clayton StonerCameron Gaunce20122
4Oscar FantenbergYohann Auvitu10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris ThorburnLandon FerraroIiro Pakarinen60122
2David BoothAdam TambelliniMike Blunden40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergYohann Auvitu60122
2Matt TennysonGriffin Reinhart40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Chris ThorburnIiro Pakarinen60122
2David BoothMike Blunden40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergYohann Auvitu60122
2Matt TennysonGriffin Reinhart40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Chris Thorburn60122Oscar FantenbergYohann Auvitu60122
2Iiro Pakarinen40122Matt TennysonGriffin Reinhart40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Chris ThorburnIiro Pakarinen60122
2David BoothMike Blunden40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergYohann Auvitu60122
2Matt TennysonGriffin Reinhart40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris ThorburnLandon FerraroIiro PakarinenOscar FantenbergYohann Auvitu
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris ThorburnLandon FerraroIiro PakarinenOscar FantenbergYohann Auvitu
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Tomas Hyka, Bryce Van Brabant, Tomas HykaBryce Van Brabant
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Clayton Stoner, Cameron Gaunce, Matt TennysonClayton StonerCameron Gaunce, Matt Tennyson
Tirs de Pénalité
Chris Thorburn, Iiro Pakarinen, David Booth, Mike Blunden, Tomas Hyka
Gardien
#1 : Peter Budaj, #2 :


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
1Senators514000001012-22020000035-23120000077020.200101828002620121484033011426991074237.14%46980.43%09917257.56%8117546.29%235740.35%11779123405928
Total514000001012-22020000035-23120000077020.200101828002620121484033011426991074237.14%46980.43%09917257.56%8117546.29%235740.35%11779123405928
_Since Last GM Reset514000001012-22020000035-23120000077020.200101828002620121484033011426991074237.14%46980.43%09917257.56%8117546.29%235740.35%11779123405928
_Vs Conference514000001012-22020000035-23120000077020.200101828002620121484033011426991074237.14%46980.43%09917257.56%8117546.29%235740.35%11779123405928
_Vs Division500000001012-22000000035-23000000077000.000101828002620121484033011426991074237.14%46980.43%09917257.56%8117546.29%235740.35%11779123405928

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
52L3101828121114269910700
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
51400001012
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
202000035
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
312000077
Derniers 10 Matchs
WLOTWOTL SOWSOL
140000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4237.14%46980.43%0
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
48403302620
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
9917257.56%8117546.29%235740.35%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11779123405928


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 - 2019-04-063Phantoms2Senators3LSommaire du Match
3 - 2019-04-0811Phantoms5Senators1WSommaire du Match
5 - 2019-04-1019Senators3Phantoms2LSommaire du Match
7 - 2019-04-1227Senators2Phantoms1LSommaire du Match
9 - 2019-04-1435Phantoms0Senators3LSommaire 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
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 162,450$ 121,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 13 0$ 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
13514000001012-22020000035-2312000007702101828002620121484033011426991074237.14%46980.43%09917257.56%8117546.29%235740.35%11779123405928
Total Séries514000001012-22020000035-2312000007702101828002620121484033011426991074237.14%46980.43%09917257.56%8117546.29%235740.35%11779123405928