Condors

GP: 22 | W: 10 | L: 10 | OTL: 2 | P: 22
GF: 70 | GA: 81 | PP%: 22.73% | PK%: 77.65%
DG: Jonathan Legault | Morale : 49 | Moyenne d'Équipe : 61
Prochain matchs #413 vs Heat
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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
1Mitchell StephensX100.005935936273807461656059586063626352600
2Ryan GroppX100.006436916081928858595654575565636248600
3Alexandre AlainX100.005937885876949357615652555463626360590
4Nicholas Caamano (R)X100.006441775579949354565353565461636460590
5Carter BancksX100.005338855469939153565351524878795557580
6Brian Pinho (R)X100.005635945469949353605251544867646160580
7Matthew Phillips (R)X100.005035955957928958655954515661636460580
8Matheson IacopelliX100.006838855582787254535151555269656054570
9Hudson Elynuik (R)X100.006339775685716254655653575261636660570
10Drake Rymsha (R)X100.005742755572787254625351545261636460560
11Chris BigrasX100.006138855776908456305951564667647654610
12Mitchell Vande SompelX100.006436776070787359306257615563587360610
13Jake CheliosX100.005936925877897057305553604575684754610
14Trevor CarrickX100.005847746180827260305954584669655761610
15Parker WotherspoonX100.005339835669928955305652534663626354590
Rayé
MOYENNE D'ÉQUIPE100.00593885577486815650565356516664635759
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
1John Muse100.00786664697776787776787779854260730
2Mike Condon100.00746563797373747373747377834460720
Rayé
1Joey Daccord (R)100.00636361806261636261636265695930630
MOYENNE D'ÉQUIPE100.0072656376717072717072717479485069
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Stevens78777179787371CAN5252,100,000$


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
1Chris BigrasCondors (Edm)D22111728-3320603570203715.71%4954124.606394877000054200.00%000001.0300000212
2Jake CheliosCondors (Edm)D2251520-332054377218466.94%3648922.2746104063000144010.00%100000.8200000101
3Matheson IacopelliCondors (Edm)LW227613-4180512662134011.29%536116.431343290001102057.92%25900000.7200000110
4Carter BancksCondors (Edm)RW225611-425526225815488.62%843819.951127290000110056.41%3900000.5000100110
5Ryan GroppCondors (Edm)LW168311-3100221756173714.29%51489.2600000000001046.67%1500001.4900000102
6Parker WotherspoonCondors (Edm)D2201111-62604434246180.00%3032114.600001600004000.00%000000.6900000001
7Mitchell Vande SompelCondors (Edm)D6268420106112718.18%514323.90235924000011000.00%000001.1200000110
8Brian PinhoCondors (Edm)C64485007101941121.05%211619.44101426000000067.92%10600001.3700000100
9Matthew PhillipsCondors (Edm)RW6538700862651119.23%115826.33101325000062063.16%1900001.0100000102
10Nicholas CaamanoCondors (Edm)RW6268410019112031010.00%216227.121233230001100064.29%1400000.9800000010
11Alexandre AlainCondors (Edm)C63363003112172614.29%117328.930113230000151067.74%15500000.6900000020
12Trevor CarrickCondors (Edm)D6246675711186611.11%914924.961121223000010110.00%000000.8000001001
13Hudson ElynuikCondors (Edm)C623550088156913.33%28113.6400004000030067.14%7000001.2200000100
14Drake RymshaCondors (Edm)C61124002512288.33%06811.4600012000000069.09%5500000.5800000000
Stats d'équipe Total ou en Moyenne1745788145151621032123948412431411.78%155335519.2818203813435900031839263.03%73300000.86001011079
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
1John MuseCondors (Edm)65010.9351.493620191380000.000060011
Stats d'équipe Total ou en Moyenne65010.9351.493620191380000.000060011


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
Alexandre AlainCondors (Edm)C221997-03-03No180 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Brian PinhoCondors (Edm)C241995-05-11Yes173 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Carter BancksCondors (Edm)RW291989-08-09No181 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm300,000$0$0$NoLien
Chris BigrasCondors (Edm)D241995-02-22No191 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Drake RymshaCondors (Edm)C201998-08-18Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Hudson ElynuikCondors (Edm)C211997-10-12Yes194 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Jake CheliosCondors (Edm)D281991-03-08No185 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Joey DaccordCondors (Edm)G221996-08-19Yes197 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
John MuseCondors (Edm)G301988-08-01No185 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Matheson IacopelliCondors (Edm)LW251994-05-15No207 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Matthew PhillipsCondors (Edm)RW211998-04-06Yes140 Lbs5 ft7NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Mike CondonCondors (Edm)G291990-04-27No195 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Mitchell StephensCondors (Edm)C221997-02-05No191 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Mitchell Vande SompelCondors (Edm)D221997-02-11No194 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Nicholas CaamanoCondors (Edm)RW201998-09-07Yes195 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Parker WotherspoonCondors (Edm)D211997-08-24No171 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Ryan GroppCondors (Edm)LW221996-09-16No187 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Trevor CarrickCondors (Edm)D241994-07-04No196 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1823.67186 Lbs6 ft13.00450,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matheson IacopelliAlexandre AlainNicholas Caamano40122
2Carter BancksBrian PinhoMatthew Phillips30122
3Alexandre AlainHudson ElynuikCarter Bancks20122
4Nicholas CaamanoDrake RymshaMatthew Phillips10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake CheliosMitchell Vande Sompel40122
2Trevor CarrickChris Bigras30122
3Parker WotherspoonJake Chelios20122
4Mitchell Vande SompelTrevor Carrick10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matheson IacopelliAlexandre AlainNicholas Caamano60122
2Carter BancksBrian PinhoMatthew Phillips40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake CheliosMitchell Vande Sompel60122
2Trevor CarrickChris Bigras40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Alexandre AlainNicholas Caamano60122
2Matthew PhillipsCarter Bancks40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake CheliosMitchell Vande Sompel60122
2Trevor CarrickChris Bigras40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Alexandre Alain60122Jake CheliosMitchell Vande Sompel60122
2Nicholas Caamano40122Trevor CarrickChris Bigras40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Alexandre AlainNicholas Caamano60122
2Matthew PhillipsCarter Bancks40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake CheliosMitchell Vande Sompel60122
2Trevor CarrickChris Bigras40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matheson IacopelliAlexandre AlainNicholas CaamanoJake CheliosMitchell Vande Sompel
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matheson IacopelliAlexandre AlainNicholas CaamanoJake CheliosMitchell Vande Sompel
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Hudson Elynuik, Drake Rymsha, Matheson IacopelliHudson Elynuik, Drake RymshaMatheson Iacopelli
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Parker Wotherspoon, Chris Bigras, Jake CheliosParker WotherspoonChris Bigras, Jake Chelios
Tirs de Pénalité
Alexandre Alain, Nicholas Caamano, Matthew Phillips, Carter Bancks, Matheson Iacopelli
Gardien
#1 : John Muse, #2 : Mike Condon


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
1Barracuda42200000911-22110000056-12110000045-140.50091524002319271882092232331114937326919210.53%15193.33%029862847.45%28767342.64%17334949.57%544398530147255127
2Eagles2100100011652100100011650000000000041.00011182900231927112320922323311491817469222.22%40100.00%029862847.45%28767342.64%17334949.57%544398530147255127
3Gulls31100100911-21000010023-12110000078-130.5009162500231927196209223233118017185010110.00%9366.67%029862847.45%28767342.64%17334949.57%544398530147255127
4Heat31200000612-62110000058-31010000014-320.3336111700231927171209223233111103826649333.33%13376.92%029862847.45%28767342.64%17334949.57%544398530147255127
5Moose2200000012482200000012480000000000041.00012243600231927179209223233114617144210220.00%6183.33%029862847.45%28767342.64%17334949.57%544398530147255127
6Rampage1010000037-41010000037-40000000000000.00036900231927117209223233115411121622100.00%6266.67%029862847.45%28767342.64%17334949.57%544398530147255127
7Reign220000001138110000005051100000063341.000112233012319271872092232331150919399555.56%60100.00%029862847.45%28767342.64%17334949.57%544398530147255127
8Roadrunners20100001710-320100001710-30000000000010.2507132000231927160209223233117624184111218.18%9366.67%029862847.45%28767342.64%17334949.57%544398530147255127
9Stars1010000015-41010000015-40000000000000.00012300231927125209223233114910619300.00%3166.67%029862847.45%28767342.64%17334949.57%544398530147255127
Total22910011017081-1114650110151492835000001932-13220.5007012819801231927167420922323311739205190418882022.73%851977.65%029862847.45%28767342.64%17334949.57%544398530147255127
11Wild20200000112-110000000000020200000112-1100.0001120023192712820922323311762428326116.67%14564.29%029862847.45%28767342.64%17334949.57%544398530147255127
_Since Last GM Reset22910011017081-1114650110151492835000001932-13220.5007012819801231927167420922323311739205190418882022.73%851977.65%029862847.45%28767342.64%17334949.57%544398530147255127
_Vs Conference926010002242-20623010002026-630300000216-1460.333223860002319271264209223233113381018917729827.59%401172.50%029862847.45%28767342.64%17334949.57%544398530147255127

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2222OTL17012819867473920519041801
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2291011017081
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
146511015149
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
83500001932
Derniers 10 Matchs
WLOTWOTL SOWSOL
701101
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
882022.73%851977.65%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
209223233112319271
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
29862847.45%28767342.64%17334949.57%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
544398530147255127


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
3 - 2019-09-048Heat3Condors4WSommaire du Match
4 - 2019-09-0522Barracuda5Condors1LSommaire du Match
8 - 2019-09-0931Condors1Barracuda4LSommaire du Match
11 - 2019-09-1257Roadrunners4Condors2LSommaire du Match
18 - 2019-09-1994Condors4Gulls3WSommaire du Match
25 - 2019-09-26129Heat5Condors1LSommaire du Match
29 - 2019-09-30138Condors1Heat4LSommaire du Match
32 - 2019-10-03166Stars5Condors1LSommaire du Match
33 - 2019-10-04171Rampage7Condors3LSommaire du Match
37 - 2019-10-08179Condors0Wild7LSommaire du Match
39 - 2019-10-10202Condors1Wild5LSommaire du Match
45 - 2019-10-16233Condors3Gulls5LSommaire du Match
46 - 2019-10-17248Eagles4Condors5WXSommaire du Match
49 - 2019-10-20256Eagles2Condors6WSommaire du Match
52 - 2019-10-23275Condors6Reign3WSommaire du Match
53 - 2019-10-24289Roadrunners6Condors5LXXSommaire du Match
58 - 2019-10-29307Reign0Condors5WSommaire du Match
60 - 2019-10-31331Moose2Condors5WSommaire du Match
64 - 2019-11-04347Moose2Condors7WSommaire du Match
67 - 2019-11-07376Barracuda1Condors4WSommaire du Match
68 - 2019-11-08380Condors3Barracuda1WSommaire du Match
73 - 2019-11-13400Gulls3Condors2LXSommaire du Match
74 - 2019-11-14413Condors-Heat-
78 - 2019-11-18433Condors-Heat-
80 - 2019-11-20446Condors-Eagles-
81 - 2019-11-21463Condors-Eagles-
86 - 2019-11-26475Condors-Gulls-
88 - 2019-11-28498Gulls-Condors-
90 - 2019-11-30510Condors-Reign-
92 - 2019-12-02517Gulls-Condors-
94 - 2019-12-04528Eagles-Condors-
95 - 2019-12-05544Roadrunners-Condors-
99 - 2019-12-09557Condors-Stars-
101 - 2019-12-11572Condors-Eagles-
102 - 2019-12-12587Condors-Eagles-
106 - 2019-12-16603Heat-Condors-
108 - 2019-12-18615Heat-Condors-
109 - 2019-12-19630Condors-Gulls-
111 - 2019-12-21643Condors-Barracuda-
113 - 2019-12-23652Eagles-Condors-
115 - 2019-12-25666Condors-Roadrunners-
116 - 2019-12-26669Condors-Roadrunners-
122 - 2020-01-01694Wild-Condors-
123 - 2020-01-02708Condors-Reign-
129 - 2020-01-08732Barracuda-Condors-
130 - 2020-01-09747Gulls-Condors-
134 - 2020-01-13768Heat-Condors-
136 - 2020-01-15778Condors-Reign-
137 - 2020-01-16792Reign-Condors-
144 - 2020-01-23838Condors-Roadrunners-
146 - 2020-01-25846Condors-Roadrunners-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29865Wild-Condors-
151 - 2020-01-30881Barracuda-Condors-
155 - 2020-02-03895Condors-Barracuda-
157 - 2020-02-05909Condors-Heat-
158 - 2020-02-06920Condors-Barracuda-
162 - 2020-02-10942Gulls-Condors-
165 - 2020-02-13966Reign-Condors-
171 - 2020-02-19993Condors-Reign-
176 - 2020-02-241025Reign-Condors-
178 - 2020-02-261036Condors-Gulls-
179 - 2020-02-271051Barracuda-Condors-
182 - 2020-03-011061Condors-Moose-
183 - 2020-03-021068Condors-Moose-
186 - 2020-03-051096Condors-Rampage-
190 - 2020-03-091111Roadrunners-Condors-
193 - 2020-03-121140Reign-Condors-
194 - 2020-03-131150Condors-Heat-



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
20 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
821,217$ 81,000$ 11,630$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 31,021$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 121 11,242$ 1,360,282$




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
1422910011017081-1114650110151492835000001932-13227012819801231927167420922323311739205190418882022.73%851977.65%029862847.45%28767342.64%17334949.57%544398530147255127
Total Saison Régulière22910011017081-1114650110151492835000001932-13227012819801231927167420922323311739205190418882022.73%851977.65%029862847.45%28767342.64%17334949.57%544398530147255127