Harvard

GP: 18 | W: 7 | L: 10 | T: 1 | P: 15
GF: 61 | GA: 61 | PP%: 24.00% | PK%: 81.25%
DG: Marcel | Morale : 48 | Moyenne d'Équipe : 65
Prochain matchs #125 vs Ailes Rouges
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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
1Ron SutterX99.008270576871797972687568746655663354680
2Tim Taylor (C)X98.006448727472727675667570836432357453680
3Jim SandlakX100.007868506381777769626864776161675535670
4German Titov (R)X100.005545847759807176796873687165485053670
5Jason Allison (R)X100.006658757666776978797573707735359853670
6Brent FedykX100.006146787072747473647374706848446140660
7Mikko MakelaX100.005741826575676767616971696759684653650
8Martin Straka (R)X100.005244697570696977707870636532369753650
9Josef BeranekX100.005339817272707275687573617138407453650
10Ronnie SternX100.008376386574747662636563796247416054640
11Craig JohnsonX100.005948677272676867657368666432328953630
12Reid SimpsonX100.006960546777687166656658795538387553630
13J. J. DaigneaultX100.006446816971777676677767736057575453670
14Sean HillX100.006549766974777871657468826432358153670
15Dimitri YushkevichX100.007765626975686874677666806240378955670
16Jeff NortonX100.006551676575697064627352765041354840630
17Janne Laukkanen (R)X100.005745787172666768627258725335288253620
18Ryan McGill (R)X100.008265556674646455546442784035357649620
Rayé
1Jozef StumpelX100.005948686778687070657367666431339732630
2Stu GrimsonX100.009890305981747660586345794352524739620
3Niklas AnderssonX100.004937827569656872647267606232328932620
4Pat PeakeX100.005544797170616466656861676041419632610
5Matthew Barnaby (R)X100.008276456674656654536054755228339850590
6Todd ReirdenX100.006347726480686864606852745019289042610
7Cory Cross (R)X100.006865446281676755525845764336419045610
8Jan Vopat (R)X100.005644796274596057586541733931339841580
MOYENNE D'ÉQUIPE99.88665466687370706864706273594041754764
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
1Vincent Riendeau100.00717883808071758477777352525438720
2Wendell Young100.00658674727068728073697173763353710
Rayé
1Milan Hnilicka100.00677475737168758175696727319732660
MOYENNE D'ÉQUIPE100.0068797775746974827572705153614170
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Michel Therrien71707072738388CAN31295,000$


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
1Tim TaylorHarvard (BOS)C188142278043971212611.27%438521.3918923691124902054.67%15000001.1400000212
2Sean HillHarvard (BOS)D18912212120153336142425.00%1740922.7475122271011073000.00%000001.0300000210
3Ron SutterHarvard (BOS)C1841620-237560545412387.41%541322.95281016780222821053.40%61800000.9700100121
4J. J. DaigneaultHarvard (BOS)D185813-41209363291315.63%2443924.414371877101179010.00%000000.5900000000
5Dimitri YushkevichHarvard (BOS)D1749133320433834102211.76%1639223.063472357011256100.00%000000.6600000021
6Jason AllisonHarvard (BOS)C186713-620163546133113.04%429916.6433611690003451064.81%21600000.8700000120
7Janne LaukkanenHarvard (BOS)D181910-416018201310177.69%2034319.07123557000041000.00%000000.5800000001
8Martin StrakaHarvard (BOS)LW183710-10206244413226.82%129216.2315615740112140150.00%4000000.6800000000
9Brent FedykHarvard (BOS)RW18369-880815468286.52%330717.071341576000001050.00%2200000.5900000001
10Reid SimpsonHarvard (BOS)LW18549420028122491320.83%021612.0200000000000042.86%1400000.8300000000
11German TitovHarvard (BOS)C182573202424817344.17%327015.04000100001440056.62%30200000.5200000000
12Mikko MakelaHarvard (BOS)LW18246-3203131811011.11%11478.2000000101160060.00%1000000.8100000000
13Josef BeranekHarvard (BOS)C18325-600610314269.68%024013.35000112000011039.53%8600000.4200000000
14Ronnie SternHarvard (BOS)RW18044-3155378193110.00%118410.24011472000010041.67%1200000.4300001000
15Craig JohnsonHarvard (BOS)LW18213-200217175711.76%11618.98000030001350050.00%3600000.3700000000
16Jan VopatHarvard (BOS)D10112217514531333.33%615115.1300013000029000.00%000000.2600000000
17Ryan McGillHarvard (BOS)D520218011351440.00%37915.9300010000011000.00%000000.5000000000
18Jeff NortonHarvard (BOS)D13112-106025992211.11%821416.51101532000022000.00%000000.1900000000
19Matthew BarnabyHarvard (BOS)RW1701111202677140.00%11649.6500001000000045.61%5700000.1200000000
20Todd ReirdenHarvard (BOS)D1000000220010.00%01616.850000100000000.00%000000.0000000000
21Cory CrossHarvard (BOS)D8000-21602413100.00%310713.430000100002000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne32361111172-372271535942356015533610.89%121523616.21244266161762369176417254.32%156300000.6600101686
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
1Vincent RiendeauHarvard (BOS)1871000.8783.3997421554510100.0000180210
2Wendell YoungHarvard (BOS)30010.8913.36107006550000.0000018000
Stats d'équipe Total ou en Moyenne2171010.8793.38108221615060100.00001818210


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
Brent FedykHarvard (BOS)RW261994-02-09 9:08:37 PMNo186 Lbs6 ft1NoNoNo2Pro & Farm575,000$57,500$45,239$No575,000$
Cory CrossHarvard (BOS)D221998-02-09 9:08:37 PMYes219 Lbs6 ft5NoNoNo3Pro & Farm380,000$38,000$29,897$No380,000$380,000$
Craig JohnsonHarvard (BOS)LW221998-02-09 9:08:37 PMNo197 Lbs6 ft2NoNoNo2Pro & Farm225,000$22,500$17,702$No225,000$
Dimitri YushkevichHarvard (BOS)D221998-02-09 9:08:37 PMNo203 Lbs6 ft0NoNoNo2Pro & Farm500,000$50,000$39,338$No500,000$
German TitovHarvard (BOS)C291991-08-11 9:51:50 AMYes176 Lbs5 ft11NoNoNo3Pro & Farm250,000$25,000$19,669$No250,000$250,000$
J. J. DaigneaultHarvard (BOS)D271993-02-09 9:08:37 PMNo180 Lbs5 ft11NoNoNo1Pro & Farm595,000$59,500$46,812$No
Jan VopatHarvard (BOS)D202000-02-09 9:08:37 PMYes207 Lbs6 ft0NoNoNo3Pro & Farm300,000$30,000$23,603$No300,000$300,000$
Janne LaukkanenHarvard (BOS)D231997-02-09 9:08:37 PMYes180 Lbs6 ft0NoNoNo1Pro & Farm280,000$28,000$22,029$No
Jason AllisonHarvard (BOS)C192001-08-11 9:56:05 AMYes205 Lbs6 ft3NoNoNo3Pro & Farm250,000$25,000$19,669$No250,000$250,000$
Jeff NortonHarvard (BOS)D281992-02-09 9:08:37 PMNo195 Lbs6 ft2NoNoNo2Pro & Farm225,000$22,500$17,702$No225,000$
Jim SandlakHarvard (BOS)RW271993-02-09 9:08:37 PMNo219 Lbs6 ft4NoNoNo2Pro & Farm400,000$40,000$31,471$No400,000$
Josef BeranekHarvard (BOS)C241996-02-09 9:08:37 PMNo195 Lbs6 ft2NoNoNo2Pro & Farm470,000$47,000$36,978$No470,000$
Jozef StumpelHarvard (BOS)C211999-02-09 9:08:37 PMNo216 Lbs6 ft3NoNoNo2Pro & Farm500,000$50,000$39,338$No500,000$
Martin StrakaHarvard (BOS)LW211999-02-09 9:08:37 PMYes175 Lbs5 ft10NoNoNo3Pro & Farm520,000$52,000$40,912$No520,000$520,000$
Matthew BarnabyHarvard (BOS)RW202000-02-09 9:08:37 PMYes195 Lbs6 ft1NoNoNo2Pro & Farm350,000$35,000$27,537$No350,000$
Mikko MakelaHarvard (BOS)LW281992-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo2Pro & Farm250,000$25,000$19,669$No250,000$
Milan HnilickaHarvard (BOS)G211999-02-09 9:08:37 PMNo180 Lbs6 ft0NoNoNo2Pro & Farm270,000$27,000$21,243$No270,000$
Niklas AnderssonHarvard (BOS)LW221998-02-09 9:08:37 PMNo175 Lbs5 ft9NoNoNo3Pro & Farm386,000$38,600$30,369$No386,000$386,000$
Pat PeakeHarvard (BOS)C202000-02-09 9:08:37 PMNo190 Lbs6 ft1NoNoNo3Pro & Farm220,000$22,000$17,309$No220,000$220,000$
Reid SimpsonHarvard (BOS)LW241996-02-09 9:08:37 PMNo210 Lbs6 ft1NoNoNo1Pro & Farm480,000$48,000$37,765$No
Ron SutterHarvard (BOS)C301990-02-09 9:08:37 PMNo180 Lbs6 ft0NoNoNo2Pro & Farm554,500$55,450$43,626$No554,500$
Ronnie SternHarvard (BOS)RW261994-02-09 9:08:37 PMNo195 Lbs6 ft0NoNoNo3Pro & Farm429,000$42,900$33,752$No429,000$429,000$
Ryan McGillHarvard (BOS)D241996-02-09 9:08:37 PMYes197 Lbs6 ft2NoNoNo1Pro & Farm387,000$38,700$30,448$No
Sean HillHarvard (BOS)D231997-02-09 9:08:37 PMNo203 Lbs6 ft0NoNoNo1Pro & Farm460,000$46,000$36,191$No
Stu GrimsonHarvard (BOS)LW281992-02-09 9:08:37 PMNo230 Lbs6 ft5NoNoNo1Pro & Farm395,000$39,500$31,077$No
Tim TaylorHarvard (BOS)C241996-02-09 9:08:37 PMNo185 Lbs6 ft1NoNoNo1Pro & Farm450,000$45,000$35,404$No
Todd ReirdenHarvard (BOS)D221998-02-09 9:08:37 PMNo220 Lbs6 ft5NoNoNo3Pro & Farm359,000$35,900$28,245$No359,000$359,000$
Vincent RiendeauHarvard (BOS)G271993-02-09 9:08:37 PMNo181 Lbs5 ft10NoNoNo3Pro & Farm985,000$98,500$77,496$No985,000$985,000$
Wendell YoungHarvard (BOS)G301990-02-09 9:08:37 PMNo182 Lbs5 ft9NoNoNo2Pro & Farm750,000$75,000$59,007$No750,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2924.14196 Lbs6 ft12.10420,534$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Josef BeranekTim TaylorBrent Fedyk35122
2Ron SutterGerman TitovMikko Makela30122
3Martin StrakaJason AllisonReid Simpson25122
4Craig JohnsonTim TaylorRonnie Stern10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sean HillDimitri Yushkevich35122
2J. J. DaigneaultRyan McGill30122
3Janne LaukkanenJeff Norton20122
4J. J. DaigneaultSean Hill15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Martin StrakaRon SutterBrent Fedyk60122
2Jason AllisonTim TaylorRonnie Stern40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1J. J. DaigneaultJeff Norton60122
2Sean HillJanne Laukkanen40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Ron SutterTim Taylor60122
2German TitovJason Allison40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1J. J. DaigneaultRyan McGill60122
2Sean HillJanne Laukkanen40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Ron Sutter60122J. J. DaigneaultJeff Norton60122
2Tim Taylor40122Sean HillJanne Laukkanen40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Ron SutterTim Taylor60122
2German TitovJason Allison40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1J. J. DaigneaultJeff Norton60122
2Sean HillJanne Laukkanen40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mikko MakelaRon SutterBrent FedykJ. J. DaigneaultSean Hill
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mikko MakelaRon SutterBrent FedykJ. J. DaigneaultSean Hill
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Josef Beranek, Martin Straka, Craig JohnsonJosef Beranek, Martin StrakaCraig Johnson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Janne Laukkanen, J. J. Daigneault, Sean HillJanne LaukkanenJ. J. Daigneault, Sean Hill
Tirs de Pénalité
Ron Sutter, Tim Taylor, German Titov, Jason Allison, Brent Fedyk
Gardien
#1 : Vincent Riendeau, #2 : Wendell Young


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
1Ailes Rouges21100000651000000000002110000065120.50061117002716171661831811942631233281317.69%11281.82%136564956.24%31961651.79%16529855.37%438295413139234116
2As1010000045-11010000045-10000000000000.000461000271617135183181194238714217342.86%6350.00%036564956.24%31961651.79%16529855.37%438295413139234116
3Canadiens43100000191091010000013-2330000001871160.750193554002716171135183181194210928568728517.86%26388.46%136564956.24%31961651.79%16529855.37%438295413139234116
4Chiefs31101000972201010007701100000020240.667917260127161719818318119426517435412325.00%16475.00%136564956.24%31961651.79%16529855.37%438295413139234116
5Citadelles1010000036-3000000000001010000036-300.0003580027161713218318119423310420500.00%2150.00%036564956.24%31961651.79%16529855.37%438295413139234116
6Pacifiques de la route1010000024-21010000024-20000000000000.00023500271617129183181194240174152150.00%2150.00%036564956.24%31961651.79%16529855.37%438295413139234116
7Riverman11000000734000000000001100000073421.000713200027161714018318119422234188675.00%20100.00%036564956.24%31961651.79%16529855.37%438295413139234116
8Snipers20110000712-5100100005501010000027-510.25071320002716171531831811942671833485360.00%12191.67%036564956.24%31961651.79%16529855.37%438295413139234116
9Spoonman's2020000035-21010000034-11010000001-100.00036900271617143183181194255630481218.33%15286.67%036564956.24%31961651.79%16529855.37%438295413139234116
Total186101100061610806110002332-910640000038299150.4176111117201271617156018318119425061212293591002424.00%961881.25%336564956.24%31961651.79%16529855.37%438295413139234116
11Wolves1010000014-31010000014-30000000000000.0001230027161712918318119421438208112.50%4175.00%036564956.24%31961651.79%16529855.37%438295413139234116
_Since Last GM Reset187100100061610806110002332-91074-1000038299160.4446111117201271617156018318119425061212293591002424.00%961881.25%336564956.24%31961651.79%16529855.37%438295413139234116
_Vs Conference10450100034286403010001114-36420000023149100.50034639701271617130818318119422626113320957915.79%591083.05%236564956.24%31961651.79%16529855.37%438295413139234116
_Vs Division9440100031229403010001114-35410000020812100.55631588901271617127618318119422295112918952917.31%57984.21%236564956.24%31961651.79%16529855.37%438295413139234116

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
1815W16111117256050612122935901
Tous les Matchs
GPWLOTWOTL TGFGA
186101016161
Matchs locaux
GPWLOTWOTL TGFGA
8061012332
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
10640003829
Derniers 10 Matchs
WLOTWOTL T
37000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1002424.00%961881.25%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
18318119422716171
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
36564956.24%31961651.79%16529855.37%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
438295413139234116


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2020-09-216Snipers5Harvard5TXSommaire du Match
2 - 2020-09-229Harvard7Riverman3WSommaire du Match
4 - 2020-09-2417Harvard3Citadelles6LSommaire du Match
5 - 2020-09-2524Harvard0Spoonman's1LSommaire du Match
6 - 2020-09-2628Chiefs2Harvard3WXSommaire du Match
7 - 2020-09-2734Harvard2Chiefs0WSommaire du Match
9 - 2020-09-2940Spoonman's4Harvard3LSommaire du Match
10 - 2020-09-3051Harvard3Ailes Rouges1WSommaire du Match
11 - 2020-10-0153Canadiens3Harvard1LSommaire du Match
13 - 2020-10-0361Harvard9Canadiens2WSommaire du Match
15 - 2020-10-0570Chiefs5Harvard4LSommaire du Match
17 - 2020-10-0778Harvard2Snipers7LSommaire du Match
19 - 2020-10-0983As5Harvard4LSommaire du Match
21 - 2020-10-1192Harvard3Ailes Rouges4LSommaire du Match
23 - 2020-10-1397Pacifiques de la route4Harvard2LSommaire du Match
25 - 2020-10-15104Harvard6Canadiens3WSommaire du Match
27 - 2020-10-17111Wolves4Harvard1LSommaire du Match
29 - 2020-10-19119Harvard3Canadiens2WSommaire du Match
31 - 2020-10-21125Harvard-Ailes Rouges-
33 - 2020-10-23131Wolves-Harvard-
35 - 2020-10-25140Ailes Rouges-Harvard-
37 - 2020-10-27147Harvard-Banshees-
39 - 2020-10-29152Harvard-Pacifiques de la route-
41 - 2020-10-31159Canadiens-Harvard-
42 - 2020-11-01168Pacifiques de la route-Harvard-
44 - 2020-11-03176Wolves-Harvard-
46 - 2020-11-05182Harvard-Snipers-
47 - 2020-11-06189Chiefs-Harvard-
49 - 2020-11-08198Harvard-Chiefs-
50 - 2020-11-09203Harvard-Wolves-
52 - 2020-11-11209Chiefs-Harvard-
53 - 2020-11-12217Snipers-Harvard-
55 - 2020-11-14226Harvard-Wolves-
57 - 2020-11-16233Harvard-As-
58 - 2020-11-17237Croque-Morts-Harvard-
59 - 2020-11-18243Harvard-Isotopes-
61 - 2020-11-20250Citadelles-Harvard-
63 - 2020-11-22261Harvard-Chiefs-
65 - 2020-11-24266Croque-Morts-Harvard-
66 - 2020-11-25273Harvard-Croque-Morts-
67 - 2020-11-26280Riverman-Harvard-
68 - 2020-11-27289Croque-Morts-Harvard-
71 - 2020-11-30297Harvard-Citadelles-
72 - 2020-12-01303As-Harvard-
73 - 2020-12-02306Harvard-As-
74 - 2020-12-03311Harvard-Spoonman's-
75 - 2020-12-04319Harvard-Croque-Morts-
76 - 2020-12-05325Isotopes-Harvard-
78 - 2020-12-07334Banshees-Harvard-
79 - 2020-12-08344Harvard-Snipers-
80 - 2020-12-09345Harvard-Riverman-
82 - 2020-12-11352Isotopes-Harvard-
84 - 2020-12-13362Canadiens-Harvard-
86 - 2020-12-15367Harvard-Citadelles-
88 - 2020-12-17375Isotopes-Harvard-
90 - 2020-12-19380Harvard-Banshees-
92 - 2020-12-21391Riverman-Harvard-
94 - 2020-12-23395Harvard-Spoonman's-
96 - 2020-12-25404As-Harvard-
98 - 2020-12-27409Harvard-Riverman-
100 - 2020-12-29416Harvard-Pacifiques de la route-
101 - 2020-12-30421Snipers-Harvard-
103 - 2021-01-01434Chiefs-Harvard-
104 - 2021-01-02439Harvard-Canadiens-
106 - 2021-01-04446Spoonman's-Harvard-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
109 - 2021-01-07454Harvard-Chiefs-
110 - 2021-01-08461Spoonman's-Harvard-
111 - 2021-01-09464Harvard-Spoonman's-
113 - 2021-01-11471Harvard-Riverman-
114 - 2021-01-12477Ailes Rouges-Harvard-
115 - 2021-01-13484Harvard-Banshees-
116 - 2021-01-14487Harvard-Ailes Rouges-
117 - 2021-01-15492Pacifiques de la route-Harvard-
119 - 2021-01-17504Spoonman's-Harvard-
121 - 2021-01-19516Snipers-Harvard-
122 - 2021-01-20521Harvard-Isotopes-
123 - 2021-01-21528Harvard-As-
124 - 2021-01-22532Citadelles-Harvard-
127 - 2021-01-25542Banshees-Harvard-
128 - 2021-01-26549Harvard-Citadelles-
130 - 2021-01-28558Banshees-Harvard-
135 - 2021-02-02573Canadiens-Harvard-



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
33 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
261,599$ 1,219,550$ 1,219,550$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,219,550$ 261,599$ 29 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 107 9,666$ 1,034,262$




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
1993186101100061610806110002332-910640000038299156111117201271617156018318119425061212293591002424.00%961881.25%336564956.24%31961651.79%16529855.37%438295413139234116
Total Saison Régulière186101100061610806110002332-910640000038299156111117201271617156018318119425061212293591002424.00%961881.25%336564956.24%31961651.79%16529855.37%438295413139234116