Dayton Clippers

GP: 7 | W: 2 | L: 3 | T: 1 | P: 5
GF: 6 | GA: 7 | PP%: 0.00% | PK%: 68.75%
DG: | Morale : 46 | Moyenne d'Équipe : 64
Prochain matchs vs Scarborough Royals
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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
1Matt ErhardX98.00192998469706573829091395099825146710
2Roy LombaX99.008959577961847583245493427075867147690
3Dion BontragerX98.5011996875525387647193668399713449690
4Brad SimsX98.50381996475506071888280508699992949680
5Ralph FrittsX99.009952456179466181837277497299993948680
6Ty SchieferX100.00235997478797171918289375099613446680
7George ZavalaX98.509939595881345173767076637799994349670
8Andrew RowmanX98.0099455357811118290858270509999149670
9Taylor VincikX100.00844057597983956379637638509979648650
10Eric TrussellX100.002914996780786979807387135099564148640
11Ron BartleyX100.003620977565697357576884397096384849630
12Jon CarvilleX98.003214997974857568826680667099904846690
13Craig DalrympleX100.006640656269839173194021845696774649680
14Chris McLachlanX98.0013199587642198879497848999993349680
15Chris AlmeidaX100.006861936568795867235164837088675949680
16Dan LemenX100.0011996581777854275166876899993048670
17Carter DecoteauX100.0011997078445564506054955599991949660
18Erick NellesX100.004924857373766377467290437086775948660
Rayé
1Jason AnastasX100.0081997574737864727279265099565148630
2Joe BardenX100.007275566876798061205662637091594648630
3Rex CareyX100.006937456862733772466050867069517948620
4Braeden HansardX100.006620896767756152645957627082756048610
5Jake WilsonX100.005940656862746150704874387087876048590
6Fredrick HembyX100.005242796761838352754760577084445748590
7Colton OrnerX100.003522417271744536463387557099847748580
8Ian HerringtonX100.003215997569748548534553537073806748580
9Mike SarnoX100.004325997265787954575679237066426248580
10Marc TheilerX100.004252807263806948263450767092726848580
11Kirk RitcheyX100.007874487358827851254644597080576848580
12Damon GinsburgX100.00241886717273595314333857070847348570
13Garrett TseleeX100.004025967174706753173943727099414948570
14Marc-Antoine CharbonneauX100.004625777362714265645539447092696148560
15Kirk McGinnisX100.006480556468714937233844757079937248610
16Ryan HorodyskiX100.00181996678797741232618745099595348590
17Kenny NevinsX100.005731746870747268526477277093406648590
18Dallas DornerX100.003015997766798232362340567096635648570
MOYENNE D'ÉQUIPE99.60472880697168656353586658679173504863
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
1Pete Hennings100.00824068777295677293676799996047760
2Lee Jonak100.00828275727481808077598245855449730
Rayé
1Devin McCollister100.00907977757674793984658885814848720
2Bryan Bourdeau100.00779071696975705473689472853648700
MOYENNE D'ÉQUIPE100.0083737373738174618265837588504873
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Curtis Goyette70757590507070CAN442250,000$


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
1Eric TrussellDayton Clippers (Cin)RW716720023268163.85%110615.1800013000000083.33%651001.3200000000
2Dion BontragerDayton Clippers (Cin)LW73252009926102111.54%413519.400002150000111057.14%731000.7400000101
3Brad SimsDayton Clippers (Cin)C7134-1005912658.33%112417.78000013000080056.14%5740000.6400000010
4Fabian TillbergCincinnati ClippersC5314-1001061881016.67%110320.72000411000061060.77%13044000.7700000001
5Dwight WardCincinnati ClippersD503350014117310.00%813126.3600001200009000.00%004000.4600000001
6Donald SissonCincinnati ClippersLW31122001492711.11%05719.1600013000020075.00%411000.7000000010
7Roy LombaDayton Clippers (Cin)C21122206671114.29%24321.6200005000060140.00%6030000.9300000010
8Chris McLachlanDayton Clippers (Cin)D5112-2001575214.29%49218.57000010000010000.00%023000.4300000000
9Ralph FrittsDayton Clippers (Cin)C7112-310010712158.33%18011.5700003000000070.45%4420000.4900000000
10Ron EdgemanCincinnati ClippersC502212018814240.00%38116.3800002000230047.83%4611000.4900000000
11Taylor VincikDayton Clippers (Cin)LW71121007983712.50%011316.1500007000070066.67%333000.3500000001
12Andrew RowmanDayton Clippers (Cin)RW7112-140177174115.88%412017.18000314000000062.50%833000.3300000000
13Matt ErhardDayton Clippers (Cin)LW20222003310230.00%15025.2300005000370082.35%1711000.7900000000
14Chris AlmeidaDayton Clippers (Cin)D711220081056320.00%1114520.80000014000013000.00%004000.2700000100
15George ZavalaDayton Clippers (Cin)RW50114155572120.00%18116.31000111000000083.33%620000.2500000000
16Dan LemenDayton Clippers (Cin)D70112000126210.00%1110915.710001400001000.00%003000.1800000000
17Jason AnastasDayton Clippers (Cin)LW5101-2000220050.00%1397.89000020000100100.00%110000.5100000000
18Joe BardenDayton Clippers (Cin)RW21011004230033.33%02713.93000000000000100.00%101000.7200000000
19Erick NellesDayton Clippers (Cin)D7011-400138440.00%59313.320000000003000.00%050000.2100000000
20Ron BartleyDayton Clippers (Cin)LW61011002221250.00%2579.550000000002000.00%020000.3500000010
21Craig DalrympleDayton Clippers (Cin)D70004206126310.00%916423.53000018000012000.00%003000.0000000000
22Jon CarvilleDayton Clippers (Cin)D20000001103110.00%35829.390001600007000.00%013000.0000000000
23Carter DecoteauDayton Clippers (Cin)D7000-100054000.00%3557.980000000001000.00%002000.0000000000
24Ty SchieferDayton Clippers (Cin)C2000000032000.00%0168.2200001000000066.67%600000.0000000000
Stats d'équipe Total ou en Moyenne12618294716355130155216731078.33%76209216.610001416800051192158.59%3964338000.4500000244
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
1Lee JonakDayton Clippers (Cin)52300.9012.80300001414172010.000052000
2Pete HenningsDayton Clippers (Cin)20110.9192.401250056222000.000020000
Stats d'équipe Total ou en Moyenne72410.9062.68425001920394010.000072000


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 CONT StatusType Salaire Actuel Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Andrew RowmanDayton Clippers (Cin)RW282/25/1989No228 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm461,000$461,000$461,000$
Brad SimsDayton Clippers (Cin)C3411/10/1982No205 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm429,000$429,000$429,000$
Braeden HansardDayton Clippers (Cin)C2010/6/1996No198 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm247,997$247,997$
Bryan BourdeauDayton Clippers (Cin)D249/29/1992No175 Lbs5 ft6NoNoNo3Avec RestrictionPro & Farm249,000$249,000$249,000$
Carter DecoteauDayton Clippers (Cin)D289/12/1988No201 Lbs6 ft8NoNoNo3Sans RestrictionPro & Farm403,000$403,000$403,000$
Chris AlmeidaDayton Clippers (Cin)D2012/13/1996No226 Lbs6 ft7NoNoNo2Contrat d'EntréePro & Farm332,267$332,267$
Chris McLachlanDayton Clippers (Cin)D354/11/1982No219 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm469,000$469,000$469,000$
Colton OrnerDayton Clippers (Cin)RW226/14/1995No182 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm250,000$250,000$250,000$
Craig DalrympleDayton Clippers (Cin)D264/11/1991No210 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm443,029$443,029$
Dallas DornerDayton Clippers (Cin)D2210/3/1994No176 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm205,035$
Damon GinsburgDayton Clippers (Cin)RW239/12/1993No182 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm254,000$254,000$254,000$
Dan LemenDayton Clippers (Cin)D2712/20/1989No217 Lbs6 ft6NoNoNo1Avec RestrictionPro & Farm400,000$
Devin McCollisterDayton Clippers (Cin)D215/22/1996No171 Lbs6 ft5NoNoNo1Contrat d'EntréePro & Farm230,419$
Dion BontragerDayton Clippers (Cin)LW278/8/1989No194 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm524,000$524,000$524,000$
Eric TrussellDayton Clippers (Cin)RW249/28/1992No207 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm370,000$370,000$370,000$
Erick NellesDayton Clippers (Cin)D207/25/1996No193 Lbs6 ft5NoNoNo2Contrat d'EntréePro & Farm294,313$294,313$
Fredrick HembyDayton Clippers (Cin)C198/5/1997No198 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm232,823$232,823$232,823$
Garrett TseleeDayton Clippers (Cin)RW223/21/1995No185 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm239,000$239,000$239,000$
George ZavalaDayton Clippers (Cin)RW3110/29/1985No231 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm443,000$443,000$443,000$
Ian HerringtonDayton Clippers (Cin)C223/7/1995No175 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm247,000$247,000$247,000$
Jake WilsonDayton Clippers (Cin)RW192/10/1998No197 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm256,370$256,370$256,370$
Jason AnastasDayton Clippers (Cin)LW244/22/1993No182 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm307,000$307,000$307,000$
Joe BardenDayton Clippers (Cin)RW216/7/1996No198 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm296,019$
Jon CarvilleDayton Clippers (Cin)D221/27/1995No175 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm477,000$477,000$477,000$
Kenny NevinsDayton Clippers (Cin)D211/31/1996No198 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm207,954$
Kirk McGinnisDayton Clippers (Cin)D201/12/1997No201 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm231,005$231,005$
Kirk RitcheyDayton Clippers (Cin)RW217/21/1995No182 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm238,793$238,793$
Lee JonakDayton Clippers (Cin)RW228/9/1994No177 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm323,000$323,000$323,000$
Marc TheilerDayton Clippers (Cin)RW2111/30/1995No197 Lbs6 ft7NoNoNo2Contrat d'EntréePro & Farm248,921$248,921$
Marc-Antoine CharbonneauDayton Clippers (Cin)C2012/18/1996No178 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm225,345$225,345$
Matt ErhardDayton Clippers (Cin)LW248/21/1992No158 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm534,000$534,000$534,000$
Mike SarnoDayton Clippers (Cin)LW229/18/1994No189 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm219,711$
Pete HenningsDayton Clippers (Cin)RW273/12/1990No189 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm459,000$459,000$459,000$
Ralph FrittsDayton Clippers (Cin)C315/18/1986No222 Lbs6 ft4NoNoNo3Sans RestrictionPro & Farm475,000$475,000$475,000$
Rex CareyDayton Clippers (Cin)C202/24/1997No172 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm243,163$243,163$
Ron BartleyDayton Clippers (Cin)LW205/15/1997No183 Lbs6 ft4NoNoNo2Contrat d'EntréePro & Farm240,746$240,746$
Roy LombaDayton Clippers (Cin)C1910/22/1997No191 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm436,635$436,635$436,635$
Ryan HorodyskiDayton Clippers (Cin)D249/28/1992No209 Lbs6 ft5NoNoNo3Avec RestrictionPro & Farm259,000$259,000$259,000$
Taylor VincikDayton Clippers (Cin)LW285/3/1989No218 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm365,000$365,000$365,000$
Ty SchieferDayton Clippers (Cin)C246/30/1992No193 Lbs6 ft7NoNoNo1Avec RestrictionPro & Farm300,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
4023.63195 Lbs6 ft32.40326,689$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt ErhardRoy LombaGeorge Zavala40122
2Dion BontragerBrad SimsAndrew Rowman30122
3Taylor VincikRalph FrittsEric Trussell20122
4Ron BartleyTy SchieferMatt Erhard10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon CarvilleChris McLachlan40122
2Chris AlmeidaCraig Dalrymple30122
3Dan LemenErick Nelles20122
4Carter DecoteauJon Carville10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt ErhardRoy LombaGeorge Zavala60122
2Dion BontragerBrad SimsAndrew Rowman40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon CarvilleChris McLachlan60122
2Chris AlmeidaCraig Dalrymple40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Matt ErhardRoy Lomba60122
2Dion BontragerBrad Sims40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon CarvilleChris McLachlan60122
2Chris AlmeidaCraig Dalrymple40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Matt Erhard60122Jon CarvilleChris McLachlan60122
2Roy Lomba40122Chris AlmeidaCraig Dalrymple40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Matt ErhardRoy Lomba60122
2Dion BontragerBrad Sims40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon CarvilleChris McLachlan60122
2Chris AlmeidaCraig Dalrymple40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt ErhardRoy LombaGeorge ZavalaJon CarvilleChris McLachlan
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt ErhardRoy LombaGeorge ZavalaJon CarvilleChris McLachlan
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ralph Fritts, Ty Schiefer, Taylor VincikRalph Fritts, Ty SchieferTaylor Vincik
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dan Lemen, Erick Nelles, Carter DecoteauDan LemenErick Nelles, Carter Decoteau
Tirs de Pénalité
Matt Erhard, Roy Lomba, Dion Bontrager, Brad Sims, Ralph Fritts
Gardien
#1 : Pete Hennings, #2 : Lee Jonak


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
1Bowling Green Red Devils11000000633000000000001100000063321.00069150085503989755024512224100.00%10100.00%08916454.27%9214563.45%518758.62%140741437114168
2Canadaigua Lakers1000010012-11000010012-10000000000000.000123008550198975502118418300.00%20100.00%08916454.27%9214563.45%518758.62%140741437114168
3Johnstown Yellow Jackets21010000523110000004131001000011030.750581300855062897550238231039400.00%5180.00%08916454.27%9214563.45%518758.62%140741437114168
4Niagara Falls Wings1010000014-31010000014-30000000000000.0001230085503189755024312411500.00%2150.00%08916454.27%9214563.45%518758.62%140741437114168
5Scarborough Royals1010000024-2000000000001010000024-200.000246108550298975502368418100.00%20100.00%08916454.27%9214563.45%518758.62%140741437114168
Since Last GM Reset733001001820-23110010067-1422000001213-160.429182947108550216897550220476351301800.00%16568.75%08916454.27%9214563.45%518758.62%140741437114168
Total723101001820-23110010067-1412100001213-150.357182947108550216897550220476351301800.00%16568.75%08916454.27%9214563.45%518758.62%140741437114168
8Virginia Beach Mariners1010000035-2000000000001010000035-200.00034700855036897550231131120400.00%4325.00%08916454.27%9214563.45%518758.62%140741437114168
Vs Conference733001001820-23110010067-1422000001213-160.429182947108550216897550220476351301800.00%16568.75%08916454.27%9214563.45%518758.62%140741437114168
Vs Division63200100151503110010067-13210000098160.500152540108550180897550217363241101400.00%12283.33%08916454.27%9214563.45%518758.62%140741437114168

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
75T1182947216204763513010
Tous les Matchs
GPWLOTWOTL TGFGA
7230111820
Matchs locaux
GPWLOTWOTL TGFGA
31101067
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
4120011213
Derniers 10 Matchs
WLOTWOTL T
23011
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1800.00%16568.75%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
89755028550
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
8916454.27%9214563.45%518758.62%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
140741437114168


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 - 2017-12-092Dayton Clippers2Scarborough Royals4LSommaire du Match
5 - 2017-12-1322Canadaigua Lakers2Dayton Clippers1LXSommaire du Match
7 - 2017-12-1536Dayton Clippers3Virginia Beach Mariners5LSommaire du Match
8 - 2017-12-1644Johnstown Yellow Jackets1Dayton Clippers4WSommaire du Match
11 - 2017-12-1961Dayton Clippers6Bowling Green Red Devils3WSommaire du Match
15 - 2017-12-2375Niagara Falls Wings4Dayton Clippers1LSommaire du Match
17 - 2017-12-2586Dayton Clippers1Johnstown Yellow Jackets1TXSommaire du Match
19 - 2017-12-27101Bowling Green Red Devils-Dayton Clippers-
21 - 2017-12-29114Dayton Clippers-Canadaigua Lakers-
23 - 2017-12-31123Dayton Clippers-Charlottesville Robins-
24 - 2018-01-01133Lafayette Racers-Dayton Clippers-
30 - 2018-01-07156Charlottesville Robins-Dayton Clippers-
33 - 2018-01-10176Columbia Tigers-Dayton Clippers-
36 - 2018-01-13192Dayton Clippers-Canadaigua Lakers-
38 - 2018-01-15203Bowling Green Red Devils-Dayton Clippers-
40 - 2018-01-17219Arlington Americans-Dayton Clippers-
42 - 2018-01-19232Dayton Clippers-Augusta Wolves-
46 - 2018-01-23247Reading Patriots-Dayton Clippers-
48 - 2018-01-25265Dayton Clippers-Lafayette Racers-
50 - 2018-01-27274Niagara Falls Wings-Dayton Clippers-
52 - 2018-01-29286Dayton Clippers-Niagara Falls Wings-
54 - 2018-01-31302Lafayette Racers-Dayton Clippers-
58 - 2018-02-04316Dayton Clippers-Lafayette Racers-
60 - 2018-02-06330Pawtucket Reds-Dayton Clippers-
62 - 2018-02-08338Dayton Clippers-Reading Patriots-
65 - 2018-02-11357Williamsburg Dragons-Dayton Clippers-
67 - 2018-02-13370Dayton Clippers-Williamsburg Dragons-
70 - 2018-02-16383Watertown Bulls-Dayton Clippers-
75 - 2018-02-21408Charlesbourg Cavaliers-Dayton Clippers-
79 - 2018-02-25431Dayton Clippers-Charlottesville Robins-
81 - 2018-02-27436Johnstown Yellow Jackets-Dayton Clippers-
83 - 2018-03-01451Dayton Clippers-Johnstown Yellow Jackets-
85 - 2018-03-03462Beverly Jr. Eagles-Dayton Clippers-
87 - 2018-03-05473Dayton Clippers-Harrisburg Rockets-
89 - 2018-03-07487Dayton Clippers-Montpelier Cougars-
90 - 2018-03-08494Harrisburg Rockets-Dayton Clippers-
93 - 2018-03-11506Dayton Clippers-Napean Spartans-
95 - 2018-03-13519Dayton Clippers-Scarborough Royals-
97 - 2018-03-15528Virginia Beach Mariners-Dayton Clippers-
100 - 2018-03-18544Dayton Clippers-Cape Breton Kings-
101 - 2018-03-19554Troy Indians-Dayton Clippers-
105 - 2018-03-23571Elmira Roadrunners-Dayton Clippers-
107 - 2018-03-25584Dayton Clippers-Niagara Falls Wings-
108 - 2018-03-26592Dayton Clippers-Arlington Americans-
111 - 2018-03-29607Lowell Plainsmen-Dayton Clippers-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
115 - 2018-04-02620Dayton Clippers-Longueuil Voyageurs-
117 - 2018-04-04629Dayton Clippers-Columbia Tigers-
118 - 2018-04-05640Dayton Clippers-Virginia Beach Mariners-
120 - 2018-04-07647Canadaigua Lakers-Dayton Clippers-
123 - 2018-04-10664Dayton Clippers-Amherst Winterhawks-
125 - 2018-04-12672Canadaigua Lakers-Dayton Clippers-
127 - 2018-04-14686Dayton Clippers-Bowling Green Red Devils-
129 - 2018-04-16698Scarborough Royals-Dayton Clippers-
136 - 2018-04-23729Scarborough Royals-Dayton Clippers-



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
24 0 - 0.00% 0$0$3000100

Dépenses
Salaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,266,887$ 3,266,887$ 0$
Dépenses Annuelles à Ce JourCap Salarial Par JourCap salarial à ce jour
374,879$ 23,846$ 374,879$

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 120 23,846$ 2,861,520$




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
Saison Régulière
13-1480274074200289314-2540142131100146157-1140131943100143157-14612894727618099959142922103597690011274196344617002214821.72%2085175.48%71123207354.17%1001191452.30%706125956.08%168489115787661587807
14-1580363162500318299194018162040016315310401815421001551469783185198374110496116229981102962917173046101348415842284519.74%1503179.33%7992207147.90%1017212547.86%617131446.96%165689016487461531783
15-1680362777300318275434019143220016613828401713451001521371579318526844119511610072929108288392836289694744016712474116.60%2013881.09%61174205157.24%1166202357.64%732128157.14%166488316267681561790
16-17804329701002752561940278401001571144340162130000118142-24932754637383090100850261693391375713255880041215312416125.31%1874575.94%41086191756.65%1014188253.88%650118454.90%166388816097521563801
1001723101001820-23110010067-1412100001213-15182947108550216897550220476351301800.00%16568.75%08916454.27%9214563.45%518758.62%140741437114168
Total Saison Régulière32714413028131200121811645416379601239006385696916465701610300580595-153161218200932271723964123971311681424138093552791144537991817661695519520.42%76217077.69%244464827653.94%4290808953.03%2756512553.78%681036276606310563843251