Admirals

GP: 10 | W: 4 | L: 5 | OTL: 1 | P: 9
GF: 34 | GA: 37 | PP%: 17.14% | PK%: 75.76%
DG: Stéphane Fournier | Morale : 49 | Moyenne d'Équipe : 61
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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
1Jason PominvilleX100.005635936770738666546870636987803245660
2Austin Poganski (R)XX100.006335935877918757625953585565636246600
3Sam AnasXX100.005135935961918758655955535771665953590
4Jansen HarkinsXX100.005837885774939156595556575663626352590
5Lukas SedlakXXX100.008037855675646056735459655871664741590
6Chase Balisy (A)X100.005337885568959654585352555173675853580
7Samuel KurkerX100.006638855881777156525353565469656753580
8Brandon GignacXX100.005436925766797156635854575263626550570
9Tanner Kaspick (R)X100.006137885474878153555252545061636448570
10Joseph GambardellaXX100.005935945670615854555753555671664243560
11Otto Somppi (R)X100.006336905479787253585252545361636453560
12Jacob MiddletonX100.006238855985796958306054635865635651620
13Ben ThomasX100.005936905576939054305551574565636545610
14Ethan BearX100.005838865972908458306252564763625949610
15Dominik MasinX100.006740795483939153305251565465637254610
16Dysin MayoX100.006238855476939053305251544865636253600
17Brandon Hickey (R)X100.006637885581837754305552584565636253600
18Emil JohanssonX100.005238855459928953305251554765626353580
Rayé
MOYENNE D'ÉQUIPE100.00613788577484815648565457536765595059
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
1Louis Domingue100.00797775857877797877797873774849760
2Jake Oettinger (R)100.00726563937170727170727161658344690
Rayé
1Jeremy Helvig (R)100.00736361847271737271737263675748690
MOYENNE D'ÉQUIPE100.0075686687747375747375746670634771
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Pascal Vincent72686671736878CAN4741,500,000$


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
1Brandon GignacAdmirals (Nas)C/LW6448200291341230.77%313722.87011221011082054.84%3100001.1700000111
2Chase BalisyAdmirals (Nas)C642611005171761423.53%113622.69101221000050254.84%12400000.8800000010
3Jason PominvilleAdmirals (Nas)RW13254200350760.00%02323.4700001000011066.67%600014.2600000100
4Ethan BearAdmirals (Nas)D614520059101410.00%1014824.72112621011017000.00%000000.6700000001
5Samuel KurkerAdmirals (Nas)RW6235140137213119.52%214123.501012190001100075.00%1200000.7100000000
6Dysin MayoAdmirals (Nas)D6044540377290.00%312921.57011414000010000.00%000000.6200000000
7Tanner KaspickAdmirals (Nas)C6134300107941111.11%014123.50022318000010055.93%5900000.5700000001
8Sam AnasAdmirals (Nas)LW/RW6123100712158186.67%115726.330112200000150047.62%2100000.3800000010
9Jansen HarkinsAdmirals (Nas)C/LW5213-20010111941410.53%113326.650003171011150052.59%11600000.4500000100
10Emil JohanssonAdmirals (Nas)D6033200170130.00%39916.650000200006000.00%000000.6000000010
11Dominik MasinAdmirals (Nas)D602222515646150.00%515025.02000320000012000.00%000000.2700111000
12Brandon HickeyAdmirals (Nas)D6022140829140.00%313121.92000518000010000.00%000000.3000000000
13Joseph GambardellaAdmirals (Nas)C/LW6022200104370.00%38113.6400004000050033.33%600000.4900000000
14Otto SomppiAdmirals (Nas)C6101-1605772814.29%07713.0000002000000060.34%5800000.2600000000
15Ben ThomasAdmirals (Nas)D3000-400351210.00%56822.960000800008000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne81193453195515791071434212813.29%40175721.703693221312321293255.20%43300010.6000111343
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
1Jake OettingerAdmirals (Nas)32100.9002.01179006600000.000031000
2Jeremy HelvigAdmirals (Nas)10100.8753.0060003240000.000013000
Stats d'équipe Total ou en Moyenne42200.8932.26239009840000.000044000


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
Austin PoganskiAdmirals (Nas)LW/RW231996-02-16Yes198 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
Ben ThomasAdmirals (Nas)D231996-05-28No180 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Brandon GignacAdmirals (Nas)C/LW211997-11-07No170 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Brandon HickeyAdmirals (Nas)D231996-04-13Yes201 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
Chase BalisyAdmirals (Nas)C271992-02-02No179 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Dominik MasinAdmirals (Nas)D231996-02-01No198 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
Dysin MayoAdmirals (Nas)D221996-08-17No194 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$NoLien
Emil JohanssonAdmirals (Nas)D231996-05-06No189 Lbs5 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Ethan BearAdmirals (Nas)D221997-06-26No197 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Jacob MiddletonAdmirals (Nas)D231996-01-02No210 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Jake OettingerAdmirals (Nas)G201998-12-18Yes220 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Jansen HarkinsAdmirals (Nas)C/LW221997-05-23No182 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Jason PominvilleAdmirals (Nas)RW361982-11-30No180 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm5,666,000$0$0$NoLien
Jeremy HelvigAdmirals (Nas)G221997-05-25Yes188 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Joseph GambardellaAdmirals (Nas)C/LW251993-12-01No196 Lbs5 ft10NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Louis DomingueAdmirals (Nas)G271992-03-06No210 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm2,500,000$0$0$NoLien
Lukas SedlakAdmirals (Nas)C/LW/RW261993-02-25No205 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Otto SomppiAdmirals (Nas)C211998-01-12Yes192 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Sam AnasAdmirals (Nas)LW/RW261993-06-01No163 Lbs5 ft8NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Samuel KurkerAdmirals (Nas)RW251994-04-08No202 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$0$0$NoLien
Tanner KaspickAdmirals (Nas)C211998-01-28Yes200 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2123.86193 Lbs6 ft03.00755,524$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Austin PoganskiLukas SedlakJason Pominville40122
2Sam AnasJansen HarkinsSamuel Kurker30122
3Brandon GignacChase BalisyJason Pominville20122
4Joseph GambardellaTanner KaspickAustin Poganski10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin40122
2Ben ThomasEthan Bear30122
3Dysin MayoBrandon Hickey20122
4Emil JohanssonJacob Middleton10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Austin PoganskiLukas SedlakJason Pominville60122
2Sam AnasJansen HarkinsSamuel Kurker40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin60122
2Ben ThomasEthan Bear40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Jason PominvilleAustin Poganski60122
2Lukas SedlakSam Anas40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin60122
2Ben ThomasEthan Bear40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Jason Pominville60122Jacob MiddletonDominik Masin60122
2Austin Poganski40122Ben ThomasEthan Bear40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Jason PominvilleAustin Poganski60122
2Lukas SedlakSam Anas40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin60122
2Ben ThomasEthan Bear40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Austin PoganskiLukas SedlakJason PominvilleJacob MiddletonDominik Masin
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Austin PoganskiLukas SedlakJason PominvilleJacob MiddletonDominik Masin
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Otto Somppi, Chase Balisy, Brandon GignacOtto Somppi, Chase BalisyBrandon Gignac
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dysin Mayo, Brandon Hickey, Emil JohanssonDysin MayoBrandon Hickey, Emil Johansson
Tirs de Pénalité
Jason Pominville, Austin Poganski, Lukas Sedlak, Sam Anas, Jansen Harkins
Gardien
#1 : Louis Domingue, #2 : Jake Oettinger


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
1Comets20200000712-51010000057-21010000025-300.000713200015108176939110321053016469333.33%8362.50%014629050.34%14531645.89%7016542.42%2361672476811758
2Griffins21100000810-2110000004311010000047-320.5008152300151081709391103285231638200.00%7271.43%014629050.34%14531645.89%7016542.42%2361672476811758
3IceHogs220000001147110000007251100000042241.00011213200151081679391103247201527400.00%4175.00%014629050.34%14531645.89%7016542.42%2361672476811758
4Rampage201010004401010000012-11000100032120.500471100151081479391103242826231218.33%7271.43%114629050.34%14531645.89%7016542.42%2361672476811758
Total1035011003437-35220010020182513010001419-590.4503462960015108128993911032321938716335617.14%33875.76%114629050.34%14531645.89%7016542.42%2361672476811758
6Wolves2010010047-31000010034-11010000013-210.2504610001510812993911032421214298225.00%70100.00%014629050.34%14531645.89%7016542.42%2361672476811758
_Since Last GM Reset1035011003437-35220010020182513010001419-590.4503462960015108128993911032321938716335617.14%33875.76%114629050.34%14531645.89%7016542.42%2361672476811758
_Vs Conference1035011003437-35220010020182513010001419-590.4503462960015108128993911032321938716335617.14%33875.76%114629050.34%14531645.89%7016542.42%2361672476811758
_Vs Division435011001119-822200100811-32130100038-591.125111930001510811059391103214742307517529.41%15380.00%014629050.34%14531645.89%7016542.42%2361672476811758

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
109W1346296289321938716300
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
103511003437
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
52201002018
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
51310001419
Derniers 10 Matchs
WLOTWOTL SOWSOL
351100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
35617.14%33875.76%1
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
93911032151081
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
14629050.34%14531645.89%7016542.42%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2361672476811758


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
2 - 2019-09-0314Comets7Admirals5LSommaire du Match
4 - 2019-09-0529Admirals4Griffins7LSommaire du Match
6 - 2019-09-0742Griffins3Admirals4WSommaire du Match
7 - 2019-09-0856Admirals2Comets5LSommaire du Match
8 - 2019-09-0966Admirals3Rampage2WXSommaire du Match
10 - 2019-09-1176Admirals4IceHogs2WSommaire du Match
12 - 2019-09-1393Rampage2Admirals1LSommaire du Match
14 - 2019-09-15112Admirals1Wolves3LSommaire du Match
15 - 2019-09-16123Wolves4Admirals3LXSommaire du Match
19 - 2019-09-20151IceHogs2Admirals7WSommaire 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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 158,660$ 38,000$ 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$ 0 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