Dallas Stars
21-38-4, 46pts · 14th in Ouest
STATISTIQUE
Astuces sur les Filtres
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 SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPM PKG PKA PKP PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS
1Mats Zuccarello Stars LW/RW61172239-176036233681687.30%919.222029900002128.09%8900000.6722
2Evander Kane Stars LW63181937-17555191192711519.38%619.337181590001242236.96%9200010.6114
3Joel Armia Stars RW63171734-160014166539710.24%2019.542461570001423130.23%8600010.5511
4Fabian Zetterlund Stars RW63132033-2215570169501207.69%1118.481231300001301038.34%31300000.5701
5Lars Eller Stars C6392130-121203610932768.26%1216.900441420001040153.46%141600000.5613
6Haydn Fleury Stars D6342327-20140318532534.71%7020.0725714500014600-%000000.4300
7Zach Aston-Reese Stars LW/RW63131326-1824094102249512.75%1815.562028000393233.72%8600000.5300
8Dylan DeMelo Stars D6362026-224201867430518.11%10725.1315615300013010-%000000.3300
9Evan Rodrigues Stars C/LW/RW6371825-18404012242845.74%417.7615615700074040.10%134900000.4500
10Jonathan Marchessault Stars LW/RW54101424-111557613647887.35%717.4601156000361028.03%13200000.5113
11Jordan Eberle Stars RW6391524-6001910031769.00%49.030221500000036.84%3800100.8400
12Brent Burns Stars D6351722-1460209224475.43%5916.313581720003320-%000000.4300
13Jamie Drysdale Stars D5941418-14140433492211.76%5814.18011110003400-%000000.4300
14Noah Juulsen Stars D6351217-217152077726566.49%8619.4224614700011311-%000000.2800
15Nick Cousins Stars C/LW/RW6371017-20275778134588.64%714.27000100001028.91%97900000.3800
16Pierre-Olivier Joseph Stars D6301313-1012028253200.00%5312.11011400013400-%000000.3400
17John Klingberg Stars D6321113-12400941761811.76%6813.710000000400-%000000.3000
18Tomas Nosek Stars C/LW50145-719527289223.57%78.38000000000053.44%45100000.2400
19Nicolas Aube-Kubel Stars RW29404-423534174823.53%29.00000000000039.23%13000000.3100
20Michael Pezzetta Stars C/LW10000001001-%013.2500000000000.00%300000.0000
Moyenne d'équipe1136151283434-281399351324185959513118.12%60816.392340631564000118121841.79%516400120.47614
Astuces sur les Filtres
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
1Jacob Ingham Stars 3181610.8923.4715382189822000-0306201
2Pheonix Copley Stars 2371010.8933.4997900575340000.66761230201
3Arturs Silovs Stars 2661220.8923.73122400767050010.37582118101
4Alex Stalock Stars 20000.9063.006000332000-009000
Moyenne d'équipe82213840.8923.5538032122520930010.500146363503
Astuces sur les Filtres
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
# VS Équipe 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 GF% SH% SV% PDO PDOBRK
1SabresSabres1100000042248120012102810117021741820200881207085920914219921.0000.00%100.00%42.56%41.08%42.44%241621713666.7%14.3%90.5%104.8FUN
2BruinsBruins211000005525914002210471620110702084410410881207085920914219920.5000.00%75.00%42.56%41.08%42.44%40275414251155.6%10.6%92.9%103.5LUCKY
3RangersRangers101000000500000000002691070289132200430881207085920914219920.0000.00%25.00%42.56%41.08%42.44%24162161360.0%0.0%82.1%82.1Unlucky
4PredatorsPredators3020100051225914001121793323221119332669701320881207085920914219920.3330.00%84.62%42.56%41.08%42.44%63427922391833.3%6.3%89.9%96.2Unlucky
5Red WingsRed Wings1010000035036900120030910110392381821410881207085920914219920.00050.00%75.00%42.56%41.08%42.44%221425711533.3%10.0%87.2%97.2FUN
6JetsJets31200000811281523003320922531360112361267103600881207085920914219920.33330.00%100.00%42.56%41.08%42.44%63427822371731.3%8.7%90.2%98.9Unlucky
7HurricanesHurricanes10100000350369101110251465028482551430881207085920914219920.00020.00%25.00%42.56%41.08%42.44%221523713650.0%12.0%82.1%94.1FUN
8CapitalsCapitals101000003503580012003281014030881920410881207085920914219920.0000.00%75.00%42.56%41.08%42.44%231523713642.9%9.4%83.3%92.7FUN
9CanadiensCanadiens11000000652610160040203111614028741253210881207085920914219921.00060.00%50.00%42.56%41.08%42.44%221524713642.9%19.4%82.1%101.5FUN
10FlyersFlyers201000014614812002110471314194652763470300881207085920914219920.2500.00%100.00%42.56%41.08%42.44%43295515261240.0%8.5%90.8%99.3Unlucky
11SharksSharks41201000141541425390048111464643561119272369123710881207085920914219920.50025.00%85.71%42.56%41.08%42.44%100728928512544.0%9.6%87.4%97.0FUN
12Black HawksBlack Hawks513000101216412203200722214645564441483746971011320881207085920914219920.40010.00%84.62%42.56%41.08%42.44%1157712137673344.0%8.2%89.2%97.4Unlucky
13AvalancheAvalanche302001007121712190024101013233324101301270120500881207085920914219920.1670.00%100.00%42.56%41.08%42.44%68457623391836.8%6.9%88.1%95.0Unlucky
14DucksDucks3210000055458130131109338282701092828621021430881207085920914219920.66720.00%78.57%42.56%41.08%42.44%61397724401860.0%5.4%95.4%100.8DULL
15OilersOilers2010000159158130031105519152049420204130920881207085920914219920.2500.00%77.78%42.56%41.08%42.44%44305615241141.7%9.1%90.4%99.5FUN
16SenateursSenateurs1100000043247110021102917480351562210310881207085920914219921.0000.00%66.67%42.56%41.08%42.44%211427711566.7%13.8%91.4%105.2LUCKY
17Maple LeafsMaple Leafs10100000120123000010307419026441730200881207085920914219920.0000.00%100.00%42.56%41.08%42.44%201326812633.3%3.3%92.3%95.6DULL
18CanucksCanucks211000004324711003100603414120631444061200881207085920914219920.50016.67%100.00%42.56%41.08%42.44%40275515241250.0%6.7%95.2%101.9DULL
19WildWild32100000784713200023208828283209026186180930881207085920914219920.6670.00%66.67%42.56%41.08%42.44%68447121401958.3%8.0%91.1%99.1DULL
20BluesBlues3110100099491423004311100353429288371465101710881207085920914219920.66710.00%85.71%42.56%41.08%42.44%70497320381950.0%9.0%89.8%98.8FUN
21KingsKings302000015161510150012238119273281042724801101120881207085920914219920.1670.00%81.82%42.56%41.08%42.44%66437723412026.3%6.2%84.6%90.8Unlucky
22Golden KnightsGolden Knights2200000095491625003420732820250552025253100881207085920914219921.00060.00%100.00%42.56%41.08%42.44%48344513251254.5%12.3%90.9%103.2FUN
23FlamesFlames5230000011214112233006230135514242018652371391201630881207085920914219920.4000.00%81.25%42.56%41.08%42.44%1087112735633037.9%8.1%88.7%96.9Unlucky
24DevilsDevils101000003503470011104319915028541552200881207085920914219920.00040.00%100.00%42.56%41.08%42.44%282018712616.7%7.0%82.1%89.1Unlucky
25PanthersPanthers1010000034036900210017103403613171811610881207085920914219920.000100.00%83.33%42.56%41.08%42.44%201326613640.0%17.6%88.9%106.5FUN
26IslandersIslanders10100000160123000010401113160381261540310881207085920914219920.0000.00%66.67%42.56%41.08%42.44%241823711516.7%2.5%84.2%86.7Unlucky
27PenguinsPenguins1010000034034700111032148100281022410100881207085920914219920.0000.00%100.00%42.56%41.08%42.44%231623613642.9%9.4%85.7%95.1FUN
28KrakenKraken6060000013250132538005350152564551020665431291521860881207085920914219920.00013.33%66.67%42.56%41.08%42.44%1288415144803936.7%8.6%87.9%96.4Unlucky
_Vs Division20511021104868174883131001916104606198205195116581991284295755380881207085920914219920.4258.77%84.91%42.56%41.08%42.44%45130250014826212641.7%7.9%89.7%97.6Unlucky
_Vs Conference47132703112114167371142043180147382581401489439460241594452309104113116131250881207085920914219920.39412.21%80.92%42.56%41.08%42.44%1051707118035061329640.8%8.1%89.5%97.7Unlucky
_Since Last GM Reset63173803113157229461572814381165523681858657567620282094616407134417024175380881207085920914219920.36514.12%78.29%42.56%41.08%42.44%1414956157546882039541.0%8.4%89.1%97.5Unlucky
Total63173803113157229461572814381165523681858657567620282094616407134417024175380881207085920914219920.36514.12%78.29%42.56%41.08%42.44%1414956157546882039541.0%8.4%89.1%97.5Unlucky

Puck Time
Offensive Zone 22
Neutral Zone 13
Defensive Zone 25
Puck Time
Offensive Zone Start 2070
Neutral Zone Start 992
Defensive Zone Start 2091
Puck Time
With Puck 28
Without Puck 31
Faceoffs
Faceoffs Won 2161
Faceoffs Lost 2992
Team Average Shots after League Average Shots after
1st Period 10.49.57
2nd Period 19.420.31
3rd Period 29.330.68
Overtime 29.731.4
Goals in Team Average Goals after League Average Goals after
1st Period10.49.57
2nd Period19.420.31
3rd Period29.330.68
Overtime29.731.4
Even Strength Goal132
PP Goal24
PK Goal0
Empty Net Goal1
Home Away
Win 714
Lost 2018
Overtime Lost 31
Win714
Lost2018
Overtime Lost31
Home
Shots For29.5
Shots Against33.2
Goals For2.5
Goals Against3.6
Hits21.3
Shots Blocked9.8
Pim6.5