Buffalo Sabres
19-36-7, 45pts
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
1Brad Marchand Sabres LW6224285212601002387215010.08%916.285914167000194233.04%11200011.0311
2Martin Necas Sabres C/RW62242751-12100622147016211.21%1120.112681910001242138.12%149000000.8204
3Zach Werenski Sabres D62133447-202356214846788.78%11924.616511193000147210.00%100000.6200
4William Nylander Sabres RW62192544-132027231692048.23%718.21257180000211143.00%10000010.7824
5Casey Mittelstadt Sabres C/LW6293140-1401813330996.77%918.40010101800001321252.10%126300000.7000
6Warren Foegele Sabres LW/RW621921401120511784613010.67%917.5555101800001051433.77%23100000.7400
7Denton Mateychuk (R) Sabres D6242428-10220747125395.63%8019.121231190009300-%000000.4700
8Jonas Brodin Sabres D6241923-9300968124484.94%11123.1514518900012200-%000100.3200
9Alexis Lafreniere Sabres LW/RW6271320-1528014710033887.00%1018.27235179000221038.10%8400000.3525
10Morgan Frost Sabres C5471320-7202110039787.00%212.79000200071157.51%23300000.5800
11Troy Stecher Sabres D6241519-22135593261912.50%8216.62000100004300-%000000.3700
12Alexander Romanov Sabres D5041418-184401014614338.70%7716.54303460002900-%000000.4400
13Michael Rasmussen Sabres C629716-1223152968245013.24%1511.7500040001070143.49%92200000.4400
14Jesper Boqvist Sabres LW627916-21300868111438.64%812.23000300041038.89%5400000.4200
15Emil Heineman Sabres LW629514-101406566185413.64%59.77000000002025.00%3600000.4600
16Matthew Nieto Sabres LW/RW625813-21140479521855.26%1212.06000000000026.42%5300000.3500
17Nate Schmidt Sabres D6211112-360101215216351.92%5520.9813416900010700-%000000.1800
18Justin Brazeau Sabres RW62246-1040425918443.39%59.84000000040043.75%3200000.2000
19Victor Soderstrom Americans (BUF) D11101-61001333733.33%815.090000000200-%000000.1200
20Laurent Dauphin Sabres C/LW/RW10000000000-%00.130000000000-%000000.0000
Moyenne d'équipe1108172308480-208371351221199658514468.62%63416.5728528018160001097161343.57%461100120.52514
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
1Joonas Korpisalo Sabres 39141930.9033.3821298012012310120.66793521441
2Jon Gillies Sabres 1841010.8843.799030057491001-01710100
3Zane McIntyre Sabres 181730.8734.5371600544250000.80051031010
Moyenne d'équipe75193670.8923.7037498023121470130.714146262551
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
1BruinsBruins3120000010112101929002440119433937086291648908208762097855202643010250.3330.00%75.00%41.77%42.20%41.95%72526721391852.6%8.4%87.2%95.6Unlucky
2RangersRangers510003101615716274300744216048723941624726991637108762097855202643010250.70018.75%85.71%41.77%42.20%41.95%1127612840683448.1%10.0%90.7%100.7FUN
3Red WingsRed Wings50301100172231732490031121185546363516048191042637208762097855202643010250.30011.54%71.43%41.77%42.20%41.95%1208411837663441.2%9.2%86.3%95.4FUN
4JetsJets10100000030000000000229850286417302008762097855202643010250.0000.00%100.00%41.77%42.20%41.95%22152471360.0%0.0%89.3%89.3Unlucky
5HurricanesHurricanes211000008628152310413057132222076311447417108762097855202643010250.50025.00%85.71%41.77%42.20%41.95%42285113261258.3%14.0%92.1%106.1LUCKY
6CapitalsCapitals211000007927121900016081272232073221734956208762097855202643010250.50055.56%66.67%41.77%42.20%41.95%44304913251322.2%8.6%87.7%96.3Unlucky
7CanadiensCanadiens422000001511415274200564014853445101112823691019108762097855202643010250.50010.00%88.89%41.77%42.20%41.95%101728727502458.3%10.1%90.1%100.2FUN
8LightningLightning413000001114211182900353013941435501323418742259308762097855202643010250.25022.73%66.67%41.77%42.20%41.95%97679029512635.3%7.9%89.4%97.3Unlucky
9FlyersFlyers3030000011150111829004430101333533010141207111110408762097855202643010250.0009.09%60.00%41.77%42.20%41.95%68467121402047.6%10.9%85.1%96.0FUN
10SharksSharks200010018838152300322170272121455201448616108762097855202643010250.75016.67%83.33%41.77%42.20%41.95%49334815281350.0%11.4%85.5%96.9FUN
11Black HawksBlack Hawks10100000130112001000281846032111021305108762097855202643010250.0000.00%80.00%41.77%42.20%41.95%211424814633.3%3.6%90.6%94.2Unlucky
12AvalancheAvalanche10000010322336000111401516753610618703108762097855202643010251.0000.00%66.67%41.77%42.20%41.95%292123712675.0%7.5%94.4%101.9DULL
13DucksDucks11000000642611170005102410104058121021105108762097855202643010251.0000.00%80.00%41.77%42.20%41.95%181228713666.7%25.0%93.1%118.1LUCKY
14SenateursSenateurs504010001023210203000333114843376621896530769013308762097855202643010250.2000.00%76.92%41.77%42.20%41.95%1188311833643133.3%6.8%87.8%94.6Unlucky
15Maple LeafsMaple Leafs5220000110125101727003341151574548415638359016215308762097855202643010250.50012.50%80.00%41.77%42.20%41.95%1208312036643247.1%6.6%92.3%98.9DULL
16KingsKings101000004804610001300291110805914822214008762097855202643010250.00050.00%100.00%41.77%42.20%41.95%201325713627.3%13.8%86.4%100.2FUN
17StarsStars1010000024024610011021513302810412202008762097855202643010250.0000.00%100.00%41.77%42.20%41.95%211424813633.3%9.5%85.7%95.2FUN
18FlamesFlames1010000004000000000023869046151218306208762097855202643010250.0000.00%66.67%41.77%42.20%41.95%19112781360.0%0.0%91.3%91.3DULL
19DevilsDevils303000008140812200061101103828440732327777010308762097855202643010250.0000.00%70.00%41.77%42.20%41.95%78546120402142.1%7.3%80.8%88.1Unlucky
20PanthersPanthers51300010151841526411084211394647444201562810610111608762097855202643010250.40010.00%45.45%41.77%42.20%41.95%1077413536622953.8%10.8%91.0%101.8FUN
21IslandersIslanders412001009183915240053101303749440180452910113311308762097855202643010250.37523.08%72.73%41.77%42.20%41.95%885910128502428.6%6.9%90.0%96.9Unlucky
22PenguinsPenguins2020000041104711002200651729190752714241217308762097855202643010250.0008.33%57.14%41.77%42.20%41.95%48344714241227.3%6.2%85.3%91.5Unlucky
23KrakenKraken1100000021224600110032151070338224401008762097855202643010251.0000.00%100.00%41.77%42.20%41.95%241623612666.7%6.3%97.0%103.2DULL
_Vs Division3171902111881112288159247102736224102933731836415103529816956710212722008762097855202643010250.35511.76%72.22%41.77%42.20%41.95%73851973822239919745.5%8.6%89.3%97.8Unlucky
_Vs Conference521131025211511993615126541620555240617335505755971917755343161020174261303708762097855202643010250.34614.94%71.54%41.77%42.20%41.95%1222850124837567533643.6%8.7%88.8%97.5Unlucky
_Since Last GM Reset621336035321772364517730948630616545820226686736672821506403861221205281644308762097855202643010250.36313.66%73.78%41.77%42.20%41.95%14501004149845380840043.6%8.8%89.0%97.8Unlucky
Total621336035321772364517730948630616545820226686736672821506403861221205281644308762097855202643010250.36313.66%73.78%41.77%42.20%41.95%14501004149845380840043.6%8.8%89.0%97.8Unlucky

Puck Time
Offensive Zone 23
Neutral Zone 13
Defensive Zone 24
Puck Time
Offensive Zone Start 2097
Neutral Zone Start 1025
Defensive Zone Start 2026
Puck Time
With Puck 29
Without Puck 30
Faceoffs
Faceoffs Won 2161
Faceoffs Lost 2987
Team Average Shots after League Average Shots after
1st Period 10.89.57
2nd Period 21.620.31
3rd Period 32.430.68
Overtime 32.831.4
Goals in Team Average Goals after League Average Goals after
1st Period10.89.57
2nd Period21.620.31
3rd Period32.430.68
Overtime32.831.4
Even Strength Goal146
PP Goal28
PK Goal0
Empty Net Goal3
Home Away
Win 118
Lost 1521
Overtime Lost 43
Win118
Lost1521
Overtime Lost43
Home
Shots For32.6
Shots Against34.7
Goals For2.9
Goals Against3.8
Hits19.7
Shots Blocked10.3
Pim6.2