Team Stats

2016–17 Regular Season

Coach: Dan Bylsma
Total Players: 39
Related2016–17 game results2016–17 standings
Season Summary

33-37-12, 78 points, a -32 goal differential.

BEST LINE
Moulson–Okposo–O'Reilly, 64.2% of 5v5 xG and 3-1 on goals
BEST PAIR
Gorges–Falk, 65.3% of 5v5 xG and 4-1 on goals
PENALTIES
Drew 298, took 298 (0)
Team Totals
199
231
-32
24.5%
77.6%
49.6%
2.82
6.4%
.929
0.993
GF
GA
DIFF
PP%
PK%
FO%
GAA
S% (5v5)
SV% (5v5)
PDO (5v5)
NHL
24th
19th
24th
1st
25th
17th
19th
27th
6th
23rd
CONF
14th
10th
14th
1st
16th
9th
10th
15th
4th
11th
DIV
7th
5th
7th
1st
8th
6th
5th
8th
2nd
6th
ALL-TIME
15th pct
23rd pct
17th pct
99th pct
14th pct
77th pct
15th pct
97th pct

All-time is where 2016–17 ranks among Sabres regular seasons, as a percentile: GF, GA and DIFF since 1970–71 (55 seasons), PP% and PK% since 1977–78 (48), FO% since 1997–98 (28), S% (5v5) and SV% (5v5) since 2009–10 (17). GF, GA and DIFF are relative to each season's league scoring. Higher is better, GA included.

Moulson–Okposo–O'Reilly
Best Line
64.2% of xG (5.17 to 2.88), 3-1 on goals and 126-146 on attempts in 156:38 together. Okposo and O'Reilly scored 3 goals with the line out. Small sample.
Gorges–Falk
Best D Pair
65.3% of xG (4.51 to 2.39), 4-1 on goals and 111-90 on attempts in 112:26 together. Small sample.
Goal differential
LEAGUE MED +5BUF -32-111+84
One dot per NHL team.
PDO (5v5)
LEAGUE MED 0.999BUF 0.9930.9701.029
One dot per NHL team.
Team Leaders
57
POINTS
+3
PLUS/MINUS
32
QUALITY STARTS

Skater Scatter

Any two stats, one dot per skater. What is xG?

Dot size is ice time per game. Above the dashed line: more Goals than xG. Shaded: ±1 SD of finishing luck. Dotted ring: goals more than 2 SD from xG, past finishing luck.

X axis:
Y axis:
Forwards Defense
0.06.813.520.327.108152330Expected goals (ixG)Goals

36 skaters shown.

More cuts on the Stats Playground scatter.

Goalies: Goals Against vs xGA

Green: fewer goals against than expected. Red: more.

xGAGoals Against
04488131175Anders NilssonAnders Nilsson: 82.1 xGAAnders Nilsson: 66 Goals Against (+16.1 vs expected)66 / 82.1Robin LehnerRobin Lehner: 158.9 xGARobin Lehner: 152 Goals Against (+6.9 vs expected)152 / 158.9Linus UllmarkLinus Ullmark: 3.9 xGALinus Ullmark: 3 Goals Against (+0.9 vs expected)3 / 3.9
Games 1 (Oct 13) to 82 (Apr 9)

82 games.

Expected Goals

Season-to-date xG against goals, game by game. What is xG?

through 82 of 82 games
Drag to zoom

These stats don’t share a natural scale, so each line is normalized to its own 0-100% range for shape comparison. Hover a point for its real value.

-29.2-13.9+1.3Oct 13Oct 30Nov 12Nov 29Dec 16Dec 31Jan 16Feb 2Feb 14Mar 2Mar 16Apr 2vs MTL 1-4 L@ EDM 6-2 W@ CGY 3-4 L@ VAN 1-2 L@ PHI 3-4 Lvs MIN 0-4 Lvs FLA 3-0 W@ WPG 3-1 W@ MIN 2-1 Wvs TOR 1-2 L@ OTT 2-1 W@ BOS 0-4 Lvs OTT 1-2 Lvs NJD 1-2 L@ NJD 2-4 L@ STL 1-4 Lvs TBL 1-4 Lvs PIT 2-1 Wvs CGY 4-2 Wvs DET 1-2 L@ WSH 1-3 L@ OTT 5-4 Wvs NYR 4-3 Wvs BOS 1-2 L@ WSH 2-3 Lvs EDM 4-3 Wvs WSH 1-4 Lvs LAK 6-3 Wvs NYI 3-2 W@ CAR 1-2 L@ FLA 3-4 Lvs CAR 1-3 L@ NYI 1-5 L@ DET 4-3 Wvs BOS 2-4 L@ BOS 1-3 L@ NYR 4-1 W@ CHI 3-4 Lvs WPG 4-3 Wvs PHI 4-1 W@ TBL 2-4 L@ CAR 2-5 Lvs DAL 4-1 W@ TOR 3-4 Lvs DET 3-2 W@ MTL 3-2 W@ NSH 5-4 W@ DAL 3-4 L@ MTL 2-5 Lvs NYR 1-2 Lvs OTT 4-0 W@ NJD 1-2 Lvs SJS 5-4 Wvs ANA 2-5 L@ TOR 3-1 Wvs VAN 2-4 L@ OTT 3-2 Wvs COL 2-0 Wvs STL 3-2 Wvs CHI 1-5 L@ COL 3-5 L@ ARI 2-3 Lvs NSH 4-5 Lvs ARI 6-3 Wvs TBL 1-2 L@ PIT 3-4 Lvs PHI 3-6 L@ CBJ 3-4 Lvs CBJ 5-3 W@ SJS 1-4 L@ LAK 0-2 L@ ANA 2-1 W@ DET 2-1 Wvs PIT 1-3 Lvs TOR 5-2 Wvs FLA 4-2 W@ CBJ 1-3 Lvs NYI 2-4 Lvs TOR 2-4 Lvs MTL 2-1 W@ FLA 0-3 L@ TBL 2-4 LGamexG Differential (cumulative)

Running total, all situations. Ticks under the axis: green won, red lost.

Shot Map

Every BUF shot attempt this season, to scale, attacking right.

xG range
Shot on goal (size = xG)GoalMissed shot×Blocked shot

Win DNA

Yes-or-no box-score traits, and how often the Sabres won with and without each. Correlation, not cause.

How this is measured

Every counting stat runs higher in a win (you score more when you win), so each game gets a yes-or-no question instead, and the win rate when yes is set against the win rate when no. The gap is the lift, in percentage points. A trait can be a symptom of a good night as much as a reason for one. Shot-attempt share (CF%) is left out: in a single game the trailing team piles up attempts, so out-attempting the opponent has gone with a lower win rate.

33-49 in 82 decided games, 2016–17 regular season, with 12 of those losses in overtime or a shootout.
Wins (33)Losses (49, 12 in overtime or a shootout)
3+ scorersxG share 50%+, allGoalie > xGD combined 3+ ptsScored firstMore HD chances, allShot qualityDepth goal50%100%

The wider the gap on an axis, the more that trait separates a win from a loss.

The raw split, wins vs losses

The totals the table above deliberately doesn't lead with. Goals and points from both positions climb in wins, but the defense's share of the offense barely moves, which is why the question is who else scored, not whether the D did.

PER GAMEWINS (33)LOSSES (49)
Forward goals3.331.47
Defense goals0.270.16
Forward points7.303.43
Defense points2.360.88
Different goal scorers3.181.57
D share of points24%20%
D share of shots23%24%

Goal Differential Breakdown

Buffalo finished -32 over 82 games. Biggest pieces: finishing -22.5, goaltending +22.3.

Added goalsCost goalsGoal differentialWhisker: one standard deviation of shot-outcome noise.
-60-40-200Goals0Start-17.5Even-strengthshot volume+4.9Even-strengthshot quality-0.9Penaltydifferential+3.4Power playefficiency-15.7Penalty killefficiency-22.5Finishing+22.3Goaltending-5.0Goaliepulled-1.0Unmodeled-32Goaldifferential
2016–17 REGULAR SEASON, GOALS
COMPONENTGOALSNOISE (ONE SD)REPEATS
Even-strength shot volume-17.5±4.4Usually
Even-strength shot quality+4.9n/aUsually
Penalty differential-0.9n/aSometimes
Power play efficiency+3.4n/aUsually
Penalty kill efficiency-15.7n/aUsually
Finishing-22.5±13.5Sometimes
Goaltending+22.3±14.4Sometimes
Goalie pulled-5.0n/aNot a skill
Unmodeled-1.0n/an/a
Goal differential-32n/an/a

Repeats asks whether a team doing this in one half of a season keeps doing it in the other, league-wide.

How this is measured
Even-strength shot volume
Out-attempting opponents at even strength, with every unblocked attempt priced at the league's average even-strength shot for the season.
Even-strength shot quality
Getting better chances than opponents at even strength, beyond the attempt count.
Penalty differential
Discipline plus drawing: minutes up a skater minus minutes down, priced at the league's net xG per power-play minute.
Power play efficiency
Net xG on the power play above or below league-rate conversion of Buffalo's own power-play minutes, shorthanded chances conceded included.
Penalty kill efficiency
Net xG on the penalty kill above or below league-rate cost of Buffalo's own shorthanded minutes, shorthanded chances created included. Positive means fewer net chances conceded than the league would have.
Finishing
Goals scored above or below what Buffalo's chances were worth, goalie in the net.
Goaltending
Goals allowed below or above what opponents' chances were worth, goalie in the net.
Goalie pulled
Net goals with a goalie pulled: into an empty net, or by the extra attacker. Follows who was trailing late, not a skill of its own.
Unmodeled
Goals on shots the model could not score, plus any goal the shot list is missing.
  • 199 for, 231 against, regulation and overtime; the rows sum to the goal differential before rounding.
  • Built from 82 of 82 games with xG data; the official goal differential was -32.
  • Even-strength volume is priced at the league's average even-strength attempt for the season (0.0571 xG in 2016-17), and penalty differential at the league's net xG per power-play minute (0.081), both measured over every game in the league with the same model. Over the games covered, Buffalo's own games averaged 0.0600 xG per even-strength attempt; quality is what remains of the even-strength xG gap after volume.
  • Power-play and shorthanded minutes are read from the situation code on each play, both goalies in, which runs slightly above the official power-play figure because a penalty that expires between two plays is credited to the earlier state. The league rate per minute is priced on the same clock, so the two cancel.
  • Regulation and overtime goals only. A shootout's deciding goal is not a shot the model sees and is left out.
  • Shots at an empty net, and shots by a team with its own goalie pulled, count only as actual goals in the goalie-pulled bar. Both depend on who was trailing late, so they stay out of finishing, goaltending, special teams and even strength.
  • Goaltending leaves out shots taken while the opponent's goalie was pulled; those count only under Goalie pulled. The Goalies table's GSAx counts every shot faced, so it reads +23.9 against +22.3 here.
  • Whiskers on finishing and goaltending are one standard deviation of shot-outcome noise, each shot a coin flip weighted at its xG. The volume whisker is a Poisson approximation from the attempt counts. Quality, the three special-teams bars, goalie pulled and unmodeled carry no whisker.
  • Repeats asks how much of a component carries from one half of a team's season to the other, measured league-wide over 2016-17 to 2025-26 (314 team-seasons) with the same model: a split-half correlation, corrected to full-season length. Usually is 0.6 and above, sometimes 0.3 to 0.6, rarely below 0.3. Even a full season of finishing is about one third signal and two thirds shot-outcome luck.

Line Combinations

Lines and pairs at 5v5 this season, summed over every game together. 82 of 82 games have shift data.

What do TOI, CF, xG% etc. mean?
GP
Games in which this exact line/pair shared the ice together at 5v5.
TOI
Time on ice together at 5v5, meaning the whole line/pair on the ice at once, not any one player's own total. Only the seconds that exact pair or trio was the unit count, which is why a pair's TOI and xG% here differ slightly from the WOWY table, where together counts every 5v5 second the two share, whoever else is on the ice.
xGF / xGA
Expected goals for/against while this combo was on the ice, from this site's own xG model.
xG%
Share of on-ice expected goals this combo earned: xGF / (xGF + xGA). The single best read on who controlled play.
GF / GA
Actual goals for/against while this combo was on the ice together.
CF / CA (Corsi For / Against, Shot Attempts)
"Corsi" is just the hockey-analytics name for total shot attempts: shots on goal, missed shots, and blocked shots combined, a volume proxy for who had the puck more. CF is this combo's own attempts, CA is the opponent's.
CF%
Share of on-ice shot attempts (Corsi) this combo earned: CF / (CF + CA).
CF% Rel
This combo's CF% minus the team's own CF% in the minutes this exact combo was NOT on the ice. Positive means the combo lifted the team's play; negative means it dragged it down.
xGF% Rel
This combo's xG% minus the team's own xG% in the minutes this exact combo was NOT on the ice. Positive means the combo lifted the team's expected-goals share; negative means it dragged it down.
FF / FA
Unblocked shot attempts (also called Fenwick): shots on goal plus misses, excluding blocks. One layer closer to real scoring chances than CF/CA.
SF / SA
Shots on goal for/against while this combo was on the ice together.
Minimum Ice Time
Drag the slider on each table down to see combos with less shared ice time. Their percentages get noisier the lower you go, since a combo that barely played together can swing to 100% or 0% off a single shot.
STRENGTH
Forward Lines
Best at 5v5: Moulson–Okposo–O'Reilly, 64.2% of xG and 3-1 on goals (min 100:00 together and 0.25 xG, half that with a goal; units ahead on goals rank first, then the best mix of xG share and on-ice goals, weighted two to one).
LineGPTOIxGFxGAxG%GFGACFCACF%CF% RelxGF% RelFFFASFSA
Gionta–Foligno–Larsson28269:187.327.1750.5%12722025046.8%-0.5%2.3%168183121142
Foligno–Reinhart–Eichel29213:057.736.2455.3%7621719752.4%5.5%7.4%178153124114
Moulson–Okposo–O'Reilly25156:385.172.8864.2%3112614646.3%-1.0%16.4%1001137973
Gionta–Kane–Girgensons23146:444.595.2446.7%4513215745.7%-1.6%-1.7%1031226876
Kane–Reinhart–Eichel20141:425.204.9151.4%6714114948.6%1.4%3.2%1051088273
Okposo–Ennis–O'Reilly17116:253.793.4052.7%729412343.3%-4.1%4.5%69935570
Gionta–O'Reilly–Kane17108:354.812.7663.6%331039851.2%4.1%15.8%79755854
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Defense Pairs
Best at 5v5: Gorges–Falk, 65.3% of xG and 4-1 on goals (min 100:00 together and 0.25 xG, half that with a goal; units ahead on goals rank first, then the best mix of xG share and on-ice goals, weighted two to one).
LineGPTOIxGFxGAxG%GFGACFCACF%CF% RelxGF% RelFFFASFSA
McCabe–Ristolainen58617:2818.2921.6045.9%293254965045.8%-1.7%-2.9%425505301378
Gorges–Ristolainen54429:3413.9213.2151.3%91434047441.8%-6.1%3.4%268360200250
Franson–McCabe51327:278.9310.9245.0%131129230149.2%2.1%-3.6%223238158173
Kulikov–Ristolainen35285:287.788.9346.6%6925032043.9%-3.6%-1.8%182244136176
Franson–Bogosian25269:0410.229.8151.0%81526126649.5%2.4%2.9%206198145139
Falk–Fedun23208:495.545.5450.0%8519416853.6%6.7%1.8%1381309791
Gorges–Franson33204:105.145.8446.8%7616315651.1%4.0%-1.6%13011110088
Bogosian–Kulikov26203:536.316.9047.8%31018120047.5%0.3%-0.5%13915495110
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With or Without You

Buffalo's 5v5 CF% and xGF% with Ristolainen on the ice, with and without each teammate. Δ is together minus apart. That gap is always measured from the named player's side, so the same pair can read positive on one player's table and negative on the other's. 2016–17 regular season, minimum 20:00 together. Together counts every 5v5 second the two share, whoever else is on the ice, so a pair's time and xGF% here differ slightly from the Line Combinations table, which counts only the seconds that exact pair or trio was the unit. 82 of 82 games have shift data.

Teammate
TOGETHER
RISTOLAINEN APART
IMPACT
TOI TogetherCF%xGF%CF%xGF%Δ CF%Δ xGF%
McCabe
618:3245.7%45.5%
42.3%49.6%
+3.4-4.1
O'Reilly
466:2748.1%53.7%
41.7%45.2%
+6.4+8.5
Gionta
445:0540.2%45.7%
45.2%48.7%
-5.0-3.0
Foligno
437:1143.0%49.1%
44.0%47.5%
-1.0+1.6
Gorges
430:5941.6%51.0%
44.6%46.7%
-3.0+4.3
Okposo
389:3544.0%51.5%
43.6%46.6%
+0.4+4.9
Kane
375:5044.3%49.4%
43.5%47.4%
+0.8+2.0
Reinhart
368:2942.9%46.6%
44.0%48.4%
-1.1-1.8
Eichel
327:5142.5%43.1%
44.1%49.4%
-1.6-6.3
Girgensons
292:3746.2%53.8%
43.2%46.5%
+3.0+7.3
Kulikov
286:1743.5%46.4%
43.8%48.2%
-0.3-1.8
Moulson
253:4748.4%55.6%
42.8%46.0%
+5.6+9.6
Larsson
249:5741.2%47.4%
44.2%48.0%
-3.0-0.6
Ennis
182:3044.8%43.5%
43.6%48.4%
+1.2-4.9
Bailey
135:2838.1%37.9%
44.3%48.8%
-6.2-10.9
Carrier
132:0151.7%48.6%
42.9%47.8%
+8.8+0.8
Deslauriers
102:4436.0%36.3%
44.3%48.8%
-8.3-12.5
Grant
90:1933.5%38.8%
44.4%48.6%
-10.9-9.8
Rodrigues
88:5045.7%39.5%
43.6%48.4%
+2.1-8.9
Bogosian
53:3038.5%45.7%
44.0%48.0%
-5.5-2.3
Falk
52:5042.2%53.1%
43.8%47.6%
-1.6+5.5
Baptiste
39:0438.8%39.9%
43.9%48.1%
-5.1-8.2
Fasching
27:5453.7%52.0%
43.6%47.8%
+10.1+4.2
Fedun
21:1841.5%63.7%
43.8%47.6%
-2.3+16.1

Shift Profile

Shift length and on-ice results, 2016–17 regular season. Empty-net goals against are left out. 82 of 82 games have shift data.

What do Short %, Hemmed-In Shifts, Long-Change Gap etc. mean?
GP (shifts)
Games in which the NHL shift chart has rows for this skater. It can read lower than the games played in the Skaters table, because a game with no usable shift chart is left out of every column here.
Short / Long
"Short" is a skater's shifts under 0:45; "Long" is their shifts of 1:00 or more. Short % / Long % is the share of all their shifts that fall in that range.
CF% (short) / CF% (long)
Shot-attempt share (Corsi) specifically during a skater's own short shifts versus their own long shifts. Compares whether they generate or allow more when the shift is quick versus when it drags on.
GF-GA (long)
Goals for minus goals against specifically during a skater's shifts of 1:00 or more. A single-game or short-series number here is a very small sample; look for it to hold up across a season.
PP Shifts / PK Shifts
Number of shifts a skater started while their team had a power play or was shorthanded, tagged by the strength in effect at the moment they stepped on the ice.
Long-Change Gap
This skater's average 2nd-period shift length minus the average of their 1st and 3rd. Positive means their shifts really do run longer in the 2nd, but that period is the "long change" (the bench sits at center ice, so whichever team is defending the far end can't change on the fly as easily), so a positive gap isn't automatically fatigue.
Hemmed-In Shifts
Even-strength shifts in which the unit was on for more than 60 seconds of unbroken play: no whistle came, so they could not change. The number in parentheses is how many of those only ended at a whistle. Most of such a shift is ordinary play: the first minute looks like any other stretch of the game, and only the time past it tilts hard toward the defending end (the game page counts that as pinned time). Shift length is an outcome here, not a cause, so this column says nothing about why a goal went in.
Short-Rest Shifts
Even-strength shifts a skater started after less than 45 seconds on the bench, same period only (an intermission is a full rest). Power-play and penalty-kill units legitimately take long shifts and short rests, so both of these columns leave them out.
PlayerGP (shifts)ShiftsAvg ShiftShort %Long %CF% (short)CF% (long)GF-GA (long)PP ShiftsPK ShiftsLong-Change GapHemmed-In ShiftsShort-Rest Shifts
R. Ristolainen7923410:5438.6%33.7%42.0%49.0%+15200268+5s296 (79 to whistle)340
J. McCabe7620360:4648.1%23.3%44.3%44.0%-5108208+3s251 (64 to whistle)275
R. O'Reilly7218330:5140.8%29.5%49.7%52.7%-2155264+2s186 (34 to whistle)121
J. Gorges6617230:4260.4%15.0%42.8%30.1%-336220+3s123 (25 to whistle)184
B. Gionta8216870:4842.9%27.7%42.3%44.3%-4172225+2s227 (59 to whistle)42
C. Franson6816480:4649.4%23.1%50.1%48.7%+5139111+2s181 (45 to whistle)149
M. Foligno8015920:4745.3%24.5%48.1%40.5%+166182+4s243 (52 to whistle)67
S. Reinhart7915920:5138.3%31.5%54.6%59.6%+817453+3s233 (46 to whistle)67
E. Kane7015740:5139.3%33.7%43.8%51.8%-5156156+2s277 (86 to whistle)77
K. Okposo6514430:5137.7%29.4%53.7%57.2%+12163480s163 (36 to whistle)72
Z. Bogosian5614240:4747.3%25.9%46.8%43.9%-855153+4s190 (47 to whistle)182
Z. Girgensons7513660:4351.6%17.9%38.8%41.8%-351156+1s160 (28 to whistle)42
J. Eichel6113430:5434.3%38.1%53.4%55.6%+712288+2s258 (56 to whistle)73
D. Kulikov4713150:4748.6%24.1%42.4%43.6%-171136+6s161 (36 to whistle)196
M. Moulson8111620:4940.7%24.0%58.3%61.3%+918718+1s121 (23 to whistle)21
J. Falk5210790:4062.8%12.5%53.8%40.4%-51979+4s72 (13 to whistle)82
T. Ennis518090:4939.6%26.2%46.4%56.9%09118+4s119 (23 to whistle)29
J. Larsson367620:4843.8%27.8%46.1%41.0%-54971+1s114 (38 to whistle)33
D. Grant406070:3961.3%11.4%34.5%27.9%-222167+4s21 (2 to whistle)16
W. Carrier415830:3867.8%7.5%52.9%40.4%01316+1s26 (6 to whistle)15
T. Fedun275280:4159.3%13.6%61.8%49.3%-14712+1s32 (6 to whistle)37
E. Rodrigues305060:4648.0%21.3%45.2%35.4%-22455+3s71 (16 to whistle)13
J. Bailey324680:4451.3%14.7%47.9%33.8%-1133+2s41 (7 to whistle)21
N. Deslauriers424200:4445.7%22.1%38.5%39.0%-31590s66 (14 to whistle)8
C. Nelson112170:3868.2%13.4%56.3%42.6%056+6s16 (5 to whistle)23
N. Baptiste141900:4155.8%12.6%49.4%31.7%0208+5s14 (4 to whistle)3
H. Fasching101450:4350.3%13.8%47.6%37.5%0512+1s14 (3 to whistle)3
B. Austin51260:3864.3%11.9%50.6%45.8%+2011+1s9 (1 to whistle)19
C. O'Reilly111140:4649.1%19.3%48.3%56.1%+1130+3s9 (1 to whistle)1
B. Guhle3710:4159.2%15.5%51.4%21.4%010+2s6 (2 to whistle)8
A. Nylander4620:4840.3%25.8%48.5%50.0%-141-1s92
C. Schneider4450:3860.0%13.3%37.5%57.1%000+4s31
E. Burgdoerfer2340:3964.7%17.6%61.1%42.9%000-19s6 (1 to whistle)3
C. Smith2300:4646.7%23.3%38.9%35.0%-110-12s41
S. Malone1150:4940.0%33.3%50.0%71.4%030+6s30

Skaters

PlayerNo.GPGAPTS+/-PIMPPSHGWGSOGG/60A/60P/60SOG/60S%FO%TOI/GxGxG/60GAx
Jack Eichel961243357-132210042491.191.632.8112.299.6%38.9%19:5521.51.06+2.5
Ryan O'Reilly9072203555-1108131890.781.362.147.3410.6%58.0%21:2821.10.82-1.1
Sam Reinhart2379173047-1189031780.751.322.077.859.6%40.9%17:1325.11.11-8.1
Kyle Okposo2165192645-7247021560.921.272.197.5912.2%54.5%18:5820.10.98-1.1
Rasmus Ristolainen557963945-9581021860.171.121.295.343.2%0.0%26:2810.40.30-4.4
Evander Kane970281543-171133052601.250.671.9211.6110.8%45.1%19:1221.00.94+7.0
Brian Gionta1282152035-11223131490.660.881.546.5710.1%43.4%16:3613.80.61+1.3
Matt Moulson81141832-41011021340.891.152.048.5510.4%25.0%11:3615.10.96-1.1
Marcus Foligno8280131023-173010970.630.481.114.7013.4%20.0%15:2812.70.62+0.3
Jake McCabe197631720-726101790.110.650.763.013.8%0.0%20:424.70.18-1.7
Cody Franson66831619-534100930.140.760.914.443.2%0.0%18:293.80.18-0.8
Zemgus Girgensons28757916-7180001120.430.550.976.816.3%47.1%13:1010.90.66-3.9
Tyler Ennis63515813-1012001890.460.731.198.165.6%18.8%12:507.90.72-2.9
Zach Bogosian4562911-1746001730.110.480.593.892.7%0.0%20:053.30.17-1.2
Johan Larsson22366511-720102490.590.491.094.8512.2%49.0%16:517.10.70-1.1
Justin Falk4152088-329000330.000.670.672.780.0%0.0%13:421.60.14-1.6
William Carrier4841538-121001500.810.491.308.1310.0%50.0%9:004.30.71+0.7
Taylor Fedun2727077+316000240.001.161.163.990.0%0.0%13:220.70.12-0.7
Josh Gorges466156-350000400.050.250.301.972.5%0.0%18:271.50.07-0.5
Evan Rodrigues7130426-74100510.620.310.937.897.8%41.6%12:563.60.55+0.4
Dmitry Kulikov7747235-2626100420.120.170.292.454.8%0.0%21:542.50.14-0.5
Justin Bailey953222404001360.350.350.716.355.6%0.0%10:382.90.51-0.9
Nick Baptiste1314314+16000161.390.461.867.4218.8%33.3%9:141.60.72+1.4
Derek Grant2735033-319000310.000.500.505.210.0%52.6%10:124.30.72-4.3
Nicolas Deslauriers4442022-638000260.000.390.395.010.0%0.0%7:252.00.38-2.0
Cal O'Reilly1911011-6000030.000.690.692.060.0%48.5%7:560.10.07-0.1
Cole Schneider104011+2000060.002.102.1012.600.0%0.0%7:090.10.17-0.1
Hudson Fasching2410011-1200060.000.580.583.460.0%0.0%10:251.20.70-1.2
Alex Nylander924011-2000040.001.221.224.870.0%0.0%12:200.30.32-0.3
C.J. Smith492011-1000020.002.602.605.200.0%0.0%11:320.20.49-0.2
Derek Grant2750000000030.000.000.004.540.0%46.4%7:564.36.44-4.3
Erik Burgdoerfer462000-1000020.000.000.005.370.0%0.0%11:100.00.080.0
Brady Austin6750000400080.000.000.005.970.0%0.0%16:050.10.08-0.1
Sean Malone4310000000010.000.000.004.920.0%62.5%12:120.20.89-0.2
Brendan Guhle453000+1000040.000.000.004.890.0%0.0%16:210.10.12-0.1
Casey Nelson811000-34000100.000.000.004.330.0%0.0%12:360.20.08-0.2
Total1993315307195733124918.0%

Goalies

PlayerNo.GPWLOTLGAASV%SOxGAGSAx
Robin Lehner4059232682.68.9202158.9+6.9
Anders Nilsson3126101042.67.923182.1+16.1
Linus Ullmark3510103.06.91703.9+0.9
Total3337123

A goalie is credited a game played for any appearance, relief included, so GP sums above the team's own games played by the number of relief outings. The Total row leaves GP out for that reason.

xG by Game

DateOpponentScorexG ForxG AgainstxG DiffGoal DiffGD vs xG Diff
Oct 13vs MTL1-42.402.89-0.49-3-2.51
Oct 16@ EDM6-23.223.44-0.22+4+4.22
Oct 18@ CGY3-43.524.31-0.79-1-0.21
Oct 20@ VAN1-23.542.51+1.03-1-2.03
Oct 25@ PHI3-42.674.55-1.880+1.88
Oct 27vs MIN0-43.582.76+0.82-4-4.82
Oct 29vs FLA3-01.802.18-0.38+3+3.38
Oct 30@ WPG3-14.072.44+1.63+2+0.37
Nov 1@ MIN2-11.891.78+0.11+1+0.89
Nov 3vs TOR1-23.562.09+1.47-1-2.47
Nov 5@ OTT2-11.832.14-0.31+1+1.31
Nov 7@ BOS0-42.724.14-1.42-4-2.58
Nov 9vs OTT1-23.092.12+0.970-0.97
Nov 11vs NJD1-22.003.96-1.96-1+0.96
Nov 12@ NJD2-41.672.48-0.81-2-1.19
Nov 15@ STL1-42.763.52-0.76-3-2.24
Nov 17vs TBL1-42.002.61-0.61-3-2.39
Nov 19vs PIT2-12.593.78-1.190+1.19
Nov 21vs CGY4-22.331.78+0.55+2+1.45
Nov 23vs DET1-23.662.40+1.260-1.26
Nov 25@ WSH1-32.753.75-1.00-2-1.00
Nov 29@ OTT5-43.043.32-0.28+1+1.28
Dec 1vs NYR4-32.612.38+0.23+1+0.77
Dec 3vs BOS1-22.281.80+0.48-1-1.48
Dec 5@ WSH2-33.733.14+0.59-1-1.59
Dec 6vs EDM4-31.934.42-2.49+1+3.49
Dec 9vs WSH1-42.232.75-0.52-3-2.48
Dec 13vs LAK6-31.901.58+0.32+3+2.68
Dec 16vs NYI3-22.812.04+0.77+1+0.23
Dec 17@ CAR1-22.122.89-0.770+0.77
Dec 20@ FLA3-43.494.47-0.980+0.98
Dec 22vs CAR1-31.843.39-1.55-2-0.45
Dec 23@ NYI1-52.223.44-1.22-4-2.78
Dec 27@ DET4-32.543.54-1.00+1+2.00
Dec 29vs BOS2-43.754.22-0.47-2-1.53
Dec 31@ BOS1-33.372.50+0.87-2-2.87
Jan 3@ NYR4-12.012.29-0.28+3+3.28
Jan 5@ CHI3-42.023.77-1.75-1+0.75
Jan 7vs WPG4-33.162.29+0.87+1+0.13
Jan 10vs PHI4-13.272.90+0.37+3+2.63
Jan 12@ TBL2-42.172.85-0.68-2-1.32
Jan 13@ CAR2-53.724.27-0.55-3-2.45
Jan 16vs DAL4-14.232.43+1.80+3+1.20
Jan 17@ TOR3-42.782.84-0.06-1-0.94
Jan 20vs DET3-24.432.59+1.84+1-0.84
Jan 21@ MTL3-22.853.18-0.33+1+1.33
Jan 24@ NSH5-43.713.02+0.69+1+0.31
Jan 26@ DAL3-41.873.27-1.40-1+0.40
Jan 31@ MTL2-53.643.67-0.03-3-2.97
Feb 2vs NYR1-23.974.63-0.66-1-0.34
Feb 4vs OTT4-02.532.14+0.39+4+3.61
Feb 6@ NJD1-21.304.53-3.23-1+2.23
Feb 7vs SJS5-42.824.06-1.24+1+2.24
Feb 9vs ANA2-51.953.25-1.30-3-1.70
Feb 11@ TOR3-12.033.78-1.75+2+3.75
Feb 12vs VAN2-42.623.61-0.99-2-1.01
Feb 14@ OTT3-22.202.83-0.63+1+1.63
Feb 16vs COL2-01.941.36+0.58+2+1.42
Feb 18vs STL3-23.252.62+0.63+1+0.37
Feb 19vs CHI1-52.842.85-0.01-4-3.99
Feb 25@ COL3-52.913.13-0.22-2-1.78
Feb 26@ ARI2-32.702.27+0.43-1-1.43
Feb 28vs NSH4-52.483.49-1.01-1+0.01
Mar 2vs ARI6-34.491.57+2.92+3+0.08
Mar 4vs TBL1-21.882.50-0.620+0.62
Mar 5@ PIT3-43.765.11-1.35-1+0.35
Mar 7vs PHI3-62.442.74-0.30-3-2.70
Mar 10@ CBJ3-41.733.82-2.09-1+1.09
Mar 11vs CBJ5-33.732.26+1.47+2+0.53
Mar 14@ SJS1-41.933.43-1.50-3-1.50
Mar 16@ LAK0-22.324.36-2.04-2+0.04
Mar 17@ ANA2-12.645.25-2.610+2.61
Mar 20@ DET2-12.733.78-1.05+1+2.05
Mar 21vs PIT1-32.593.00-0.41-2-1.59
Mar 25vs TOR5-24.083.05+1.03+3+1.97
Mar 27vs FLA4-23.083.37-0.29+2+2.29
Mar 28@ CBJ1-32.633.28-0.65-2-1.35
Apr 2vs NYI2-42.601.97+0.63-2-2.63
Apr 3vs TOR2-42.043.42-1.38-2-0.62
Apr 5vs MTL2-13.582.13+1.45+1-0.45
Apr 8@ FLA0-32.643.74-1.10-3-1.90
Apr 9@ TBL2-41.974.76-2.79-2+0.79

All situations. GD vs xG Diff is goal differential minus xG differential. Both difference columns are taken from the values printed beside them, so each row adds up as shown.