2017-2018 NBA Rest Days Stats

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The teams that take place in today’s slate and their past performance under the same rest day situation are shown in green.
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RANKTEAM NAMEOPPONENT3IN4-B2B
GP3IN4-B2B Games PlayedTotal number of games played in (3rd game -also played yesterday- in 4 nights) situation
3IN4-B2B
W%3IN4-B2B Games Winning PercentagePercentage of games won played in (3rd game -also played yesterday- in 4 nights) situation
3IN4-B2B
AED3IN4-B2B Games Adjusted Efficiency DifferentialEfficiency differential in (3rd game -also played yesterday- in 4 nights) situation
B2B
GPB2B Games PlayedTotal number of games played in (back-to-back) situation
B2B
W%B2B Games Winning PercentagePercentage of games won played in (back-to-back) situation
B2B
AEDB2B Games Adjusted Efficiency DifferentialEfficiency differential in the (back-to-back) situation
3IN4
GP3IN4 Games PlayedTotal number of games played in (3rd game in 4 nights) situation
3IN4
W%3IN4 Games Winning PercentagePercentage of games won played in (3rd game in 4 nights) situation
3IN4
AED3IN4 Games Adjusted Efficiency DifferentialEfficiency differential in the (3rd game in 4 nights) situation
1 DAY
GP1 DAY Games PlayedTotal number of games played in (having one day rest) situation
1 DAY
W%1 DAY Games Winning PercentagePercentage of games won played in (having one day rest) situation
1 DAY
AED1 DAY Games Adjusted Efficiency DifferentialEfficiency differential in the (having one day rest) situation
2 DAYS
GP2 DAYS Games PlayedTotal number of games played in (having two days rest) situation
2 DAYS
W%2 DAYS Games Winning PercentagePercentage of games won played in (having two days rest) situation
2 DAYS
AED2 DAYS Games Adjusted Efficiency DifferentialEfficiency differential in the (having two days rest) situation
3+ DAYS
GP3+ DAYS Games PlayedTotal number of games played in (having three or more days rest) situation
3+ DAYS
W%3+ DAYS Games Winning PercentagePercentage of games won played in (having three or more days rest) situation
3+ DAYS
AED3+ DAYS Games Adjusted Efficiency DifferentialEfficiency differential in the (having three or more days rest) situation
Atlanta
    10
    0.200
    -10.9
    3
    0.000
    -14.2
    6
    0.500
    -4.9
    27
    0.296
    -5.1
    9
    0.333
    -4.7
    5
    0.400
    -6.8
Boston
    9
    0.667
    -0.5
    2
    0.500
    -1.4
    7
    0.714
    3.3
    32
    0.750
    5.0
    6
    0.500
    1.7
    5
    0.600
    7.4
Brooklyn
    7
    0.286
    -15.0
    5
    0.200
    -14.3
    7
    0.429
    -8.5
    24
    0.333
    -7.2
    15
    0.333
    -10.0
    2
    0.000
    -17.0
    Charlotte
    vs. Detroit
    9
    0.333
    -6.8
    2
    0.500
    -0.4
    7
    0.714
    0.6
    28
    0.464
    -1.1
    7
    0.429
    1.6
    6
    0.167
    -7.3
Chicago
    7
    0.143
    -18.8
    3
    0.333
    -24.0
    7
    0.429
    -14.2
    27
    0.370
    -8.8
    10
    0.400
    -12.1
    5
    0.200
    -15.3
    Cleveland
    vs. San Antonio
    3
    1.000
    8.2
    8
    0.375
    -0.9
    3
    0.667
    9.7
    24
    0.708
    5.0
    17
    0.529
    0.5
    3
    0.333
    -3.2
Dallas
    7
    0.143
    -9.0
    4
    0.500
    3.0
    7
    0.143
    -6.9
    28
    0.321
    -1.8
    10
    0.500
    0.5
    4
    0.000
    -9.0
    Denver
    vs. Houston
    8
    0.250
    -1.7
    3
    0.333
    5.8
    6
    0.500
    0.1
    27
    0.630
    8.2
    9
    0.778
    13.0
    6
    0.500
    2.3
    Detroit
    @Charlotte
    6
    0.500
    -6.4
    3
    0.667
    -0.4
    7
    0.429
    -0.6
    28
    0.464
    0.4
    8
    0.375
    -1.5
    6
    0.667
    6.0
Golden State
    7
    0.857
    10.0
    3
    0.333
    -4.1
    6
    0.833
    13.7
    28
    0.857
    15.1
    12
    0.583
    2.5
    4
    0.750
    4.8
    Houston
    @Denver
    4
    0.750
    10.8
    4
    0.500
    2.3
    6
    0.500
    10.0
    30
    0.867
    18.7
    8
    0.625
    13.8
    6
    1.000
    19.2
Indiana
    8
    0.625
    6.9
    4
    0.000
    -8.8
    8
    0.625
    7.4
    23
    0.522
    1.7
    11
    0.636
    6.6
    5
    1.000
    10.3
LA Clippers
    4
    0.250
    -3.4
    5
    0.200
    -3.4
    6
    0.333
    -4.1
    28
    0.679
    2.5
    10
    0.500
    0.2
    5
    0.600
    7.4
LA Lakers
    5
    0.200
    -14.8
    5
    0.400
    -15.9
    5
    0.200
    -22.2
    31
    0.516
    -5.4
    7
    0.429
    -9.8
    6
    0.333
    -9.9
Memphis
    7
    0.143
    -4.7
    5
    0.400
    3.3
    7
    0.714
    -2.7
    22
    0.182
    -7.9
    11
    0.364
    -3.7
    6
    0.333
    -11.6
Miami
    7
    0.429
    -9.8
    4
    0.500
    7.6
    6
    0.500
    0.1
    29
    0.586
    -2.6
    9
    0.444
    -2.3
    5
    0.400
    1.1
    Milwaukee
    vs. New Orleans
    8
    0.750
    6.4
    4
    0.750
    8.4
    6
    0.500
    4.1
    21
    0.571
    1.2
    14
    0.429
    -1.9
    5
    0.600
    7.0
Minnesota
    8
    0.250
    2.7
    3
    1.000
    29.4
    8
    0.750
    16.8
    34
    0.618
    10.1
    6
    0.667
    11.4
    4
    0.250
    -2.4
    New Orleans
    @Milwaukee
    6
    0.333
    -2.2
    3
    0.667
    4.7
    4
    0.500
    -4.2
    32
    0.563
    0.6
    6
    0.833
    3.0
    7
    0.429
    -4.8
New York
    6
    0.500
    1.2
    6
    0.167
    -13.3
    9
    0.333
    -3.4
    26
    0.423
    -2.0
    10
    0.400
    5.1
    4
    0.500
    2.6
Oklahoma City
    10
    0.500
    3.3
    1
    1.000
    12.7
    5
    0.600
    3.3
    31
    0.484
    2.6
    11
    0.727
    15.1
    3
    0.667
    8.1
Orlando
    8
    0.375
    -8.4
    2
    0.500
    5.1
    6
    0.500
    -8.2
    27
    0.185
    -9.8
    11
    0.364
    -11.2
    5
    0.400
    -7.4
    Philadelphia
    @Washington
    6
    0.167
    -12.3
    2
    0.500
    1.9
    6
    0.667
    0.4
    27
    0.630
    0.9
    11
    0.545
    2.4
    5
    0.600
    -3.2
Phoenix
    9
    0.222
    -26.2
    4
    0.500
    -6.2
    9
    0.333
    -12.0
    24
    0.250
    -17.9
    12
    0.417
    -12.0
    3
    0.000
    -35.1
Portland
    9
    0.556
    -2.5
    3
    1.000
    17.3
    6
    0.333
    -7.4
    28
    0.500
    -0.1
    9
    0.667
    3.2
    5
    0.800
    15.4
Sacramento
    7
    0.143
    -16.2
    4
    0.500
    1.0
    6
    0.333
    -2.9
    25
    0.400
    -9.9
    12
    0.167
    -12.9
    5
    0.200
    -9.4
    San Antonio
    @Cleveland
    7
    0.571
    5.0
    5
    0.600
    10.6
    7
    0.857
    14.4
    26
    0.538
    5.6
    12
    0.500
    4.3
    3
    0.667
    20.4
Toronto
    6
    0.667
    18.2
    3
    0.333
    -0.3
    6
    1.000
    23.9
    29
    0.690
    10.5
    9
    0.667
    10.2
    5
    0.800
    17.6
Utah
    7
    0.857
    9.9
    6
    0.500
    -1.0
    8
    0.250
    -8.2
    23
    0.478
    1.1
    11
    0.636
    7.9
    5
    0.400
    2.1
    Washington
    vs. Philadelphia
    4
    0.500
    2.4
    5
    0.600
    9.3
    7
    0.571
    7.5
    28
    0.643
    8.4
    11
    0.364
    -7.0
    4
    0.750
    5.8
Last updated through games completed on February 24, 2018.
Adjusted Efficiency Differential (AED) Explained
In the rest days stats, raw efficiency numbers are adjusted to account for opponent strength and game location (road/home) in an effort to single out the rest days impact more precisely.

The formula for Adjusted Efficiency Differential (AED) = {Expected Efficiency Differential}*- {Actual Efficiency Differential}

“Expected Efficiency Differential” first estimates the pace of game and then the expected offensive and defensive efficiency in related to game venue (road or home) and opponent strength. Let’s say, Warriors have won some games by a higher margin than expected. For that reason, they might have negative (-) average of “adjusted efficiency differential” values under different types of rest days.
NBA Rest Days Explained
For each team, we take team schedules and tag the “game-day”s and “off-day”s. This way, we can analyze the rest days patterns. Let’s code: X as the game-day, and O, as the off-day.
GAME DAYS WITH NO REST:
4IN5-B2B: 4th game in 5 days w/ playing on last 2 consecutive nights. Pattern=…X+X+O+[X+X]
Side note: The NBA avoided scheduling “4IN5” games starting from 2017-18 season!
3IN4-B2B: 3rd game in 4 days w/ playing on last 2 consecutive nights. Pattern=…X+O+[X+X]
B2B: 2nd game in 2 days w/ playing on the last 2 consecutive nights. Pattern=…[X+X]
AT LEAST 1 DAY REST:
3IN4: 3rd game in 4 days and had 1 day rest yesterday. Pattern=…X+X+O+X
1:Had 1 day rest (yesterday) and a playing a game today. Pattern=…O+X
2 :Had 2 days rest and a playing a game a game today. Pattern=…O+O+X
3+: 3 or more days rest and playing a game today. Pattern=…O+O+O+X