This is the same scenario as this but with weights applied to each number to account for their percent within the total population of occurences within the sample.
Our Criteria here: Win - a given team wins the game if they were losing/tied (in this order) in extra innings, 9th, 8th or 7th inning. Loss - a given team loses the game when they were winning/tied in extra innings, 9th, 8th, or 8th inning.
ZScore: is based on the population standard deviation and mean here. It tells you how many standard deviations from the mean you are. For wins, a positive ZScore is what you want as that relfects "you came back to win more than others". So 1.5 is better than 0.5. For the loss, a negative ZScore is what you want as that reflects "you did not lose your leads like others around the mean". So -1.5 is better than -0.5
"Which team in the AL had the BEST improvement between the first half of the season and the second half of the season between 2003 and 2019 with late inning rallies and late inning losses.
From July to the end of regular season:
2nd half inn Rally wins: Anaheim Angels: 1.14
If you look at the data below, you'll see Texas is influenced by the fact that they lost a lot less in the late innings in the 2nd half.
If you want to see the significance again of the ZScore and what it can be telling you, please see:
https://baseballfan999.wixsite.com/baseballdat/post/what-does-the-zscore-tell-you Note: We did take the league change where the Houston switched leagues after 2012 so their figures from 2013 on were not included. We also treat Montreal as WSH.
The figures based on this time frame 2003-2019
Green: Most improved "devil magic" AL team in the 2nd half in this study
Second Half ZScore improvement over First Half:
Team ZScoreImprovement
25 SLN 2.315956
9 COL 1.979303
18 NYN 1.420010
0 ANA 1.136570
14 MIA 1.024799
27 TEX 1.018952
19 OAK 0.940428
17 NYA 0.540984
20 PHI 0.453258
8 CLE 0.411754
29 WAS 0.383953
16 MIN 0.304716
7 CIN 0.273005
26 TBA 0.243325
21 PIT -0.053742
6 CHN -0.076383
10 DET -0.114353
12 KCA -0.252776
4 BOS -0.273139
15 MIL -0.675979
13 LAN -0.719267
11 HOU -0.792323
24 SFN -0.805687
23 SEA -0.966879
1 ARI -1.070192
28 TOR -1.104966
2 ATL -1.317827
3 BAL -1.389925
22 SDN -1.406904
5 CHA -1.426672
Team ZScoreImprovement 2ndHalfImprovement 1stHalfImprovement
25 SLN 2.315956 2.273758 -0.825264
9 COL 1.979303 0.133391 -2.817947
18 NYN 1.420010 -0.294682 -2.479019
0 ANA 1.136570 1.902572 0.509576
14 MIA 1.024799 -0.684394 -2.341295
27 TEX 1.018952 0.504141 -0.945771
19 OAK 0.940428 2.193548 1.143103
17 NYA 0.540984 2.022668 1.542501
20 PHI 0.453258 0.360724 -0.265117
8 CLE 0.411754 -0.063862 -0.698300
29 WAS 0.383953 -0.486704 -1.149989
16 MIN 0.304716 1.003705 0.707768
7 CIN 0.273005 0.356364 0.000000
26 TBA 0.243325 -0.067786 -0.450398
21 PIT -0.053742 -0.063426 0.000000
6 CHN -0.076383 -1.272886 -1.377233
10 DET -0.114353 -0.431779 -0.338928
12 KCA -0.252776 -1.129904 -0.945987
4 BOS -0.273139 1.342633 1.969443
15 MIL -0.675979 -0.976460 -0.132559
13 LAN -0.719267 1.296207 2.584033
11 HOU -0.792323 -1.569311 -0.649882
24 SFN -0.805687 0.741064 2.065849
23 SEA -0.966879 -1.294682 -0.067786
1 ARI -1.070192 -1.621622 -0.294383
28 TOR -1.104966 -1.877289 -0.540564
2 ATL -1.317827 0.800349 2.902733
3 BAL -1.389925 -1.147123 0.738541
22 SDN -1.406904 -0.555144 1.454702
5 CHA -1.426672 -1.307759 0.606198
Team Disp1stHalfLIW Disp1stHalfLIL Disp2ndHalfLIW Disp2ndHalfLIL
25 SLN 141 154 179 147
9 COL 123 168 154 152
18 NYN 142 178 167 171
0 ANA 152 144 165 136
14 MIA 143 177 152 162
27 TEX 139 154 133 124
19 OAK 174 158 165 131
17 NYA 142 114 161 129
20 PHI 152 156 168 163
8 CLE 142 153 146 147
29 WAS 159 175 156 163
16 MIN 155 144 161 146
7 CIN 162 162 166 161
26 TBA 146 153 155 156
21 PIT 157 157 145 146
6 CHN 150 170 136 156
10 DET 155 160 138 145
12 KCA 150 164 135 153
4 BOS 159 127 164 144
15 MIL 153 155 153 167
13 LAN 177 139 166 147
11 HOU 146 156 138 162
24 SFN 175 145 175 165
23 SEA 157 158 156 174
1 ARI 169 173 143 167
28 TOR 153 161 146 173
2 ATL 185 144 159 147
3 BAL 149 137 129 148
22 SDN 179 159 137 146
5 CHA 161 152 140 160
Weighted..
Team 1stHalfLIW 1stHalfLIL 2ndHalfLIW 2ndHalfLIL
25 SLN 4.278244 5.103508 6.983653 4.709895
9 COL 3.255649 6.073596 5.169137 5.035745
18 NYN 4.339144 6.818162 6.078684 6.373365
0 ANA 4.971810 4.462234 5.933958 4.031386
14 MIA 4.400473 6.741769 5.035745 5.720139
27 TEX 4.157736 5.103508 3.855493 3.351351
19 OAK 6.515171 5.372068 5.933958 3.740410
17 NYA 4.339144 2.796643 5.649738 3.627071
20 PHI 4.971810 5.236927 6.151700 5.790976
8 CLE 4.339144 5.037444 4.646033 4.709895
29 WAS 5.440284 6.590273 5.304272 5.790976
16 MIN 5.170002 4.462234 5.649738 4.646033
7 CIN 5.647515 5.647515 6.006103 5.649738
26 TBA 4.587045 5.037444 5.236486 5.304272
21 PIT 5.304282 5.304282 4.582607 4.646033
6 CHN 4.841833 6.219066 4.031386 5.304272
10 DET 5.170002 5.508930 4.150828 4.582607
12 KCA 4.841833 5.787820 3.972319 5.102223
4 BOS 5.440284 3.470841 5.862249 4.519616
15 MIL 5.037444 5.170002 5.102223 6.078684
13 LAN 6.741769 4.157736 6.006103 4.709895
11 HOU 4.587045 5.236927 4.150828 5.720139
24 SFN 6.590273 4.524424 6.675022 5.933958
23 SEA 5.304282 5.372068 5.304272 6.598954
1 ARI 6.146116 6.440499 4.457062 6.078684
28 TOR 5.037444 5.578007 4.646033 6.523322
2 ATL 7.364967 4.462234 5.510244 4.709895
3 BAL 4.777491 4.038950 3.627071 4.774194
22 SDN 6.894986 5.440284 4.090889 4.646033
5 CHA 5.578007 4.971810 4.272014 5.579773The data file can be found here
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