Distributions

League-wide player histograms · 12 games played · 134 qualifying batters (3+ PA) · 61 qualifying pitchers (3+ outs)
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Player ID 2737 not found in the qualifying population — no histogram marker shown.

Batting distributions

PAVG n=134 · μ=0.334 · σ=0.223
0.000
21
0.083
8
0.167
15
0.250
19
0.333
19
0.417
12
0.500
21
0.583
3
0.667
10
0.750
5
0.833
0
0.917
1
10th25th Median 75th90th 95th99th
0.000 0.167 0.333 0.500 0.667 0.714 0.783
OPS n=134 · μ=0.994 · σ=0.571
0.000
11
0.202
9
0.405
18
0.607
22
0.810
18
1.012
5
1.214
16
1.417
14
1.619
9
1.821
9
2.024
1
2.226
2
10th25th Median 75th90th 95th99th
0.333 0.579 0.882 1.482 1.750 2.000 2.289
OPS+ n=134 · μ=98 · σ=56.218
0
11
20
9
40
18
60
22
80
18
100
5
119
16
139
14
159
9
179
9
199
1
219
2
10th25th Median 75th90th 95th99th
33 57 87 146 172 197 225
wOBA n=134 · μ=0.476 · σ=0.271
0.000
8
0.112
13
0.225
26
0.337
24
0.450
17
0.562
13
0.674
13
0.787
11
0.899
4
1.012
3
1.124
1
1.237
1
10th25th Median 75th90th 95th99th
0.184 0.253 0.447 0.665 0.814 0.925 1.119
BAVG n=134 · μ=0.409 · σ=0.274
0.000
21
0.083
1
0.167
10
0.250
14
0.333
29
0.417
5
0.500
20
0.583
3
0.667
11
0.750
9
0.833
3
0.917
8
10th25th Median 75th90th 95th99th
0.000 0.250 0.388 0.593 0.750 1.000 1.000
ISO n=134 · μ=0.176 · σ=0.220
0.000
67
0.071
6
0.143
15
0.214
6
0.286
12
0.357
4
0.429
4
0.500
10
0.571
4
0.643
3
0.714
1
0.786
2
10th25th Median 75th90th 95th99th
0.000 0.000 0.062 0.333 0.500 0.581 0.794
BABIP n=134 · μ=0.448 · σ=0.300
0.000
23
0.083
0
0.167
5
0.250
9
0.333
32
0.417
2
0.500
20
0.583
6
0.667
11
0.750
8
0.833
4
0.917
14
10th25th Median 75th90th 95th99th
0.000 0.250 0.400 0.667 0.963 1.000 1.000
K% n=134 · μ=15.2% · σ=16.7%
0.0%
57
6.9%
6
13.9%
30
20.8%
15
27.8%
13
34.7%
3
41.7%
1
48.6%
7
55.6%
0
62.5%
1
69.4%
0
76.4%
1
10th25th Median 75th90th 95th99th
0.0% 0.0% 14.3% 25.0% 33.3% 50.0% 61.2%
BB% n=134 · μ=13.9% · σ=15.0%
0.0%
58
5.0%
1
10.0%
23
15.0%
7
20.0%
9
25.0%
12
30.0%
15
35.0%
0
40.0%
2
45.0%
0
50.0%
6
55.0%
1
10th25th Median 75th90th 95th99th
0.0% 0.0% 13.4% 25.0% 33.3% 43.5% 50.0%
2C-RBI% n=134 · μ=0.4% · σ=5.2%
0.0%
133
5.0%
0
10.0%
0
15.0%
0
20.0%
0
25.0%
0
30.0%
0
35.0%
0
40.0%
0
45.0%
0
50.0%
0
55.0%
1
10th25th Median 75th90th 95th99th
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
2C-Conv% n=134 · μ=2.2% · σ=14.8%
0.0%
131
8.3%
0
16.7%
0
25.0%
0
33.3%
0
41.7%
0
50.0%
0
58.3%
0
66.7%
0
75.0%
0
83.3%
0
91.7%
3
10th25th Median 75th90th 95th99th
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%
MhAB% n=134 · μ=0.4% · σ=4.3%
0.0%
133
4.2%
0
8.3%
0
12.5%
0
16.7%
0
20.8%
0
25.0%
0
29.2%
0
33.3%
0
37.5%
0
41.7%
0
45.8%
1
10th25th Median 75th90th 95th99th
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
RISP-AVG n=134 · μ=0.321 · σ=0.282
0.000
43
0.083
0
0.167
10
0.250
8
0.333
25
0.417
0
0.500
23
0.583
3
0.667
13
0.750
3
0.833
0
0.917
6
10th25th Median 75th90th 95th99th
0.000 0.000 0.333 0.500 0.667 0.800 1.000
RISP-OPS n=134 · μ=0.967 · σ=0.751
0.000
30
0.250
4
0.500
25
0.750
6
1.000
25
1.250
6
1.500
14
1.750
0
2.000
18
2.250
2
2.500
2
2.750
2
10th25th Median 75th90th 95th99th
0.000 0.425 1.000 1.500 2.000 2.140 2.890
RISP-Conv n=134 · μ=0.38 · σ=0.397
0.00
50
0.17
17
0.33
12
0.50
19
0.67
19
0.83
3
1.00
9
1.17
1
1.33
2
1.50
0
1.67
1
1.83
1
10th25th Median 75th90th 95th99th
0.00 0.00 0.29 0.67 0.95 1.00 1.58
WAR n=134 · μ=0.02 · σ=0.075
-0.13
6
-0.09
13
-0.05
27
-0.02
27
0.02
29
0.06
11
0.09
8
0.13
8
0.17
3
0.20
1
0.24
0
0.28
1
10th25th Median 75th90th 95th99th
-0.07 -0.03 0.01 0.05 0.12 0.16 0.22

Pitching distributions

wERA n=61 · μ=14.19 · σ=10.580
0.00
6
5.26
23
10.52
13
15.78
9
21.03
3
26.29
5
31.55
0
36.81
0
42.07
1
47.33
0
52.58
0
57.84
1
10th25th Median 75th90th 95th99th
5.53 7.40 11.98 18.90 27.78 29.69 52.78
xRA n=61 · μ=14.19 · σ=10.580
0.00
6
5.26
23
10.52
13
15.78
9
21.03
3
26.29
5
31.55
0
36.81
0
42.07
1
47.33
0
52.58
0
57.84
1
10th25th Median 75th90th 95th99th
5.53 7.40 11.98 18.90 27.78 29.69 52.78
Decay n=3 · μ=-1.9 · σ=19.067
-24.6
1
-20.8
0
-16.9
0
-13.0
0
-9.1
0
-5.2
1
-1.3
0
+2.6
0
+6.5
0
+10.4
0
+14.2
0
+18.1
0
10th25th Median 75th90th 95th99th
-20.3 -13.8 -2.9 +9.5 +17.0 +19.5 +21.5
GSc avg n=61 · μ=51.0 · σ=7.380
30.8
1
33.8
1
36.8
2
39.7
6
42.7
4
45.6
13
48.6
6
51.6
8
54.5
5
57.5
11
60.4
3
63.4
1
10th25th Median 75th90th 95th99th
41.7 46.2 50.9 57.5 60.2 61.2 63.7
GSc+ n=61 · μ=102 · σ=14.707
61
1
67
1
73
2
79
6
85
4
91
13
97
6
103
8
109
5
115
11
120
3
126
1
10th25th Median 75th90th 95th99th
83 92 101 115 120 122 127
FOP n=61 · μ=59 · σ=15.304
5
1
12
1
18
0
24
3
31
1
37
4
43
5
50
5
56
13
62
11
69
11
75
6
10th25th Median 75th90th 95th99th
41 51 62 69 74 78 81
OS+ n=61 · μ=120 · σ=73.222
41
14
68
9
95
13
122
9
149
9
176
2
204
0
231
2
258
0
285
0
312
0
339
3
10th25th Median 75th90th 95th99th
54 81 109 149 204 231 366
GE n=61 · μ=0.3 · σ=0.200
0.1
14
0.2
9
0.3
13
0.3
9
0.4
4
0.5
5
0.6
2
0.6
2
0.7
0
0.8
0
0.9
0
0.9
3
10th25th Median 75th90th 95th99th
0.1 0.2 0.3 0.4 0.6 0.6 1.0
K% n=61 · μ=21.7% · σ=13.1%
0.0%
6
4.2%
2
8.3%
5
12.5%
9
16.7%
9
20.8%
4
25.0%
12
29.2%
2
33.3%
4
37.5%
2
41.7%
2
45.8%
4
10th25th Median 75th90th 95th99th
6.2% 12.5% 20.0% 28.6% 40.0% 50.0% 50.0%
BB% n=61 · μ=15.3% · σ=11.8%
0.0%
11
4.2%
5
8.3%
8
12.5%
15
16.7%
7
20.8%
1
25.0%
3
29.2%
4
33.3%
4
37.5%
2
41.7%
0
45.8%
1
10th25th Median 75th90th 95th99th
0.0% 7.7% 13.3% 20.0% 33.3% 36.4% 44.0%
HR% n=61 · μ=1.9% · σ=4.5%
0.0%
50
2.1%
0
4.2%
0
6.2%
3
8.3%
6
10.4%
1
12.5%
0
14.6%
0
16.7%
0
18.8%
0
20.8%
0
22.9%
1
10th25th Median 75th90th 95th99th
0.0% 0.0% 0.0% 0.0% 9.1% 9.1% 16.7%
K-BB% n=61 · μ=1.5% · σ=18.5%
-50.0%
1
-41.7%
1
-33.3%
4
-25.0%
2
-16.7%
7
-8.3%
5
0.0%
19
8.3%
9
16.7%
6
25.0%
4
33.3%
2
41.7%
1
10th25th Median 75th90th 95th99th
-25.0% -8.3% 0.0% 13.3% 25.0% 28.6% 41.4%
oAVG n=61 · μ=0.379 · σ=0.156
0.000
1
0.062
1
0.125
3
0.188
5
0.250
14
0.312
9
0.375
5
0.438
5
0.500
9
0.562
5
0.625
2
0.688
2
10th25th Median 75th90th 95th99th
0.217 0.250 0.346 0.500 0.583 0.625 0.729
WAR n=61 · μ=0.07 · σ=0.132
-0.25
1
-0.20
2
-0.14
3
-0.08
10
-0.03
7
0.03
13
0.09
11
0.14
7
0.20
4
0.26
0
0.32
0
0.37
2
10th25th Median 75th90th 95th99th
-0.08 -0.04 0.06 0.14 0.21 0.25 0.42
Methodology
Each histogram is a 12-bucket equal-width binning of the qualifying-player population's values. Bucket bounds run from min to max across the population — no fixed domain. The labels on the left are the bucket's lower bound; the count on the right is how many players fell into it. Bar widths are normalized to the largest-count bucket (so the longest bar = 100% of the panel width).

Qualifying thresholds are the same as on the Leaders page — ~1× games-per-team in PA for batters and outs for pitchers, scaled with games played.

Percentiles use linear interpolation (matches numpy percentile() default). σ is population standard deviation across the qualifying group.

The Decay distribution is restricted to pitchers with cross-arc sample (faced batters in both arc-1 and arc-3), so the n on that panel is lower than the rest of the pitching panels. Pitchers without enough sample to compute Decay aren't binned.

xRA is the non-negative linear-weights expected runs allowed (HR=1.4, single≈0.45, BB/HBP=0.32, K/out=0), multiplicatively anchored so league xRA matches league xRA. K-BB% is plain (K - BB) / BF.
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