Distributions

League-wide player histograms · 18 games played · 210 qualifying batters (3+ PA) · 86 qualifying pitchers (3+ outs)
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Player ID 6002 not found in the qualifying population — no histogram marker shown.

Batting distributions

PAVG n=210 · μ=0.279 · σ=0.250
0.000
74
0.069
0
0.139
8
0.208
19
0.278
49
0.347
9
0.417
1
0.486
15
0.556
3
0.625
18
0.694
11
0.764
3
10th25th Median 75th90th 95th99th
0.000 0.000 0.333 0.400 0.667 0.750 0.795
OPS n=210 · μ=0.861 · σ=0.708
0.000
37
0.250
36
0.500
36
0.750
12
1.000
29
1.250
17
1.500
14
1.750
8
2.000
8
2.250
6
2.500
5
2.750
2
10th25th Median 75th90th 95th99th
0.000 0.333 0.667 1.312 1.850 2.250 2.652
OPS+ n=210 · μ=97 · σ=79.592
0
41
30
35
60
41
90
20
120
22
149
17
179
10
209
7
239
11
269
4
299
1
329
1
10th25th Median 75th90th 95th99th
0 36 80 149 215 247 298
wOBA n=210 · μ=0.000 · σ=0.000
0.000
210
0.000
0
0.000
0
0.000
0
0.000
0
0.000
0
0.000
0
0.000
0
0.000
0
0.000
0
0.000
0
0.000
0
10th25th Median 75th90th 95th99th
0.000 0.000 0.000 0.000 0.000 0.000 0.000
BAVG n=210 · μ=0.329 · σ=0.316
0.000
74
0.167
16
0.333
48
0.500
29
0.667
35
0.833
0
1.000
6
1.167
0
1.333
0
1.500
1
1.667
0
1.833
1
10th25th Median 75th90th 95th99th
0.000 0.000 0.333 0.500 0.675 0.777 1.000
ISO n=210 · μ=0.172 · σ=0.310
0.000
138
0.125
7
0.250
35
0.375
1
0.500
8
0.625
4
0.750
5
0.875
0
1.000
7
1.125
2
1.250
1
1.375
2
10th25th Median 75th90th 95th99th
0.000 0.000 0.000 0.250 0.607 1.000 1.321
BABIP n=210 · μ=0.415 · σ=0.405
0.000
79
0.167
3
0.333
26
0.500
37
0.667
26
0.833
0
1.000
36
1.167
0
1.333
0
1.500
1
1.667
0
1.833
2
10th25th Median 75th90th 95th99th
0.000 0.000 0.333 0.667 1.000 1.000 1.455
K% n=210 · μ=25.2% · σ=24.1%
0.0%
82
8.3%
0
16.7%
9
25.0%
23
33.3%
50
41.7%
1
50.0%
18
58.3%
0
66.7%
22
75.0%
4
83.3%
0
91.7%
1
10th25th Median 75th90th 95th99th
0.0% 0.0% 25.0% 38.3% 66.7% 66.7% 75.0%
BB% n=210 · μ=11.3% · σ=16.5%
0.0%
135
5.6%
0
11.1%
1
16.7%
11
22.2%
18
27.8%
0
33.3%
34
38.9%
3
44.4%
0
50.0%
5
55.6%
0
61.1%
3
10th25th Median 75th90th 95th99th
0.0% 0.0% 0.0% 25.0% 33.3% 37.0% 65.2%
2C-RBI% n=210 · μ=1.9% · σ=13.0%
0.0%
205
8.3%
0
16.7%
0
25.0%
0
33.3%
1
41.7%
0
50.0%
0
58.3%
0
66.7%
1
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% 97.0%
2C-Conv% n=210 · μ=3.8% · σ=19.1%
0.0%
202
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%
8
10th25th Median 75th90th 95th99th
0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%
MhAB% n=210 · μ=0.2% · σ=3.4%
0.0%
209
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=210 · μ=0.262 · σ=0.336
0.000
109
0.167
10
0.333
32
0.500
28
0.667
14
0.833
0
1.000
16
1.167
0
1.333
0
1.500
0
1.667
0
1.833
1
10th25th Median 75th90th 95th99th
0.000 0.000 0.000 0.500 0.750 1.000 1.000
RISP-OPS n=210 · μ=0.794 · σ=1.004
0.000
112
0.667
48
1.333
25
2.000
14
2.667
8
3.333
1
4.000
0
4.667
1
5.333
0
6.000
0
6.667
0
7.333
1
10th25th Median 75th90th 95th99th
0.000 0.000 0.500 1.238 2.000 2.592 3.477
RISP-Conv n=210 · μ=0.29 · σ=0.538
0.00
154
0.42
35
0.83
14
1.25
3
1.67
1
2.08
0
2.50
1
2.92
1
3.33
0
3.75
0
4.17
0
4.58
1
10th25th Median 75th90th 95th99th
0.00 0.00 0.00 0.50 0.82 1.00 2.45
WAR n=210 · μ=0.00 · σ=0.013
-0.03
2
-0.02
3
-0.02
17
-0.01
53
-0.01
46
0.00
28
0.01
27
0.01
18
0.02
8
0.03
1
0.03
5
0.04
2
10th25th Median 75th90th 95th99th
-0.02 -0.01 0.00 0.01 0.02 0.03 0.04

Pitching distributions

wERA n=86 · μ=12.34 · σ=9.287
0.00
11
4.18
24
8.35
20
12.53
11
16.70
9
20.88
3
25.06
1
29.23
2
33.41
3
37.58
1
41.76
0
45.94
1
10th25th Median 75th90th 95th99th
4.10 6.27 9.44 15.47 22.70 33.04 42.43
xRA n=86 · μ=12.34 · σ=9.287
0.00
11
4.18
24
8.35
20
12.53
11
16.70
9
20.88
3
25.06
1
29.23
2
33.41
3
37.58
1
41.76
0
45.94
1
10th25th Median 75th90th 95th99th
4.10 6.27 9.44 15.47 22.70 33.04 42.43
Decay n=12 · μ=+13.8 · σ=40.662
-34.1
2
-24.1
2
-14.1
2
-4.1
0
+5.9
2
+15.9
0
+25.9
0
+35.9
0
+45.9
1
+55.9
1
+65.9
0
+75.9
2
10th25th Median 75th90th 95th99th
-23.9 -21.3 -0.3 +48.4 +78.4 +83.2 +85.4
GSc avg n=86 · μ=54.8 · σ=7.812
40.0
2
43.0
5
46.0
9
48.9
19
51.9
14
54.9
14
57.9
8
60.8
3
63.8
4
66.8
2
69.8
2
72.7
4
10th25th Median 75th90th 95th99th
46.4 50.0 53.5 58.5 66.3 72.3 74.1
GSc+ n=86 · μ=103 · σ=14.684
75
2
81
5
86
9
92
19
97
14
103
14
109
8
114
3
120
4
126
2
131
2
137
4
10th25th Median 75th90th 95th99th
87 94 100 110 125 136 139
FOP n=86 · μ=57 · σ=18.337
8
3
15
3
22
1
29
5
36
5
43
7
50
11
56
15
63
17
70
9
77
6
84
4
10th25th Median 75th90th 95th99th
32 47 59 69 78 83 89
OS+ n=86 · μ=119 · σ=81.412
39
31
65
3
91
23
117
6
144
8
170
3
196
1
222
2
248
2
274
1
300
1
326
5
10th25th Median 75th90th 95th99th
39 52 98 144 242 323 352
GE n=86 · μ=0.3 · σ=0.231
0.1
24
0.2
10
0.3
15
0.3
14
0.4
6
0.5
5
0.6
1
0.6
2
0.7
2
0.8
1
0.9
1
0.9
5
10th25th Median 75th90th 95th99th
0.1 0.1 0.3 0.4 0.7 0.9 1.0
K% n=86 · μ=31.1% · σ=18.6%
0.0%
10
6.7%
3
13.3%
12
20.0%
12
26.7%
8
33.3%
9
40.0%
12
46.7%
10
53.3%
4
60.0%
4
66.7%
1
73.3%
1
10th25th Median 75th90th 95th99th
0.0% 16.9% 29.7% 44.4% 53.9% 61.3% 70.6%
BB% n=86 · μ=12.3% · σ=9.9%
0.0%
23
2.8%
2
5.6%
7
8.3%
6
11.1%
11
13.9%
8
16.7%
5
19.4%
8
22.2%
2
25.0%
5
27.8%
7
30.6%
2
10th25th Median 75th90th 95th99th
0.0% 0.0% 12.5% 20.0% 27.3% 29.2% 33.3%
HR% n=86 · μ=2.7% · σ=6.5%
0.0%
67
2.8%
2
5.6%
6
8.3%
1
11.1%
5
13.9%
2
16.7%
0
19.4%
0
22.2%
0
25.0%
1
27.8%
0
30.6%
2
10th25th Median 75th90th 95th99th
0.0% 0.0% 0.0% 0.0% 11.1% 13.8% 33.3%
K-BB% n=86 · μ=11.5% · σ=18.9%
-33.3%
1
-26.0%
2
-18.6%
6
-11.2%
8
-3.8%
20
3.5%
3
10.9%
18
18.3%
10
25.7%
6
33.0%
7
40.4%
1
47.8%
4
10th25th Median 75th90th 95th99th
-10.9% 0.0% 12.5% 22.9% 37.5% 42.1% 54.6%
oAVG n=86 · μ=0.342 · σ=0.198
0.000
8
0.083
3
0.167
15
0.250
20
0.333
14
0.417
5
0.500
12
0.583
2
0.667
4
0.750
0
0.833
2
0.917
1
10th25th Median 75th90th 95th99th
0.134 0.204 0.300 0.455 0.586 0.667 0.858
WAR n=86 · μ=0.05 · σ=0.140
-0.25
3
-0.19
5
-0.12
5
-0.06
18
-0.00
18
0.06
16
0.12
9
0.18
4
0.24
3
0.30
3
0.36
0
0.43
1
10th25th Median 75th90th 95th99th
-0.11 -0.04 0.04 0.12 0.24 0.32 0.47
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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