Analytics

SABR-flavoured context-tier metrics · 753 games played · 235 qualifying batters (≥50 PA)

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RE24-O27 · Run Expectancy by (bases, outs) 34371 events · 1506 halves · league-avg runs/half = 11.08

Each cell shows expected runs scored from this state to end-of-half. Outs are bucketed in 3s (the engine's natural arc). Read across a row to see how RE decays as outs accumulate; read down a column to see how RE rises with runners on base.

Bases	0-2	3-5	6-8	9-11	12-14	15-17	18-20	21-23	24-26
`___`	10.73 (1791)	9.33 (672)	8.70 (560)	6.93 (507)	5.51 (464)	4.78 (424)	3.62 (445)	2.24 (470)	1.84 (382)
`1__`	12.09 (872)	11.02 (667)	10.47 (573)	8.96 (600)	6.96 (545)	5.31 (460)	3.87 (507)	2.90 (493)	1.96 (390)
`_2_`	13.62 (939)	12.14 (998)	10.59 (893)	9.34 (837)	7.50 (774)	5.83 (757)	4.69 (706)	3.46 (622)	2.72 (451)
`12_`	12.99 (393)	11.31 (459)	10.05 (426)	8.12 (492)	6.52 (479)	5.82 (408)	4.79 (449)	3.32 (349)	2.31 (266)
`__3`	15.58 (499)	13.48 (539)	10.53 (586)	8.94 (575)	7.11 (543)	5.72 (467)	4.27 (474)	3.22 (486)	2.86 (361)
`1_3`	10.01 (207)	8.80 (299)	7.55 (337)	5.69 (367)	5.29 (366)	4.40 (292)	3.54 (347)	2.37 (304)	2.05 (257)
`_23`	9.15 (170)	8.19 (394)	6.38 (365)	5.71 (359)	4.37 (305)	3.69 (355)	2.87 (329)	2.46 (295)	2.29 (260)
`123`	10.82 (165)	8.47 (285)	7.26 (297)	6.24 (328)	4.86 (355)	4.03 (323)	3.54 (367)	3.02 (330)	2.44 (263)

Bunting rates · league barometer 1257 bunts · 2.33% of PA

Bunt rate (% of PA)

2.33%

Bunt-hit rate

30.2%

Squeeze share of bunts

8.0%

Run value / 100 bunts (RE24)

+18.7

Split	Bunts	Bunt%PA	Hit%	Sac share	Sqz share
Pitchers	498	16.23%	15.3%	66.1%	0.0%
Position players	759	1.49%	40.1%	32.0%	13.2%

Team	Bunts	Bunt%PA	Hit%	Sac share	Sqz share	RV/100
BB1	30	4.56%	30.0%	40.0%	3.3%	-37.7
KKK	29	4.33%	48.3%	31.0%	3.4%	+45.9
JF	29	4.33%	24.1%	58.6%	10.3%	+30.3
QBS	30	4.21%	36.7%	36.7%	6.7%	+39.0
KRM	28	3.99%	42.9%	32.1%	3.6%	+1.9
CNC	23	3.77%	34.8%	52.2%	8.7%	+45.8
KBK	24	3.76%	37.5%	45.8%	0.0%	+16.1
NYL	27	3.75%	14.8%	63.0%	7.4%	-1.4
GB	24	3.73%	33.3%	29.2%	16.7%	+9.9
FCW	25	3.56%	36.0%	36.0%	16.0%	+9.2
HMR	24	3.50%	33.3%	33.3%	8.3%	-33.4
CBK	22	3.48%	18.2%	54.5%	9.1%	+46.7
OF	23	3.44%	30.4%	47.8%	4.3%	+65.0
OS	23	3.30%	21.7%	34.8%	13.0%	+19.3
MCP	24	3.27%	33.3%	58.3%	8.3%	+7.6
PF	22	3.17%	27.3%	59.1%	4.5%	-10.7
CCB	21	3.13%	33.3%	47.6%	14.3%	+29.5
BIC	23	3.05%	21.7%	43.5%	8.7%	+19.4
NE	20	3.01%	10.0%	45.0%	5.0%	+35.5
WBC	19	2.90%	21.1%	52.6%	10.5%	+56.8
HEE	19	2.89%	52.6%	31.6%	0.0%	+16.5
MF	22	2.80%	40.9%	45.5%	4.5%	+32.2
PDR	21	2.76%	33.3%	28.6%	9.5%	-18.8
GP	20	2.72%	25.0%	55.0%	5.0%	+25.3
GS	24	2.68%	16.7%	54.2%	20.8%	-62.8
RE	20	2.66%	30.0%	30.0%	25.0%	+38.8
HM1	18	2.60%	38.9%	50.0%	11.1%	+91.2
HCC	19	2.53%	42.1%	47.4%	10.5%	-27.3
MB	21	2.49%	28.6%	71.4%	4.8%	-37.8
BNS	16	2.47%	37.5%	43.8%	18.8%	+42.2
PPS	18	2.47%	38.9%	50.0%	5.6%	-31.4
NYP	16	2.41%	31.2%	31.2%	12.5%	+30.6
KO	16	2.36%	31.2%	43.8%	12.5%	+29.3
LM	18	2.31%	11.1%	77.8%	5.6%	+119.9
PC	18	2.28%	27.8%	66.7%	0.0%	+40.5
ŽS	17	2.23%	29.4%	58.8%	5.9%	-5.2
TF1	16	2.22%	12.5%	50.0%	6.2%	+15.9
CBC	15	2.15%	26.7%	33.3%	13.3%	+5.6
EI	15	2.14%	26.7%	53.3%	0.0%	-12.0
SK	17	2.06%	52.9%	23.5%	5.9%	+6.3
RDJ	14	2.02%	7.1%	57.1%	21.4%	+76.4
OB	15	2.01%	53.3%	33.3%	6.7%	+99.1
DGT	14	2.00%	28.6%	42.9%	7.1%	-54.0
BBC	11	2.00%	18.2%	27.3%	9.1%	+98.8
OH	15	1.98%	26.7%	46.7%	0.0%	-95.6
DAF	15	1.96%	20.0%	53.3%	0.0%	+11.7
TF	13	1.93%	7.7%	76.9%	0.0%	+31.0
CS	14	1.92%	42.9%	42.9%	0.0%	-24.8
BT	12	1.91%	41.7%	50.0%	0.0%	+26.9
MP	12	1.90%	58.3%	33.3%	8.3%	+39.3
PB	11	1.83%	18.2%	63.6%	0.0%	+38.9
BB	12	1.82%	8.3%	58.3%	8.3%	-42.0
SYC	12	1.80%	50.0%	25.0%	8.3%	+48.2
KBC	13	1.79%	30.8%	38.5%	0.0%	+107.1
SL	13	1.79%	30.8%	38.5%	7.7%	-37.3
HM	13	1.79%	30.8%	38.5%	0.0%	+47.6
NH	13	1.78%	30.8%	46.2%	0.0%	-7.8
KTH	13	1.73%	53.8%	30.8%	0.0%	+51.7
ZL	12	1.71%	25.0%	41.7%	8.3%	+50.5
CF	12	1.67%	33.3%	41.7%	0.0%	+49.5
VB	11	1.66%	45.5%	18.2%	0.0%	+46.7
LP	11	1.58%	18.2%	36.4%	9.1%	-19.1
SPL	12	1.57%	58.3%	16.7%	8.3%	+8.1
NP	12	1.56%	16.7%	41.7%	25.0%	+1.8
YBC	12	1.54%	8.3%	50.0%	8.3%	+1.7
PAF	10	1.49%	10.0%	50.0%	60.0%	+2.8
KH	11	1.42%	36.4%	45.5%	0.0%	+35.2
TBC	10	1.39%	20.0%	60.0%	20.0%	+95.9
CGT	8	1.33%	37.5%	37.5%	12.5%	+31.5
CB	9	1.28%	33.3%	44.4%	11.1%	-25.8
SCJ	8	1.19%	12.5%	75.0%	0.0%	-4.1
SPD	9	1.18%	33.3%	66.7%	0.0%	-4.6
MCB	6	0.84%	16.7%	33.3%	0.0%	-19.0
LRC	6	0.82%	0.0%	66.7%	16.7%	+67.3
SDC	4	0.45%	0.0%	75.0%	0.0%	+183.9
LAB	3	0.42%	66.7%	33.3%	0.0%	+133.7

Bunt-hit rate = bunt singles ÷ bunts. Sac share = runners advanced or squeezed home ÷ bunts. Productive = reached base or moved a runner. RV/100 = RE24-O27 run value (RE after − RE before + runs) per 100 bunts; positive means bunts added runs vs. expected.

RE by outs-remaining · 1-D curve expected future runs given outs already recorded

The "how much offence is left?" curve. Anchors GSc / xRA scaling and gives one number for any leverage-aware context.

Outs done	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26
Outs left	27	26	25	24	23	22	21	20	19	18	17	16	15	14	13	12	11	10	9	8	7	6	5	4	3	2	1
RE	12.59	12.31	11.09	11.22	10.41	10.68	9.69	9.47	8.94	8.21	7.98	7.43	6.59	6.17	6.15	5.49	4.96	4.87	4.22	4.08	3.73	3.09	3.17	2.51	2.60	2.28	1.95
n	2022	1593	1421	1460	1418	1435	1347	1317	1373	1352	1381	1332	1263	1312	1256	1195	1139	1152	1194	1200	1230	1125	1137	1087	1035	916	679

Linear weights · empirical run values driving wOBA + Game Score 33498 BIP events · league RE/half = 11.27 · league wOBA = league OBP = 0.476 (by construction)

Each event's run value is derived from the RE matrix above: RV(event) = runs_scored + RE(state_after) − RE(state_before), averaged across all BIP events. BB / HBP go analytically (forced-runner transitions weighted by empirical state occupation). These values feed both the wOBA weights (OBP-scaled, replacing MLB defaults in expected_woba.py and _aggregate_batter_rows) and the Game Score coefficients (run-prevention values × 2 GSc points per run, replacing the MLB-tuned penalty constants in _pitcher_game_score).

Event run values

Event	RV (runs)
HR	+3.192
3B	+2.282
2B	+1.383
1B	+0.146
BB	-0.244
HBP	-0.244
K_over_out	+0.050
out	-0.403

Out RV is negative (an out costs the offense ~0.4 runs vs prior expectation). 2C is the empirical RV of a credited Second-Chance event — broken out from 1B so the single's value reflects true singles only.

wOBA weights (OBP-scaled)

Event	O27 refit	MLB default	Δ%
BB	0.152	0.720	-79%
HBP	0.152	0.740	-79%
1B	0.528	0.950	-44%
2B	1.718	1.300	+32%
3B	2.583	1.700	+52%
HR	3.459	2.050	+69%

High-RPG environment: walks and singles gain ground over MLB (bases are full more often, so each free baserunner is worth more). HR's marginal value shrinks because singles + walks already clear the bases. The empirical BB/HBP marginal RV exceeds 1B's here (a HR clears bases and drops RE by ~1 per baserunner, while a walk only adds RE without losing anyone); we cap BB/HBP at the 1B weight so the displayed ordering stays BB ≤ 1B ≤ 2B ≤ 3B ≤ HR. Drives every wOBA / xwOBA value on /leaders and /analytics.

Game Score coefficients

Term	O27 refit	MLB
base	55.80	50
out	1.00	1
K_over_out	0.10	2
FO_over_out	1.00	1
H	1.87	2
HR_over_H	4.51	4
BB	-0.49	1
ER	2.00	4
UER	1.00	2

League starter GSc dist over 1506 outings: mean = 49.86 (target 50, auto-tuned via base), p25/p50/p75 = 42.3 / 49.2 / 57.2, range [8.9, 82.8]. No clamping at 0 or 100.

Expected wOBA · contact-quality model league wOBA = 0.469 · league xwOBA = 0.469 (must match — calibration check)

Contact-quality table

Quality	n BIP	xwOBA / BIP
hard	11336	1.315
medium	16605	0.494
weak	6430	0.188

Per-BIP wOBA points expected from each quality bin. Linear-weight scaffolding: weights are O27-empirical (derived from this league's RE matrix in linear_weights.py), not MLB defaults. League wOBA = league OBP by construction.

Top 15 by xwOBA

#	Player	Tm	PA	wOBA	xwOBA	Δ
1	Sukhwinder Bedi	HCC	68	1.267	0.824	+0.443
2	Jae-ho Kang	HM1	58	0.934	0.784	+0.150
3	Arnav Khanna	GS	75	1.155	0.780	+0.375
4	Yusof Mustafa	OF	51	0.766	0.770	-0.004
5	David Visser	BNS	54	1.032	0.756	+0.276
6	Rohan Ramphal	SDC	56	0.995	0.740	+0.255
7	António Pereira	MF	59	0.935	0.738	+0.197
8	Earnest Rivera	NYP	51	0.925	0.730	+0.194
9	Finn Martins	PF	57	0.782	0.729	+0.053
10	Dann Zinderstein	MF	63	0.980	0.724	+0.256
11	Mohun Sharma	EI	58	0.808	0.723	+0.085
12	Jean Polanco	PPS	59	0.956	0.719	+0.237
13	Naina Guérin	ŽS	59	0.624	0.716	-0.091
14	Mujeeb Hassan	GS	64	0.983	0.714	+0.269
15	Rajdeep Sen	GS	75	0.605	0.713	-0.108

Biggest BABIP swings · Δ = wOBA − xwOBA

Hot bats — production above contact (regression candidates)

Player	Tm	PA	wOBA	xwOBA	Δ
Tony Feliz	MCP	66	1.100	0.594	+0.507
Sukhwinder Bedi	HCC	68	1.267	0.824	+0.443
Don Wild	SDC	59	1.071	0.637	+0.434
Dennis McMichael	PPS	59	1.089	0.670	+0.419
Arnav Khanna	GS	75	1.155	0.780	+0.375
Marcus Low	SK	55	0.903	0.560	+0.343
Kallen Langlois	MCP	61	1.020	0.678	+0.341

Cold bats — contact above production (ceiling above headline wOBA)

Player	Tm	PA	wOBA	xwOBA	Δ
Robby Spoelstra	KBK	52	0.120	0.395	-0.274
Preston Singh	GB	52	0.276	0.518	-0.242
Laros Cruz	CBC	54	0.250	0.476	-0.226
Baghdad Al-Saadi	DAF	58	0.296	0.520	-0.224
Syahmi Razak	KKK	55	0.364	0.585	-0.221
Ramón Zamora	CCB	62	0.150	0.364	-0.215
Benjaloud Ngamaleu	CBC	50	0.182	0.388	-0.206

Pythagorean exponent · empirically refit for O27 76 teams · k* = 2.156 vs MLB default 1.83 · RMSE 0.0913 (cut 5.0%)

Bill James's exponent (1.83) was fit to MLB's ~9 R/G run environment. O27 sits at ~22 R/G; the win/loss curve sharpens, so the optimal exponent is much higher. The fitted value comes from a 1-D ternary search minimising SSE in win-percentage prediction across the league.

Tm	G	W	RS	RA	W%	Pythag W (1.83)	Luck (1.83)	Pythag W (k*)	Luck (k*)
KRM	20	4	166	174	0.200	9.6	-5.6	9.5	-5.5
GB	20	12	188	227	0.600	8.3	+3.7	8.0	+4.0
SPL	20	8	273	238	0.400	11.2	-3.2	11.5	-3.5
CS	20	10	259	184	0.500	13.0	-3.0	13.5	-3.5
QBS	20	3	180	257	0.150	6.9	-3.9	6.3	-3.3
CBK	20	12	211	237	0.600	8.9	+3.1	8.8	+3.2
BBC	20	15	185	157	0.750	11.5	+3.5	11.8	+3.2
BNS	20	13	202	200	0.650	10.1	+2.9	10.1	+2.9
WBC	20	3	147	226	0.150	6.3	-3.3	5.7	-2.7
LP	20	14	235	206	0.700	11.2	+2.8	11.4	+2.6
OB	20	11	286	201	0.550	13.1	-2.1	13.6	-2.6
GP	20	10	245	310	0.500	7.9	+2.1	7.5	+2.5
KO	20	9	214	299	0.450	7.0	+2.0	6.5	+2.5
SPD	20	9	247	216	0.450	11.2	-2.2	11.4	-2.4
CCB	20	6	163	322	0.300	4.5	+1.5	3.7	+2.3
SL	20	15	311	241	0.750	12.3	+2.7	12.7	+2.3
JF	21	3	152	255	0.143	5.9	-2.9	5.2	-2.2
BB	20	16	244	168	0.800	13.3	+2.7	13.8	+2.2
TF1	20	14	309	260	0.700	11.6	+2.4	11.8	+2.2
KH	20	11	290	214	0.550	12.7	-1.7	13.2	-2.2
BT	19	9	185	156	0.474	11.0	-2.0	11.2	-2.2
DGT	20	11	227	252	0.550	9.0	+2.0	8.9	+2.1
SDC	20	11	413	311	0.550	12.5	-1.5	13.0	-2.0
EI	19	12	276	260	0.632	10.0	+2.0	10.1	+1.9
FCW	20	5	211	284	0.250	7.3	-2.3	6.9	-1.9
PPS	20	7	264	296	0.350	9.0	-2.0	8.8	-1.8
KBC	20	14	278	227	0.700	11.8	+2.2	12.2	+1.8
NH	19	15	319	216	0.789	12.8	+2.2	13.3	+1.7
HEE	19	4	189	279	0.211	6.3	-2.3	5.7	-1.7
HM1	20	10	197	169	0.500	11.4	-1.4	11.6	-1.6
HCC	20	10	282	327	0.500	8.7	+1.3	8.4	+1.6
LAB	20	8	197	205	0.400	9.6	-1.6	9.6	-1.6
KBK	20	9	171	162	0.450	10.5	-1.5	10.6	-1.6
CNC	20	6	140	253	0.300	5.1	+0.9	4.4	+1.6
MB	20	16	385	247	0.800	13.9	+2.1	14.4	+1.6
PF	20	9	239	303	0.450	7.9	+1.1	7.5	+1.5
OF	19	9	208	254	0.474	7.8	+1.2	7.5	+1.5
NYP	19	8	207	274	0.421	7.1	+0.9	6.7	+1.3
MCB	20	5	218	315	0.250	6.8	-1.8	6.2	-1.2
CBC	20	3	159	292	0.150	4.9	-1.9	4.2	-1.2
GS	20	14	482	286	0.700	14.4	-0.4	15.1	-1.1
MCP	19	14	350	248	0.737	12.4	+1.6	12.9	+1.1
KKK	19	2	172	369	0.105	3.8	-1.8	3.1	-1.1
ŽS	20	13	317	213	0.650	13.5	-0.5	14.0	-1.0
TF	20	9	223	224	0.450	10.0	-1.0	10.0	-1.0
SYC	19	9	243	278	0.474	8.3	+0.7	8.1	+0.9
DAF	20	9	256	259	0.450	9.9	-0.9	9.9	-0.9
HM	19	11	282	266	0.579	10.0	+1.0	10.1	+0.9
OH	20	7	279	345	0.350	8.1	-1.1	7.8	-0.8
NP	20	15	352	232	0.750	13.6	+1.4	14.2	+0.8
OS	21	5	173	330	0.238	4.9	+0.1	4.2	+0.8
LM	20	13	361	294	0.650	11.9	+1.1	12.2	+0.8
PC	20	12	290	258	0.600	11.1	+0.9	11.3	+0.7
NYL	20	9	238	278	0.450	8.6	+0.4	8.3	+0.7
HMR	20	8	231	296	0.400	7.8	+0.2	7.4	+0.6
PB	20	8	152	195	0.400	7.8	+0.2	7.4	+0.6
CB	20	11	248	238	0.550	10.4	+0.6	10.4	+0.6
YBC	20	14	338	241	0.700	13.0	+1.0	13.5	+0.5
MF	20	15	367	234	0.750	13.9	+1.1	14.5	+0.5
CF	20	11	243	233	0.550	10.4	+0.6	10.5	+0.5
PDR	20	11	334	315	0.550	10.5	+0.5	10.6	+0.4
RE	20	12	262	225	0.600	11.4	+0.6	11.6	+0.4
RDJ	19	6	209	308	0.316	6.3	-0.3	5.7	+0.3
MP	19	11	220	196	0.579	10.5	+0.5	10.7	+0.3
ZL	20	14	233	162	0.700	13.2	+0.8	13.7	+0.3
SCJ	20	13	211	164	0.650	12.3	+0.7	12.7	+0.3
KTH	19	14	295	187	0.737	13.2	+0.8	13.8	+0.2
CGT	18	10	144	127	0.556	10.0	-0.0	10.2	-0.2
NE	19	9	189	202	0.474	8.9	+0.1	8.8	+0.2
BB1	20	4	157	306	0.200	4.6	-0.6	3.8	+0.2
TBC	19	9	255	273	0.474	8.9	+0.1	8.8	+0.2
BIC	20	11	263	241	0.550	10.8	+0.2	10.9	+0.1
PAF	20	9	186	206	0.450	9.1	-0.1	8.9	+0.1
SK	20	17	377	167	0.850	16.3	+0.7	17.1	-0.1
LRC	20	11	268	243	0.550	10.9	+0.1	11.1	-0.1
VB	19	3	137	296	0.158	3.7	-0.7	3.0	-0.0

Sorted by |Luck (k*)|. With the fitted exponent the residuals generally compress vs. the default — the teams that still appear with double-digit luck are the genuine sequencing outliers.

BaseRuns · sequencing luck on offense and defense 76 teams · fitted B = (2.536·TB -0.751·H +2.000·HR -0.964·(BB+HBP)) vs MLB (1.4·TB −0.6·H −3·HR +0.1·(BB+HBP)) · SSE cut 26.6%

BaseRuns predicts runs scored from raw event counts (H, 2B, 3B, HR, BB, HBP, AB) with no information about the order events arrived in. The residual actual − predicted is therefore pure sequencing/cluster luck — hits-with-RISP timing, double-play avoidance, runner distribution. Applied to opposing offenses it gives sequencing luck on defense; the net is a clean "runs of cluster luck" figure that complements xwOBA (event-level luck) and the Pythag k* residual (W%-from-RD curvature). Default coefficients are MLB-fit for ~9 R/G; O27 sits at ~22 R/G, so we additionally refit all four B coefficients via joint coordinate-descent (analogous to Pythag's k* refit). The fitted luck column is the cleaner sequencing read; the gap between default and fitted shows how much of the apparent "luck" was actually environment shape mis-fit.

Tm	RS	RA	MLB-default coeffs			Refit coeffs (O27)
Tm	RS	RA	Off	Def	Net	Off	Def	Net
CBK	202	237	-34.2	+4.6	-38.8	-35.7	+3.0	-38.7
SK	374	167	+8.5	-3.5	+12.0	+22.9	-12.3	+35.3
EI	273	260	-44.3	+4.8	-49.1	-30.3	+4.7	-35.0
MF	358	234	+18.8	-8.5	+27.3	+27.9	-6.4	+34.3
BT	184	156	-1.0	+29.9	-30.8	-9.1	+23.3	-32.4
GS	480	286	-3.8	+1.6	-5.4	+32.5	+2.1	+30.4
BNS	196	200	-17.6	+14.8	-32.4	-18.2	+10.8	-29.0
PAF	184	206	+11.8	-24.5	+36.4	+3.5	-24.9	+28.5
NH	315	216	+2.5	-8.9	+11.4	+14.1	-11.4	+25.4
BIC	261	241	+15.9	-9.1	+25.0	+11.9	-12.9	+24.7
KRM	166	174	+22.9	-7.5	+30.4	+12.3	-12.1	+24.5
PDR	332	315	-12.4	+20.7	-33.1	+0.3	+23.1	-22.8
PB	149	195	+20.3	-6.4	+26.7	+11.9	-9.1	+21.0
LRC	260	243	+0.2	+26.6	-26.5	+0.6	+20.8	-20.2
SYC	234	278	-2.6	-32.4	+29.8	-4.5	-24.6	+20.1
SPL	273	238	+30.8	+4.9	+25.9	+21.5	+1.6	+19.9
HEE	186	279	-0.7	+5.9	-6.6	-9.2	+10.6	-19.8
DAF	255	259	+3.1	-24.3	+27.4	+2.5	-16.6	+19.1
VB	134	296	+10.8	+22.2	-11.4	+1.8	+20.7	-18.9
SL	301	241	-16.4	+19.1	-35.5	-8.0	+10.8	-18.9
SCJ	206	164	-11.3	+9.3	-20.6	-16.3	+2.4	-18.7
RE	255	225	-8.1	+12.1	-20.2	-12.1	+5.3	-17.4
OS	171	330	+4.4	+2.2	+2.2	-5.5	+11.1	-16.6
ŽS	317	213	+6.8	-2.9	+9.7	+12.4	-4.2	+16.5
MP	217	196	-8.2	+12.7	-20.9	-10.7	+5.3	-16.0
HM1	186	169	+4.6	+18.8	-14.3	-2.3	+13.1	-15.4
NYP	203	274	-17.2	-10.8	-6.4	-21.3	-7.1	-14.2
CBC	157	292	+11.3	+19.3	-8.1	+6.7	+20.7	-14.0
BB1	150	306	+6.5	-0.9	+7.3	-3.1	+10.8	-13.8
DGT	227	252	+11.1	-7.6	+18.7	+7.4	-5.8	+13.2
CB	247	238	-2.4	-14.0	+11.7	-3.2	-16.4	+13.2
RDJ	207	308	+14.9	-17.7	+32.6	+10.6	-2.2	+12.8
OF	199	254	-28.7	-20.6	-8.1	-25.7	-13.0	-12.7
TBC	254	273	+5.0	-13.0	+18.0	+3.8	-8.5	+12.3
MCP	345	248	+9.6	+12.2	-2.6	+22.7	+10.7	+12.0
GP	243	310	+1.4	-19.8	+21.2	-0.5	-12.4	+11.9
NE	188	202	-0.9	+10.4	-11.3	-9.2	+2.5	-11.7
ZL	232	162	-1.0	+20.3	-21.3	+0.5	+12.0	-11.5
HMR	231	296	+22.2	+24.8	-2.6	+12.7	+24.0	-11.3
PF	238	303	-13.1	-6.7	-6.4	-15.3	-4.0	-11.3
FCW	208	284	+4.7	-21.0	+25.7	-1.1	-12.3	+11.2
OB	283	201	-7.3	+15.8	-23.1	-2.9	+8.0	-10.9
MB	385	247	-19.1	-7.9	-11.1	+8.6	-2.3	+10.9
KBC	276	227	-29.4	-5.2	-24.2	-16.4	-6.2	-10.2
MCB	216	315	+24.2	-3.3	+27.6	+14.2	+4.4	+9.8
CS	258	184	-5.6	-8.7	+3.1	-5.2	-15.0	+9.8
WBC	144	226	+20.0	+7.1	+12.8	+14.7	+5.1	+9.6
TF	216	224	-3.9	+4.2	-8.1	-7.7	+0.6	-8.3
CNC	139	253	+3.0	+10.3	-7.3	-1.3	+6.9	-8.2
LP	234	206	-20.9	-25.0	+4.2	-14.9	-22.9	+8.0
HCC	279	327	-0.5	-15.7	+15.2	+0.9	-7.0	+7.9
SDC	410	311	-20.1	-13.4	-6.6	+5.8	-2.1	+7.9
KKK	164	369	+3.0	-22.6	+25.5	-5.9	+1.7	-7.7
LM	361	294	-3.3	+11.0	-14.3	+16.2	+8.7	+7.6
QBS	177	257	+10.7	+10.1	+0.6	-0.1	+7.0	-7.2
LAB	197	205	+15.5	+1.4	+14.1	+6.7	+0.3	+6.4
OH	276	345	+5.8	-0.1	+5.8	+5.2	+11.4	-6.2
BBC	185	157	-7.1	-5.8	-1.3	-10.9	-16.9	+6.0
KTH	295	187	+2.3	+11.9	-9.6	+9.2	+3.3	+5.9
PC	288	258	+5.4	-1.9	+7.3	+3.3	-2.3	+5.7
TF1	300	260	-4.2	+11.8	-16.1	+2.7	+7.9	-5.2
NYL	234	278	+18.8	+4.4	+14.4	+11.0	+6.5	+4.5
KBK	164	162	+11.9	+0.1	+11.8	+3.2	-1.1	+4.3
CCB	154	322	+10.1	-13.6	+23.7	-0.4	-4.6	+4.2
PPS	247	296	+9.8	+0.5	+9.3	+3.1	+6.7	-3.7
BB	237	168	+3.5	+14.5	-10.9	+2.8	+6.3	-3.5
CF	239	233	-23.8	-21.4	-2.4	-25.2	-21.8	-3.4
CGT	144	127	+0.7	-3.6	+4.3	-6.7	-9.7	+3.0
GB	184	227	+4.3	+9.0	-4.7	-2.6	-0.3	-2.4
KH	288	214	-22.0	-11.1	-10.9	-14.6	-12.4	-2.2
JF	152	255	+7.1	-12.8	+19.9	-7.0	-9.2	+2.1
KO	214	299	-2.6	-14.1	+11.5	-2.6	-4.6	+2.0
HM	277	266	+10.4	+17.1	-6.6	+12.1	+13.7	-1.6
YBC	338	241	-24.0	-5.5	-18.6	-4.8	-6.0	+1.2
SPD	245	216	-0.4	+1.7	-2.1	-4.3	-3.2	-1.1
NP	342	232	+3.3	+23.6	-20.3	+14.6	+15.8	-1.1

Sorted by |Net (refit)|. Off = RS − RS_BsR (positive = clustered hits well). Def = RA − RA_BsR (positive = opponents clustered against you — unlucky on D). Net = Off − Def. Both passes re-center to league means before residualising, so columns are directly comparable. The refit fits all four B coefficients (TB, H, HR, BB+HBP weights) jointly across offense and defense via coordinate- descent ternary search — 4 parameters from 60 datapoints (30 teams × 2 sides), warm-started from MLB defaults.

XO Crossover · Calibration MLB-anchor mean + sd vs O27 league mean + sd. By construction the XO map sends O27 league mean → MLB anchor mean exactly and matches the spread — these rows are the sourcing health check.

Method: xo = MLB_mean + ((value − O27_mean) / O27_sd) · MLB_sd. The linear-ratio rescaling was rejected for spread collapse — z-anchoring preserves rank AND spread. If any row's O27 sd is 0 (insufficient qualifying players), that stat falls through to the native value.

Stat	O27 mean	O27 sd	MLB mean	MLB sd	Health
Pitching
ERA	12.096	7.203	4.300	1.050	OK
ra27	14.889	8.205	4.300	1.050	OK
WHIP	2.128	0.840	1.300	0.140	OK
K/9	7.608	3.133	8.500	2.100	OK
BB/9	4.351	2.514	3.200	0.950	OK
HR/9	1.574	1.852	1.200	0.450	OK
oAVG	0.399	0.112	0.250	0.022	OK
oOBP	0.472	0.105	0.320	0.026	OK
oSLG	0.520	0.203	0.415	0.050	OK
oOPS	0.992	0.291	0.735	0.072	OK
Batting
AVG	0.463	0.130	0.250	0.024	OK
OBP	0.529	0.122	0.320	0.030	OK
SLG	0.719	0.269	0.415	0.055	OK
OPS	1.248	0.380	0.735	0.080	OK
wOBA	0.572	0.230	0.320	0.034	OK
BABIP	0.530	0.124	0.295	0.024	OK

Walk-Back Stop% has no MLB analog and is therefore not z-anchored. It's surfaced natively on the pitcher card and the leaders page as the O27-rule strand rate for the post-HR rule-placed runner.