Bryce Rainer

SS West Michigan Whitecaps

Age 22 L/R 6'3" / 195 lbs A+ HR -8% Svc 0.0 · Ctrl thru 2033

Overview

A+PROSPECTMiLBFA 2034

OGV OFP50OGV rank#38ETA2028MLB%11%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2025	20	ADET	149	.288/.390/.448	5	9	97	—	.246/.329/.392
2026	21	A+/A/INTL2 orgs	508	.253/.361/.450	19	17	75	—	.208/.292/.356
2027PROJ11% MLB	22	MLBDET	22	.211/.295/.359	1	0	89	0.0
2028PROJ53% MLB	23	MLBDET	233	.216/.300/.376	8	5	95	0.8
2029PROJ65% MLB	24	MLBDET	312	.220/.304/.387	11	7	99	1.2

Next 3 projected WAR 2.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2033Service0.0First FA2034

2027MiLB2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Arb-1$5M2032Arb-2$9M2033Arb-3$12M

Skills · percentileMiLB Statcast 2026 A+

wRC+81

wOBA78

ISO78

BB%76

Chase%73

Speed45

Career WAR0.0 WAR median (P10 0.0 / P90 21, comp-based) · star 7% · didn't stick 82%

CompsBo Naylor (age 23) · Austin Wells (age 23) · Scott Moore (age 22)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†89

AVG/OBP/SLG.211 / .295 / .359

PA22

HR1

K%36

BB%9

BABIP320

ISO200

MLB%11%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$37M ctrl surplus

Contract

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2029	Pre-Arb	$0.8M	+1.2	$8M	+$8M
2030	Pre-Arb	$0.8M	+1.5	$10M	+$9M
2031	Arb-1	$5M	+1.6	$9M	+$6M
2032	Arb-2	$9M	+1.6	$9M	+$4M
2033	Arb-3	$12M	+1.4	$7M	+$0.8M
Totals		$29M		$46M	+$29M

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how these numbers are built

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2025	20	A	Lakeland Flying Tigers	—	149	125	36	5	0	5	20	33	1	9	3	288	390	448	838	160	344	22	13	369	97	—	—	—	—	—	—
2026	21	A+	West Michigan Whitecaps	—	429	362	98	21	1	18	63	151	2	13	4	271	382	483	865	213	410	35	15	382	87	—	—	—	—	—	—
2026	21	A	Lakeland Flying Tigers	—	49	42	7	3	0	1	6	20	0	4	0	167	271	310	580	143	273	41	12	262	9	—	—	—	—	—	—
2026	21	INTL	Scottsdale Scorpions	—	30	27	4	2	0	0	2	11	0	0	0	148	207	222	429	74	235	37	7	192	16	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2025	20	A MLE	Lakeland Flying Tigers	—	149	130	32	4	0	5	15	45	1	9	3	246	329	392	721	146	312	30	10	311	97	—	—	—	—	—	—
2026	21	A+ MLE	West Michigan Whitecaps	—	429	380	83	17	1	13	45	192	2	13	4	218	304	371	676	153	387	45	10	297	87	—	—	—	—	—	—
2026	21	A MLE	Lakeland Flying Tigers	—	49	44	5	2	0	1	4	27	0	4	0	114	188	227	415	114	237	55	8	181	9	—	—	—	—	—	—
2025	20	A MLE	Lakeland Flying Tigers	—	149	130	32	4	0	5	15	45	1	9	3	246	329	392	721	146	325	30	10	311	97	—	—	—	—	—	—
2025	20	A RAW	Lakeland Flying Tigers	—	149	125	36	5	0	5	20	33	1	9	3	288	390	448	838	160	344	22	13	369	97	—	—	—	—	—	—
2026	21	A+ MLE	3 teams	—	508	450	94	20	1	15	52	233	2	17	4	209	294	358	651	149	383	46	10	285	79	—	—	—	—	—	—
2026	21	A+ RAW	3 teams	—	508	431	109	26	1	19	71	182	2	17	4	253	361	450	811	197	385	36	14	359	79	—	—	—	—	—	—
2025	20	A MLE	Lakeland Flying Tigers	—	149	132	32	4	0	5	15	45	1	9	3	242	329	386	715	144	312	30	10	311	97	—	—	—	—	—	—
2026	21	A+ MLE	3 teams	—	508	449	94	20	1	15	52	233	2	17	4	209	294	359	652	149	372	46	10	285	79	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2025	20	A MLE	Lakeland Flying Tigers	—	149	132	32	4	0	5	15	45	1	9	3	242	329	386	715	144	312	30	10	311	97	—	—	—	—	—	—
2026	21	A+ MLE	3 teams	—	508	449	94	20	1	15	52	233	2	17	4	209	294	359	652	149	372	46	10	285	79	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	DET	11%	562	497	107	20	2	18	56	210	4	12	3	215	299	369	668	154	326	37	10	299	89	-8	+1	+2	+6	+12	0.6
▸ 2027 — real world (MLB)
2027	22	MLB CTX	DET	11%	22	20	5	1	0	1	2	8	0	0	0	211	295	359	654	149	320	36	9	294	89	-0	+0	+0	+0	+0	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	DET	53%	438	388	86	16	2	15	44	159	3	9	2	221	304	386	690	166	325	36	10	308	95	-3	+1	+2	+5	+9	1.4
2029	24	MLB MLE	DET	65%	480	426	96	18	2	17	48	170	3	10	3	225	308	398	706	173	324	35	10	314	99	-1	+1	+2	+5	+10	1.8
2030	25	MLB MLE	DET	70%	505	447	102	19	2	19	50	176	3	10	3	227	310	405	715	178	322	35	10	318	101	+1	+1	+3	+5	+11	2.1
2031	26	MLB MLE	DET	72%	518	458	105	19	2	20	51	177	4	10	3	229	311	408	720	180	320	34	10	319	102	+1	+1	+3	+6	+11	2.3
2032	27	MLB MLE	DET	71%	521	461	106	20	2	19	51	176	4	10	3	229	311	406	717	177	318	34	10	318	102	+1	+1	+3	+6	+11	2.2
2033	28	MLB MLE	DET	71%	517	458	104	19	2	19	51	175	3	8	2	227	309	401	710	174	317	34	10	316	100	-0	+1	+2	+6	+11	2.0
2034	29	MLB MLE	DET	69%	506	448	101	19	2	18	50	173	3	6	2	225	306	395	702	171	316	34	10	312	97	-2	+0	+2	+5	+11	1.7
2035	30	MLB MLE	DET	68%	494	440	98	18	2	17	48	171	3	4	2	222	303	388	691	166	314	35	10	308	94	-3	+0	+1	+5	+11	1.4
2036	31	MLB MLE	DET	68%	477	425	92	17	1	16	46	167	3	1	1	218	298	378	677	160	311	35	10	302	91	-5	-0	+0	+5	+10	1.0
2037	32	MLB MLE	DET	67%	456	408	87	16	1	15	43	161	2	1	1	213	292	366	658	153	307	35	9	295	86	-8	-0	-1	+5	+10	0.6
2038	33	MLB MLE	DET	73%	421	377	78	14	1	13	39	151	2	0	1	207	285	351	636	144	301	36	9	286	80	-10	-0	-2	+5	+9	0.1
2028	23	MLB CTX	DET	53%	233	206	45	8	1	8	23	85	2	5	1	216	300	376	676	160	319	36	10	302	95	-1	+1	+1	+2	+5	0.8
2029	24	MLB CTX	DET	65%	312	276	61	11	1	11	31	111	2	7	2	220	304	387	691	167	318	36	10	308	99	-1	+1	+2	+3	+7	1.2
2030	25	MLB CTX	DET	70%	353	313	70	13	1	13	35	123	2	7	2	223	306	394	700	171	317	35	10	312	101	+0	+1	+2	+4	+8	1.5
2031	26	MLB CTX	DET	72%	372	329	74	14	1	14	37	127	3	7	2	224	307	397	705	173	315	34	10	313	102	+1	+1	+2	+4	+8	1.6
2032	27	MLB CTX	DET	71%	371	328	73	14	1	13	37	125	3	7	2	224	307	395	702	171	312	34	10	312	102	+1	+1	+2	+4	+8	1.6
2033	28	MLB CTX	DET	71%	366	325	72	13	1	13	36	124	2	6	2	222	305	390	695	168	312	34	10	310	100	-0	+0	+2	+4	+8	1.4
2034	29	MLB CTX	DET	69%	350	311	69	13	1	12	34	120	2	4	1	220	302	385	687	164	310	34	10	306	97	-1	+0	+1	+4	+8	1.2
2035	30	MLB CTX	DET	68%	337	299	65	12	1	11	33	116	2	3	1	217	299	377	676	160	308	34	10	302	94	-2	+0	+1	+4	+7	1.0
2036	31	MLB CTX	DET	68%	323	287	61	11	1	10	31	113	2	1	1	214	294	368	663	155	305	35	10	297	91	-4	-0	+0	+3	+7	0.7
2037	32	MLB CTX	DET	67%	307	273	57	10	1	9	29	109	2	0	1	209	289	356	645	148	301	36	9	289	86	-5	-0	-0	+3	+7	0.4
2038	33	MLB CTX	DET	73%	306	273	56	10	1	9	29	110	1	0	0	203	281	342	623	139	296	36	9	281	80	-7	+0	-1	+3	+7	0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3630	3220	703	129	11	123	355	1263	23	47	15	218	300	380	680	161	313	35	10	304	94	-20	+3	+11	+39	+79	11.5
/ 162G	—	A+C		—	650	577	126	23	2	22	64	226	4	8	3	218	301	380	681	161	312	35	10	304	94	-4	+1	+2	+7	+14	2.1
Career	—	MLE		—	6200	5502	1222	227	21	215	609	2213	37	99	31	222	304	388	692	166	324	36	10	307	94	-32	+5	+17	+59	+120	17.3
/ 162G	—	MLE		—	650	577	129	24	2	23	64	232	4	10	3	224	306	392	698	168	325	36	10	307	94	-4	+1	+2	+7	+14	2.0

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 A+West Michigan Whitecaps · 429 PAwOBA .373 → .297 (−76)K% 35.2% → 44.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	35.20%	÷1.000	×1.270	—	—	44.70%
BB% (unintentional) /PA	14.45%	÷1.000	×0.710	—	×1.027	10.54%
HBP% /PA	0.47%	—	×0.790	—	×1.027	0.38%
Singles /BIP	27.49%	÷1.000	×0.920	×1.050	×1.027	27.27%
Doubles /BIP	9.95%	÷1.000	×0.810	×1.050	×1.027	8.69%
Triples /BIP	0.47%	÷1.000	×0.850	×1.050	×1.027	0.43%
Home runs /BIP	8.53%	÷1.000	×0.800	—	×1.027	7.01%

Factors used: league row Midwest League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .373 → .297; ISO .213 → .161; BABIP .410 → .387. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2026 ALakeland Flying Tigers · 49 PAwOBA .261 → .181 (−80)K% 40.8% → 55.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	40.82%	÷1.000	×1.360	—	—	55.51%
BB% (unintentional) /PA	12.24%	÷1.000	×0.690	—	×1.015	8.58%
HBP% /PA	0.00%	—	×0.780	—	×1.015	0.00%
Singles /BIP	13.64%	÷1.000	×0.920	—	×1.015	12.73%
Doubles /BIP	13.64%	÷1.000	×0.830	—	×1.015	11.49%
Triples /BIP	0.00%	÷1.000	×0.910	—	×1.015	0.00%
Home runs /BIP	4.55%	÷1.000	×0.800	—	×1.015	3.69%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average).

Result: wOBA .261 → .181; ISO .143 → .095; BABIP .273 → .237. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 ALakeland Flying Tigers · 149 PAwOBA .367 → .311 (−56)K% 22.1% → 30.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.15%	÷0.998	×1.360	—	—	30.17%
BB% (unintentional) /PA	13.42%	÷0.945	×0.690	—	×1.030	10.10%
HBP% /PA	0.67%	—	×0.780	—	×1.030	0.54%
Singles /BIP	28.26%	÷1.051	×0.920	×1.011	×1.030	25.76%
Doubles /BIP	5.43%	÷0.971	×0.830	×1.011	×1.030	4.84%
Triples /BIP	0.00%	÷1.150	×0.910	×1.011	×1.030	0.00%
Home runs /BIP	5.43%	÷0.864	×0.800	—	×1.030	5.18%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 73, 1B 110, 2B 94, 3B 130, K 100, BB 89 — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.011.

Result: wOBA .367 → .311; ISO .160 → .144; BABIP .344 → .312. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Paul DeJonglast yr '25 career totals — 9 seasons, 3,500 PA	5.3	3,500	146	29	229	294	416	+36	+35	16.1	16.0
/162	664	28	6	+6.8	+6.6	3.1	pk7: 16
#2Greg Gagne'83-'97 * career totals — 13 seasons, 6,207 PA	9.3	6,207	111	108	249*	297*	394*	+65	+26	13.2	13.0
/162	664	12	12	+6.9	+2.8	1.4	pk7: 13
#3Khalil Greenelast yr '09 career totals — 7 seasons, 2,835 PA	4.3	2,835	90	25	245	302	422	+30	+14	13.0	13.0
/162	664	21	6	+7.1	+3.2	3.0	pk7: 13
#4Danny Espinosalast yr '17 career totals — 8 seasons, 3,267 PA	4.9	3,267	98	64	221	297	378	+16	+36	11.0	11.4
/162	664	20	13	+3.2	+7.3	2.2	pk7: 12
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 8 projected seasons	5.5	3,652	129	48	223	301	392	+39	+14	12.3	11.0
/162	664	24	9	+7.1	+2.6	2.2	pk7: 10
#5Alex Gonzalez'94-'06 * career totals — 12 seasons, 5,528 PA	8.3	5,528	137	97	232*	290*	379*	+55	+6	8.3	10.0
/162	664	16	12	+6.6	+0.8	1.0	pk7: 12
#6Kevin Elster'86-'00 * career totals — 9 seasons, 3,225 PA	4.9	3,225	88	14	223*	294*	388*	+34	+9	7.9	8.1
/162	664	18	3	+7.0	+1.9	1.6	pk7: 8

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Bryce Rainer (OGILVIE)	22	—	—	—	—	213/296/366	153	326	7	4	37%	10%	89	+0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Bo Naylor 2023 · AAA	23	42→46	50→55	54→50	49	211/301/366	155	290	17	16	32%	10%	90	+0.6	217/302/391	174	272	21	10	27%	10%	96	+1.0	206/293/384	178	246	22	6	26%	10%	92	+0.5
✕Austin Wells 2022 · A	23	43→44	48→55	56→50	47	212/302/359	147	307	15	12	34%	10%	88	+0.5	219/297/382	163	280	19	10	28%	9%	92	+0.7	215/296/383	167	260	20	8	25%	9%	91	+0.5
✕Scott Moore 2006 · A	22	47→50	49→55	50	40	227/290/380	153	332	17	15	35%	7%	88	+0.5	229/292/389	160	309	18	9	31%	7%	92	+0.7	236/301/378	142	289	16	5	23%	7%	91	+0.5
✕Jimmy Crooks 2023 · A	22	48→47	47→50	51→40	43	229/308/368	139	326	14	6	32%	8%	93	+0.8	238/300/361	123	328	12	4	29%	7%	88	+0.4	240/311/381	141	337	17	2	32%	8%	94	+0.6
✕Trey Sweeney 2022 · A	22	44→45	50	53→55	46	221/292/385	164	297	17	9	31%	9%	90	+0.6	211/284/353	142	277	15	19	28%	8%	80	-0.1	219/291/353	133	286	15	17	27%	8%	81	-0.1
✕Emmanuel Rodriguez 2024 · A	21	44→40	50→45	55→50	55	201/327/360	159	328	16	16	38%	15%	99	+1.2	225/344/381	156	362	16	16	36%	14%	109	+2.0	227/352/388	161	353	18	17	35%	15%	110	+0.9
●Jazz Chisholm Jr. 2020 · AA	22	39→49	53→60	54→60	38	203/265/376	173	304	22	14	39%	7%	79	-0.2	231/293/420	189	313	23	20	32%	7%	99	+1.2	247/318/446	199	301	28	36	27%	9%	115	+2.1
✕Addison Barger 2022 · A	22	40→49	50→55	52→45	36	200/265/354	154	321	18	7	41%	7%	74	-0.6	226/290/381	155	309	18	7	31%	7%	89	+0.5	222/291/386	164	273	18	6	25%	8%	89	+0.4
●Zack Gelof 2022 · A	22	48→53	49→55	54→55	43	235/299/383	148	333	16	17	33%	8%	93	+0.8	237/301/410	173	329	21	20	32%	8%	99	+1.3	233/299/410	177	319	22	24	33%	8%	97	+1.0
✕Kirk Nieuwenhuis 2010 · AA	22	50→51	48→60	51→50	43	241/307/393	152	335	13	11	30%	7%	97	+1.1	246/301/395	149	342	13	10	30%	7%	95	+1.0	221/299/412	191	304	20	11	32%	9%	99	+0.7
✕Everson Pereira 2023 · AA	22	47→49	52→55	54→50	39	232/288/405	173	334	20	16	36%	7%	93	+0.8	228/292/381	153	338	18	15	35%	7%	90	+0.6	220/292/370	150	322	19	15	35%	8%	84	+0.1
●Nolan Gorman 2022 · AAA	22	44→46	50→60	49→45	39	228/274/377	149	301	19	6	31%	5%	82	-0.0	228/292/429	201	304	29	7	34%	8%	101	+1.4	216/289/434	218	282	33	7	35%	9%	102	+1.2
✕Zack Collins 2017 · A	22	46→42	47→50	47→40	49	217/309/351	135	339	14	6	37%	12%	89	+0.5	194/292/340	146	302	16	3	37%	12%	81	-0.1	199/306/353	154	293	17	2	34%	13%	89	+0.4
✕Jarred Kelenic 2021 · AA	22	45→54	54→60	53→50	43	235/291/415	180	301	21	14	29%	7%	97	+1.1	229/294/412	183	290	21	13	27%	8%	97	+1.1	230/297/414	184	294	20	15	28%	8%	99	+1.1
✕Jason Martin 2018 · AA	22	43→52	49→60	47→50	41	221/271/374	153	296	16	13	31%	6%	80	-0.2	235/282/374	139	306	13	12	26%	6%	83	+0.1	226/292/414	187	279	24	8	28%	8%	94	+0.6
✕Shed Long Jr. 2018 · AA	22	48→50	47→50	50	43	237/295/379	142	319	15	10	30%	7%	90	+0.6	234/295/375	141	317	14	12	29%	7%	89	+0.5	230/294/371	141	309	14	12	29%	8%	86	+0.2
✕Marcelo Mayer 2024 · AA	21	42→47	49→50	50	43	213/279/366	153	297	17	12	33%	8%	81	-0.1	235/289/373	138	304	15	10	26%	7%	86	+0.3	240/295/371	130	302	14	9	24%	7%	87	+0.2
✕Ryan Ritter 2024 · AA	23	44→48	49→50	52→50	40	214/290/365	152	331	17	14	38%	8%	86	+0.3	231/304/361	130	324	13	14	31%	7%	90	+0.6	239/315/362	122	327	11	14	28%	7%	91	+0.4
●Colt Keith 2023 · A	21	50→53	47→55	53→45	45	241/305/384	143	332	14	8	30%	8%	95	+0.9	257/313/415	158	319	18	5	24%	7%	105	+1.7	260/320/417	157	316	18	4	23%	8%	107	+1.6
✕Jordan Danks 2009 · A	22	50	47→50	52→50	38	232/289/374	142	358	14	10	37%	6%	86	+0.3	231/290/348	117	336	10	13	32%	7%	80	-0.1	238/309/368	130	328	15	11	30%	9%	92	+0.5

Bryce Rainer

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps