Scott Bandura — OGILVIE

Scott BanduraOF Richmond Flying Squirrels

Age 24 L/R 6'3" / 190 lbs AA BB -3% Svc 0.0 · Ctrl thru 2034 peak 0.8 · 2026

wRC+†95

AVG/OBP/SLG.198 / .275 / .305

PA320

HR6

SB15

K%34

BB%8

MLB%2%

Scouting · now → future

HIT

50→50

PWR

40→40

SPD

60→60

EYE

49↗50

trajectory · 10 yrs

0.5peak

2029

Contract

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

Status MiLB

MLB Debut 2029

Service 0 yrs (est)

Team Control Through 2034

First FA Year 2035

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2029
2027	MiLB	still in minors · estimated debut 2029
2028	MiLB	still in minors · estimated debut 2029
2029	Arb-1	$0.8M	+0.5	$2M	+$1M
2030	Arb-2	$0.9M	+0.4	$2M	+$0.9M
2031	Arb-3	$0.9M	+0.2	$0.9M	+$0.0M
2032	Ext / FA-deal	$3M	—	—	—
2033	Ext / FA-deal	$0.4M	—	—	—
2034	Ext / FA-deal	$0.6M	—	—	—
Totals		$7M		$1M	-$5M

Why some years run red
On long-term deals the salary is locked in regardless of how the player ages. Late years are red whenever projected production drops below the AAV — that's expected, not a sign the deal is bad. The honest scorecard is the Net Surplus over the whole contract, not any single year.

Career Projections (MLE)

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	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
2023	21	A	2 teams	120	100	21	5	1	2	14	45	2	3	1	.210	.319	.340	.659	.130	.333	38	12	.292	82	-2	+0	+0	-1	+3	0.0
2024	22	A+	2 teams	373	331	59	11	2	4	30	134	9	24	5	.178	.265	.260	.525	.082	.281	36	8	.241	42	-24	+3	+0	-2	+11	-1.3
2025	23	A+	2 teams	559	501	107	18	3	8	46	188	8	41	2	.214	.290	.309	.599	.096	.321	34	8	.265	61	-24	+7	+0	-3	+16	-0.5
▸ 2026 Season (actual · ROS · total)
2026	24	AA	Richmond Flying Squirrels	83	73	24	7	2	1	4	16	3	5	1	.329	.388	.521	.908	.192	.404	19	5	.384	152	+5	+1	+0	-0	+2	0.7
ROS	24	MLB	SF	237	213	46	9	2	4	18	75	4	10	1	.216	.289	.333	.623	.117	.313	32	8	.284	76	-7	+2	+0	-1	+7	0.0
TOT	24	MLB	SF	320	286	70	16	4	5	22	91	7	15	2	.245	.314	.381	.695	.136	.339	28	7	.310	95	-2	+2	+0	-2	+9	0.8
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	25	MLB 11%	SF	370	330	73	14	3	7	31	111	6	14	2	.221	.300	.345	.645	.124	.307	30	8	.291	81	-8	+2	+0	-2	+10	0.2
2028	26	MLB 26%	SF	407	363	81	16	3	8	35	120	6	14	2	.223	.302	.350	.652	.127	.306	29	9	.295	84	-7	+2	+0	-2	+12	0.4
2029	27	MLB 44%	SF	420	374	84	16	3	9	37	122	6	14	1	.225	.305	.356	.660	.131	.305	29	9	.297	85	-7	+2	+0	-3	+12	0.5
2030	28	MLB 53%	SF	425	379	84	16	3	9	37	124	6	13	1	.222	.301	.351	.652	.129	.305	29	9	.296	85	-7	+2	-1	-3	+12	0.4
2031	29	MLB 64%	SF	420	374	82	16	3	8	37	124	6	11	1	.219	.300	.342	.642	.123	.304	30	9	.294	83	-8	+2	-1	-3	+12	0.2
2032	30	MLB 73%	SF	414	368	81	16	3	8	37	123	6	10	0	.220	.302	.345	.647	.125	.303	30	9	.291	81	-9	+2	-2	-2	+12	0.0
2033	31	MLB 81%	SF	401	357	78	15	3	8	35	121	6	8	0	.218	.299	.345	.644	.126	.301	30	9	.287	78	-10	+2	-3	-2	+11	-0.2
2034	32	MLB	SF	384	341	72	14	2	7	34	118	6	7	0	.211	.294	.326	.619	.114	.300	31	9	.283	75	-11	+1	-4	-2	+11	-0.5
2035	33	MLB	SF	355	316	66	13	2	6	31	111	5	6	0	.209	.290	.320	.609	.111	.298	31	9	.277	70	-12	+1	-4	-2	+10	-0.7
2036	34	MLB	SF	311	277	57	11	2	5	27	100	4	5	0	.206	.286	.314	.600	.108	.296	32	9	.271	66	-12	+1	-5	-2	+9	-0.9
▸ Career Totals (MLE all levels + projections)
Career	—			5196	4624	991	190	35	93	449	1616	80	180	16	.214	.295	.331	.626	.117	.305	31	9	.283	75	-149	+30	-20	-31	+147	-2.3
/ 162G	—			650	578	124	24	4	12	56	202	10	23	2	.215	.295	.332	.627	.118	.304	31	9	.283	75	-19	+4	-2	-4	+18	-0.3

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

Year	Age	Lvl	Team	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
2023	21	A	San Jose Giants	99	79	19	5	1	2	15	26	2	3	1	.241	.375	.405	.780	.165	.315	26	15	.344	122	+2	+0	—	—	+3	0.6
2023	21	ROK	ACL Giants Orange	21	15	6	1	0	1	5	6	0	0	0	.400	.550	.667	1.217	.267	.556	29	24	.499	240	+3	+0	—	—	+1	0.4
2024	22	A+	Eugene Emeralds	247	211	48	9	2	6	31	69	3	19	2	.227	.335	.374	.709	.147	.304	28	13	.320	103	+1	+3	—	—	+7	1.1
2024	22	A	San Jose Giants	126	105	29	7	1	0	14	24	6	5	3	.276	.392	.362	.754	.086	.354	19	11	.348	124	+3	-0	—	—	+4	0.7
2025	23	AA	Richmond Flying Squirrels	186	161	32	9	1	3	23	57	1	11	0	.199	.303	.323	.626	.124	.287	31	12	.287	78	-5	+2	—	—	+5	0.3
2025	23	A+	Eugene Emeralds	373	319	98	15	3	7	44	90	7	30	2	.307	.403	.439	.842	.132	.404	24	12	.377	147	+20	+5	—	—	+11	3.6

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
Scott Bandura (OGILVIE)	24	50	40	60	50	.198/.275/.305	.107	.296	6	12	34%	8%	62	-0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Eliezer Álvarez 2019 · AA	24	45→55	42→45	55	40	.218/.275/.328	.110	.315	9	21	32%	6%	66	-0.6	.193/.254/.297	.104	.312	10	16	39%	7%	50	-1.8	.173/.241/.263	.090	.287	9	13	40%	8%	32	-2.0
✕Kameron Misner 2022 · AA	24	43→42	43→50	55	43	.203/.278/.320	.117	.313	10	19	36%	8%	66	-0.6	.200/.289/.347	.147	.322	15	23	39%	10%	79	+0.3	.192/.287/.345	.153	.303	17	26	39%	11%	74	-0.0
✕Khalil Lee 2021 · AA	23	44→52	41→45	57→55	42	.207/.282/.306	.099	.324	9	28	36%	8%	65	-0.7	.207/.309/.341	.134	.340	12	16	39%	9%	86	+0.8	.194/.308/.336	.141	.334	13	13	40%	10%	81	+0.3
✕Ji Hwan Bae 2022 · AA	23	48→53	41→45	54→60	43	.230/.288/.333	.103	.317	7	22	29%	7%	73	-0.1	.242/.301/.350	.108	.317	8	29	24%	7%	82	+0.5	.248/.310/.350	.103	.323	8	33	24%	8%	84	+0.5
✕Drew Avans 2021 · AA	25	45→53	46→45	54→60	42	.222/.279/.347	.126	.302	13	20	30%	7%	73	-0.1	.225/.296/.338	.113	.325	8	28	30%	9%	78	+0.2	.218/.296/.324	.106	.311	8	30	30%	9%	71	-0.2
✕Darrell Ceciliani 2014 · AA	24	51→54	40→45	56→55	41	.240/.287/.337	.097	.320	7	21	26%	5%	73	-0.1	.245/.284/.355	.110	.324	10	21	26%	4%	77	+0.1	.241/.281/.357	.116	.309	11	21	25%	4%	74	-0.0
✕Travis Swaggerty 2022 · AAA	24	44→45	42→45	51→55	45	.213/.279/.317	.104	.294	10	16	30%	8%	66	-0.6	.215/.278/.334	.119	.306	10	19	31%	8%	69	-0.4	.209/.277/.321	.112	.309	8	20	32%	8%	62	-0.4
✕Slade Heathcott 2015 · AA	24	47	43→45	51→50	38	.222/.273/.335	.113	.326	9	16	34%	6%	67	-0.5	.230/.281/.335	.105	.321	10	10	30%	6%	71	-0.3	.230/.288/.345	.115	.317	12	10	30%	7%	74	-0.1
✕Canaan Smith-Njigba 2023 · AAA	24	50→47	42→45	54→55	48	.231/.306/.345	.114	.335	8	17	31%	10%	84	+0.6	.220/.287/.341	.121	.326	10	19	33%	9%	75	-0.0	.208/.277/.326	.118	.309	10	21	34%	9%	65	-0.4
✕Victor Labrada 2023 · A	23	42→52	41→45	54→60	39	.201/.265/.304	.103	.312	8	21	36%	7%	56	-1.3	.213/.280/.314	.101	.307	8	30	31%	7%	65	-0.7	.227/.304/.334	.106	.305	9	41	26%	8%	77	+0.1
✕Jeremy Hazelbaker 2012 · AA	24	42→52	43→55	59→60	41	.204/.268/.321	.117	.305	11	33	35%	7%	62	-0.9	.221/.269/.344	.123	.314	13	31	32%	5%	68	-0.5	.241/.302/.415	.174	.340	16	21	32%	7%	96	+0.8
✕Jared Oliva 2020 · AA	24	46	42→50	56→65	42	.223/.286/.326	.103	.303	9	27	28%	6%	71	-0.3	.218/.273/.320	.102	.304	8	24	29%	6%	63	-0.8	.224/.292/.359	.135	.282	14	55	25%	7%	78	+0.1
✕Luigi Rodriguez 2017 · AA	24	45→49	44→50	53→55	36	.218/.260/.335	.116	.319	11	18	34%	5%	61	-1.0	.229/.269/.371	.142	.350	16	15	37%	5%	76	+0.0	.231/.275/.385	.154	.349	19	14	38%	5%	78	+0.1
✕Daniel Fields 2015 · AAA	24	47→55	42→45	54→55	39	.226/.276/.334	.108	.314	9	18	30%	5%	68	-0.5	.199/.261/.298	.099	.306	8	16	35%	7%	53	-1.5	.176/.247/.262	.085	.285	7	16	38%	8%	35	-1.6
●Aneury Tavárez 2016 · AAA	24	42→52	43→45	51→50	33	.209/.247/.321	.112	.302	10	16	34%	4%	53	-1.5	.246/.286/.362	.116	.321	9	16	25%	5%	79	+0.3	.250/.290/.360	.110	.320	8	16	23%	5%	77	+0.1
✕Juan Silva 2015 · A	24	49→47	41→45	55	51	.234/.314/.339	.105	.310	8	27	26%	10%	85	+0.7	.218/.292/.308	.090	.286	6	18	24%	9%	69	-0.4	.196/.269/.272	.076	.260	4	10	24%	9%	46	-0.7
●Roger Bernadina 2008 · AAA	24	47→57	40→45	54→60	46	.224/.286/.316	.092	.294	8	26	26%	7%	68	-0.5	.262/.317/.373	.111	.341	9	29	24%	7%	95	+1.4	.263/.320/.391	.127	.327	12	31	22%	7%	97	+1.4
●Matthew den Dekker 2012 · AA	24	47→57	45→50	52→55	38	.223/.278/.354	.131	.330	11	14	34%	6%	74	-0.1	.234/.283/.370	.136	.329	12	16	31%	6%	81	+0.4	.247/.298/.381	.134	.332	11	18	28%	6%	88	+0.7
✕Forrest Wall 2019 · AA	23	45→55	41→45	52→70	41	.216/.272/.312	.096	.296	8	21	29%	6%	61	-1.0	.219/.279/.330	.111	.311	9	21	30%	7%	69	-0.4	.260/.332/.371	.111	.354	9	50	27%	9%	98	+1.0
✕Brennon Lund 2019 · AA	24	51→55	41→45	53→50	42	.241/.292/.339	.098	.318	8	16	26%	6%	76	+0.1	.217/.270/.335	.118	.302	10	11	30%	6%	66	-0.6	.194/.245/.319	.125	.273	12	6	32%	5%	50	-1.0

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)