Henry Lalane

P Tampa Tarpons

Age 23 LHP 6'7" / 211 lbs A Svc 0.0 · Ctrl thru 2033 peak 0.9 · 2028

Overview

APROSPECTMiLBFA 2034

OGV OFP40OGV rank#290ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	20	MIX2 levels	6	4	12	6.57	5.29	24.5%	17.0%	—	K 24.5% · BB 17.0% · FIP 5.25
2025	21	MIX2 levels	7	7	19	2.33	4.34	26.2%	16.7%	—	K 20.3% · BB 21.0% · FIP 5.21
2026	22	MIX2 levels	21	20	100	3.16	2.62	28.1%	8.4%	—	K 21.1% · BB 9.8% · FIP 3.59
2027PROJ	23	MLBSF	—	—	0	4.56	4.56	21.1%	10.4%	—
2028PROJ43% MLB	24	MLBSF	6	6	33	4.31	4.25	22.1%	9.6%	0.4
2029PROJ66% MLB	25	MLBSF	8	8	48	4.21	4.14	22.6%	9.1%	0.6

Next 3 projected WAR 1.0Projected 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$2M2032Arb-2$3M2033Arb-3$3M

Career WAR0.0 WAR median (P10 -0.3 / P90 6.6, comp-based) · star 2% · didn't stick 87%

CompsT.J. Sikkema (age 24) · Hayden Mullins (age 23) · Cole Ragans (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 104112vR 120

ERA4.56

FIP4.56

K%21.1%

BB%10.4%

K-BB%10.7%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$21M 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	+0.4	$1M	+$0.8M
2029	Pre-Arb	$0.8M	+0.6	$2M	+$1M
2030	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2031	Arb-1	$2M	+0.8	$2M	+$1M
2032	Arb-2	$3M	+0.7	$2M	+$0.3M
2033	Arb-3	$3M	+0.6	$2M	+$0.0M (cut)
Totals		$7M		$12M	+$6M

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 WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to the standard WAR scale.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2021	17	ROK MLE	DSL Yankees 2	12	12	41	188	39	25	2	100%	3.4	14.1%	16.6%	-2.5%	1.4%	3.70	4.78	—
2021	17	ROK RAW	DSL Yankees 2	12	12	41	188	39	25	2	100%	3.4	20.7%	13.3%	7.4%	1.1%	3.70	3.66	—
2022	18	ROK MLE	DSL NYY Yankees	11	11	48	198	52	14	0	100%	4.4	17.9%	8.8%	9.0%	0.0%	2.98	2.71	—
2022	18	ROK RAW	DSL NYY Yankees	11	11	48	198	52	14	0	100%	4.4	26.3%	7.1%	19.2%	0.0%	2.98	1.82	—
2023	19	ROK MLE	FCL Yankees	8	5	22	88	34	4	3	62%	2.7	26.3%	5.7%	20.6%	3.5%	4.57	3.50	—
2023	19	ROK RAW	FCL Yankees	8	5	22	88	34	4	3	62%	2.7	38.6%	4.5%	34.1%	3.4%	4.57	2.32	—
2024	20	MIX MLE	2 levels	6	4	12	53	13	9	2	67%	2.1	24.5%	17.0%	7.5%	3.8%	6.57	5.25	—
2024	20	MIX MLE	2 levels	6	4	12	53	13	9	2	67%	2.1	24.5%	17.0%	7.5%	3.8%	6.57	5.25	—
2024	20	MIX RAW	2 levels	6	4	12	53	13	9	2	67%	2.1	24.5%	17.0%	7.5%	3.8%	6.57	5.29	—
2025	21	MIX MLE	2 levels	7	7	19	84	22	14	2	100%	2.8	20.3%	21.0%	-0.7%	2.1%	2.33	5.21	—
2025	21	MIX MLE	2 levels	7	7	19	84	22	14	2	100%	2.8	20.3%	21.0%	-0.7%	2.1%	2.33	5.21	—
2025	21	MIX RAW	2 levels	7	7	19	84	22	14	2	100%	2.8	26.2%	16.7%	9.5%	2.4%	2.33	4.34	—
2026	22	MIX MLE	2 levels	21	20	100	405	114	34	6	95%	4.7	21.1%	9.8%	11.3%	1.9%	3.16	3.59	—
2026	22	MIX MLE	2 levels	21	20	100	405	114	34	6	95%	4.7	21.1%	9.8%	11.3%	1.9%	3.16	3.59	—
2026	22	MIX RAW	2 levels	21	20	100	405	114	34	6	95%	4.7	28.1%	8.4%	19.8%	1.5%	3.16	2.62	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	SF	—	—	0	—	—	—	—	—	—	21.1%	10.4%	10.7%	2.8%	4.56	4.56	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	SF	14	14	78	328	72	31	9	100%	5.5	22.1%	9.6%	12.5%	2.8%	4.43	4.37	+0.9
2029	25	MLB MLE	SF	12	12	73	307	69	28	9	100%	6.1	22.6%	9.1%	13.5%	2.8%	4.33	4.26	+1.0
2030	26	MLB MLE	SF	12	12	72	303	69	27	9	100%	6.0	22.8%	9.0%	13.8%	2.8%	4.28	4.24	+1.0
2031	27	MLB MLE	SF	12	12	70	295	67	27	8	100%	5.8	22.8%	9.0%	13.7%	2.9%	4.28	4.28	+0.9
2032	28	MLB MLE	SF	11	11	66	280	63	26	8	100%	6.0	22.6%	9.2%	13.5%	3.0%	4.33	4.36	+0.8
2033	29	MLB MLE	SF	10	10	62	260	58	24	8	100%	6.2	22.4%	9.4%	13.0%	3.1%	4.43	4.49	+0.7
2034	30	MLB MLE	SF	10	10	61	259	62	23	9	100%	6.1	24.0%	8.9%	15.2%	3.3%	4.41	4.40	+0.7
2035	31	MLB MLE	SF	9	9	54	229	54	21	8	100%	6.0	23.6%	9.2%	14.4%	3.5%	4.52	4.60	+0.5
2036	32	MLB MLE	SF	8	8	47	199	46	19	8	100%	5.9	23.2%	9.6%	13.6%	3.8%	4.70	4.83	+0.3
2028	24	MLB CTX	SF	6	6	33	139	31	13	4	100%	5.5	22.1%	9.6%	12.5%	2.6%	4.31	4.25	+0.4
2029	25	MLB CTX	SF	8	8	48	203	46	18	5	100%	6.0	22.6%	9.1%	13.5%	2.6%	4.21	4.14	+0.6
2030	26	MLB CTX	SF	10	10	57	241	55	22	6	100%	5.7	22.8%	9.0%	13.8%	2.6%	4.16	4.12	+0.8
2031	27	MLB CTX	SF	10	10	59	249	57	22	7	100%	5.9	22.8%	9.0%	13.7%	2.7%	4.16	4.16	+0.8
2032	28	MLB CTX	SF	10	10	59	249	56	23	7	100%	5.9	22.6%	9.2%	13.5%	2.7%	4.21	4.24	+0.7
2033	29	MLB CTX	SF	9	9	56	236	53	22	7	100%	6.2	22.4%	9.4%	13.0%	2.9%	4.30	4.36	+0.6
2034	30	MLB CTX	SF	10	10	57	241	58	21	7	100%	5.7	24.0%	8.9%	15.2%	3.1%	4.27	4.26	+0.7
2035	31	MLB CTX	SF	8	8	51	215	51	20	7	100%	6.4	23.6%	9.2%	14.4%	3.3%	4.37	4.45	+0.5
2036	32	MLB CTX	SF	7	7	44	186	43	18	7	100%	6.3	23.2%	9.6%	13.6%	3.5%	4.54	4.67	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		78	78	464	1959	449	180	56	100%	5.9	22.9%	9.2%	13.7%	2.9%	4.27	3.91	+8.3
/ 200 IP	—	RAW		34	34	200	844	194	78	24	100%	6.0	22.9%	9.2%	13.7%	2.9%	4.27	3.91	+3.6
Career	—	MLE		65	59	243	1016	200	120	17	91%	3.7	19.7%	11.8%	7.9%	1.7%	3.45	3.85	+6.8
/ 200 IP	—	MLE		54	49	200	837	165	99	14	91%	3.7	19.7%	11.8%	7.9%	1.7%	3.45	3.85	+2.3

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 ATampa Tarpons · 62 IPFIP 1.68 → 2.67 (+0.99)K% 32.8% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.79%	—	×0.740	24.27%
BB% (unintentional) /BF	8.91%	—	×1.180	10.51%
HR / BF /BF	0.40%	÷1.000	×1.300	0.53%

Factors used: pitcher A level factors — K ×0.74, BB ×1.18, HR ×1.30. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 1.68 → 2.67, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2026 A+Eugene Emeralds · 37 IPFIP 4.04 → 5.02 (+0.98)K% 20.9% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.89%	—	×0.770	16.08%
BB% (unintentional) /BF	7.59%	—	×1.150	8.73%
HR / BF /BF	3.16%	÷1.000	×1.250	3.96%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 4.04 → 5.02, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2025 ATampa Tarpons · 16 IPFIP 3.79 → 5.21 (+1.42)K% 27.4% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.40%	—	×0.740	20.27%
BB% (unintentional) /BF	17.81%	—	×1.180	21.01%
HR / BF /BF	1.37%	÷0.842	×1.300	2.12%

Result: FIP 3.79 → 5.21, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 ATampa Tarpons · 6 IPFIP 5.21 → 6.81 (+1.60)K% 25.0% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.740	18.50%
BB% (unintentional) /BF	17.86%	—	×1.180	21.07%
HR / BF /BF	3.57%	÷0.979	×1.300	4.74%

Result: FIP 5.21 → 6.81, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 ROKFCL Yankees · 6 IPFIP 5.30 → 6.95 (+1.65)K% 24.0% → 16.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.00%	—	×0.680	16.32%
BB% (unintentional) /BF	16.00%	—	×1.250	20.00%
HR / BF /BF	4.00%	÷1.142	×1.400	4.91%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 128).

Result: FIP 5.30 → 6.95, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2023 ROKFCL Yankees · 22 IPFIP 2.28 → 3.50 (+1.21)K% 38.6% → 26.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.64%	—	×0.680	26.27%
BB% (unintentional) /BF	4.55%	—	×1.250	5.68%
HR / BF /BF	3.41%	÷1.383	×1.400	3.45%

Result: FIP 2.28 → 3.50, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2022 ROKDSL NYY Yankees · 48 IPFIP 1.78 → 2.71 (+0.93)K% 26.3% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.26%	—	×0.680	17.86%
BB% (unintentional) /BF	7.07%	—	×1.250	8.84%
HR / BF /BF	0.00%	÷1.195	×1.400	0.00%

Result: FIP 1.78 → 2.71, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2021 ROKDSL Yankees 2 · 41 IPFIP 3.62 → 4.78 (+1.17)K% 20.7% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.74%	—	×0.680	14.11%
BB% (unintentional) /BF	13.30%	—	×1.250	16.62%
HR / BF /BF	1.06%	÷1.063	×1.400	1.40%

Result: FIP 3.62 → 4.78, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Henry Lalane (OGILVIE)	—	—	—	—	—	2.8%	—	4.29	22.5%	13.2%	222	-0.27	—	—	—
T.J. Sikkema L 2022 · 4.55 FIP	24	SP	4.55	21.9%	9.0%	3.9%	.298	4.54	16.9%	7.5%	231	-0.01	3.57	300	88
Hayden Mullins L 2024 · 4.39 FIP	23	SP-	4.39	23.4%	12.4%	3.1%	.288	3.69	25.5%	11.8%	194	-0.70	3.54	283	85
Cole Ragans L 2021 · 5.14 FIP	23	SP	5.14	20.2%	11.2%	4.2%	.296	3.34	26.8%	17.5%	445	-1.80	2.48	623	85
Matt Mikulski L 2022 · 4.92 FIP	23	SP-	4.92	19.4%	10.0%	4.0%	.360	6.03	16.3%	-2.8%	144	+1.11	4.92	223	84
Anthony Veneziano L 2021 · 4.27 FIP	23	SP	4.27	24.9%	10.8%	3.5%	.298	4.94	18.6%	8.6%	358	+0.67	4.18	539	84
Christian MacLeod L 2023 · 4.52 FIP	23	SP	4.52	16.4%	10.5%	2.7%	.312	4.61	19.4%	5.0%	215	+0.09	3.88	280	84
A.J. Block L 2021 · 3.72 FIP	23	SP-	3.72	22.8%	10.0%	2.3%	.262	5.74	20.1%	8.4%	51	+2.02	3.65	203	83
Jimmy Robbins L 2022 · 3.85 FIP	24	SP-	3.85	23.3%	11.3%	2.3%	.286	4.82	18.0%	2.8%	99	+0.97	3.85	176	83
Robby Ahlstrom L 2022 · 4.62 FIP	23	SP-	4.62	20.1%	9.0%	3.8%	.349	4.04	21.9%	8.9%	175	-0.58	3.79	332	83
Sam Weatherly L 2021 · 4.07 FIP	22	SP	4.07	24.0%	12.8%	2.5%	.323	4.14	21.9%	8.9%	41	+0.07	4.07	212	83
Hunter Barco L 2024 · 3.61 FIP	23	SP	3.61	23.4%	10.0%	2.2%	.275	3.72	21.1%	10.0%	195	+0.11	3.29	257	83
Brian Holmes L 2015 · 4.32 FIP	24	SP-	4.32	21.0%	9.9%	3.2%	.333	4.78	17.3%	8.0%	104	+0.46	3.60	205	83
Samy Natera Jr. L 2023 · 5.14 FIP	23	SP	5.14	22.9%	13.3%	4.2%	.294	3.26	30.7%	17.2%	124	-1.88	1.94	208	83
Joe Whitman L 2024 · 3.89 FIP	22	SP	3.89	18.6%	9.9%	2.0%	.303	3.65	19.8%	11.7%	252	-0.24	3.51	355	82
Evan Lee L 2021 · 3.84 FIP	24	SP	3.84	24.2%	11.1%	2.5%	.333	4.49	21.0%	2.7%	52	+0.65	3.82	129	82
Jake Bennett L 2023 · 3.41 FIP	22	SP	3.41	21.2%	7.2%	2.2%	.339	3.29	19.3%	13.9%	222	-0.12	3.22	285	82
Hogan Harris L 2019 · 3.84 FIP	22	SP	3.84	20.5%	10.6%	2.1%	.235	3.71	27.4%	12.7%	74	-0.13	3.09	501	81
Brandon Knarr L 2021 · 4.86 FIP	23	SP	4.86	22.6%	13.6%	3.5%	.299	4.15	19.9%	10.8%	158	-0.71	4.08	256	81
Pete Hansen L 2023 · 4.18 FIP	23	SP	4.18	20.1%	9.9%	2.8%	.283	3.85	18.0%	10.5%	367	-0.33	3.77	480	80
Brad Halsey L 2004 · 4.31 FIP	23	SP	4.31	16.3%	9.2%	2.6%	.336	4.43	11.9%	5.4%	254	+0.12	4.31	286	80

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	3.3	65	22.7%	9.3%	1.18	4.42
David Hernandez ('19)	3.2	65	23.9%	9.1%	1.22	4.12
Stan Belinda ('00)	3.4	61	21.3%	9.9%	1.13	4.12
Dan Miceli ('06)	3.5	64	20.6%	10.1%	1.19	4.48
Xavier Hernandez ('89-'98, 3 WAR*)	3.4	67	23.9%*	9.1%*	1.12*	4.20*
Rob Murphy ('85-'95, 6 WAR*)	3.1	69	25.2%*	9.2%*	1.07*	3.94*
Frank DiPino ('81-'93, 3 WAR*)	3.5	78	22.5%*	9.0%*	1.00*	4.44*