Ryan Thompson

P Arizona Diamondbacks

Age 35 RHP 6'5" / 210 lbs MLB peak 0.1 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	32	MLBARI	67	66	3.26	3.10	19.1%	4.8%	1.1
2025	33	MIX2 levels	50	43	3.74	3.35	20.4%	6.1%	0.6	K 20.6% · BB 6.3% · FIP 3.49
2026	34	MIX2 levels	47	42	4.32	3.34	16.3%	5.8%	0.6	K 15.6% · BB 5.4% · FIP 3.40
2027PROJ	35	MLBARI	21	22	4.01	4.14	17.1%	5.8%	0.1
2028PROJ91% MLB	36	MLBARI	16	17	4.31	4.51	16.0%	6.4%	0.0

Last 3 seasons WAR 2.4 · Next 2 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs51

FB Velo10

K%10

CompsJean Machi (age 35) · Brendan Donnelly (age 35) · Hector Navarro (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109101vR 93

ERA4.01

FIP4.14

K%17.1%

BB%5.8%

K-BB%11.2%

Proj IP22

Value2027 · WAR

Runs saved vs league avg · 22 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL6060

CMD4545

K†4040

Statcast Percentiles

FB Velo

p1091.3

Whiff%

p1019.2%

p1015.6%

xwOBA vs

p510.311

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

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)
2015	23	MIX MLE	2 levels	43	0	63	256	60	17	4	0%	1.5	18.4%	8.0%	10.4%	2.3%	3.00	3.81	—
2015	23	MIX RAW	2 levels	43	0	63	256	60	17	4	0%	1.5	23.4%	6.6%	16.8%	1.6%	3.00	2.83	—
2016	24	MIX MLE	2 levels	43	0	75	314	65	19	3	0%	1.8	16.2%	6.8%	9.4%	1.0%	3.35	3.11	—
2016	24	MIX RAW	2 levels	43	0	75	314	65	19	3	0%	1.8	20.7%	6.1%	14.6%	1.0%	3.35	2.65	—
2017	25	MIX MLE	2 levels	37	0	67	290	61	11	5	0%	1.8	18.2%	4.5%	13.7%	1.4%	4.05	2.91	—
2017	25	MIX RAW	2 levels	37	0	67	290	61	11	5	0%	1.8	21.0%	3.8%	17.2%	1.7%	4.05	2.74	—
2019	27	MIX MLE	2 levels	16	5	23	101	25	6	1	31%	1.5	18.0%	7.3%	10.7%	1.4%	2.70	3.30	—
2019	27	MIX RAW	2 levels	16	5	23	101	25	6	1	31%	1.5	24.8%	5.9%	18.8%	1.0%	2.70	2.29	—
2020	28	MLB MLE	Tampa Bay Rays	25	1	26	114	23	8	4	4%	1.1	20.2%	7.0%	13.2%	3.6%	4.44	4.27	+0.1
2020	28	MLB RAW	Tampa Bay Rays	25	1	26	114	23	8	4	4%	1.1	20.2%	7.0%	13.2%	3.5%	4.44	4.24	+0.1
2021	29	MIX MLE	3 levels	41	0	38	151	45	10	3	0%	0.9	27.6%	5.2%	22.4%	2.3%	2.11	2.69	+0.9
2021	29	MIX RAW	3 levels	41	0	38	151	45	10	3	0%	0.9	29.8%	6.6%	23.2%	2.0%	2.11	2.55	+0.9
2022	30	MIX MLE	2 levels	48	0	44	185	40	10	4	0%	0.9	21.5%	5.0%	16.6%	2.3%	3.71	3.16	+0.7
2022	30	MIX RAW	2 levels	48	0	44	185	40	10	4	0%	0.9	21.6%	5.4%	16.2%	2.2%	3.71	3.15	+0.7
2023	31	MIX MLE	2 levels	46	0	53	208	49	19	3	0%	1.1	21.7%	8.6%	13.1%	1.5%	3.42	3.20	+0.8
2023	31	MIX RAW	2 levels	46	0	53	208	49	19	3	0%	1.1	23.6%	9.1%	14.4%	1.4%	3.42	3.06	+0.9
2024	32	MLB MLE	Arizona Diamondbacks	67	0	66	272	52	13	5	0%	1.0	19.1%	4.8%	14.3%	1.9%	3.26	3.16	+1.1
2024	32	MLB MLE	Arizona Diamondbacks	67	0	66	272	52	13	5	0%	1.0	19.1%	4.8%	14.3%	1.9%	3.26	3.16	+1.1
2024	32	MLB RAW	Arizona Diamondbacks	67	0	66	272	52	13	5	0%	1.0	19.1%	4.8%	14.3%	1.8%	3.26	3.10	+1.1
2025	33	MIX MLE	2 levels	50	0	43	181	37	11	4	0%	0.9	20.6%	6.3%	14.3%	2.4%	3.74	3.49	+0.5
2025	33	MIX MLE	2 levels	50	0	43	181	37	11	4	0%	0.9	20.6%	6.3%	14.3%	2.4%	3.74	3.49	+0.5
2025	33	MIX RAW	2 levels	50	0	43	181	37	11	4	0%	0.9	20.4%	6.1%	14.4%	2.2%	3.74	3.35	+0.6
2026	34	MIX MLE	2 levels	47	0	42	190	31	11	3	0%	0.9	15.6%	5.4%	10.2%	1.7%	4.32	3.40	+0.6
2026	34	MIX MLE	2 levels	47	0	42	190	31	11	3	0%	0.9	15.6%	5.4%	10.2%	1.7%	4.32	3.40	+0.6
2026	34	MIX RAW	2 levels	47	0	42	190	31	11	3	0%	0.9	16.3%	5.8%	10.5%	1.6%	4.32	3.34	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			300	1	282	1183	237	66	26	0%	0.9	20.0%	5.6%	14.5%	2.2%	3.67	3.32	+4.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	ARI	21	0	22	93	16	5	2	0%	1.0	17.1%	5.8%	11.2%	2.5%	4.01	4.14	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	ARI	18	0	19	81	13	5	2	0%	1.1	16.0%	6.4%	9.6%	2.9%	4.31	4.51	+0.0
2028	36	MLB CTX	ARI	16	0	17	72	12	5	2	0%	1.1	16.0%	6.4%	9.6%	2.9%	4.31	4.51	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		317	1	299	1257	249	71	28	0%	0.9	19.8%	5.6%	14.2%	2.2%	3.71	3.37	+4.2
/ 200 IP	—	RAW		211	1	200	839	166	47	19	0%	0.9	19.8%	5.6%	14.2%	2.2%	3.71	3.37	+2.8
Career	—	MLE		463	6	541	2262	438	140	42	1%	1.2	19.3%	6.2%	13.2%	1.9%	3.46	3.28	+4.1
/ 200 IP	—	MLE		171	2	200	837	162	52	16	1%	1.2	19.3%	6.2%	13.2%	1.9%	3.46	3.28	+2.7

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.

2023 AAAReno Aces · 22 IPFIP 1.98 → 2.20 (+0.22)K% 32.2% → 27.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.18%	—	×0.860	27.68%
BB% (unintentional) /BF	12.64%	—	×0.900	11.38%
HR / BF /BF	0.00%	÷1.012	×1.100	0.00%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 102).

Result: FIP 1.98 → 2.20, 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).

2019 AAMontgomery Biscuits · 20 IPFIP 2.68 → 3.30 (+0.63)K% 22.2% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.810	18.00%
BB% (unintentional) /BF	6.67%	—	×1.100	7.33%
HR / BF /BF	1.11%	÷0.920	×1.200	1.45%

Factors used: pitcher AA level factors — K ×0.81, BB ×1.10, HR ×1.20. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 84).

Result: FIP 2.68 → 3.30, 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).

2017 AACorpus Christi Hooks · 59 IPFIP 2.39 → 2.91 (+0.52)K% 22.4% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.45%	—	×0.810	18.18%
BB% (unintentional) /BF	4.08%	—	×1.100	4.49%
HR / BF /BF	1.22%	÷1.035	×1.200	1.42%

Result: FIP 2.39 → 2.91, 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).

2017 AAAFresno Grizzlies · 8 IPFIP 4.70 → 5.19 (+0.50)K% 13.3% → 11.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.33%	—	×0.880	11.73%
BB% (unintentional) /BF	2.22%	—	×1.050	2.33%
HR / BF /BF	4.44%	÷0.963	×1.100	5.08%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 93).

Result: FIP 4.70 → 5.19, 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).

2016 A+Lancaster JetHawks · 35 IPFIP 2.62 → 3.24 (+0.62)K% 26.6% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.58%	—	×0.770	20.47%
BB% (unintentional) /BF	5.70%	—	×1.150	6.55%
HR / BF /BF	1.90%	÷1.252	×1.250	1.90%

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 150).

Result: FIP 2.62 → 3.24, 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).

2016 AACorpus Christi Hooks · 40 IPFIP 2.67 → 2.98 (+0.32)K% 14.7% → 11.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.74%	—	×0.810	11.94%
BB% (unintentional) /BF	6.41%	—	×1.100	7.05%
HR / BF /BF	0.00%	÷1.196	×1.200	0.00%

Result: FIP 2.67 → 2.98, 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).

2015 AQuad Cities River Bandits · 54 IPFIP 2.85 → 3.81 (+0.96)K% 24.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.89%	—	×0.740	18.42%
BB% (unintentional) /BF	6.79%	—	×1.180	8.01%
HR / BF /BF	1.81%	÷1.032	×1.300	2.28%

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 106).

Result: FIP 2.85 → 3.81, 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).

2015 A+Lancaster JetHawks · 9 IPFIP 2.62 → 3.00 (+0.39)K% 14.3% → 11.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.29%	—	×0.770	11.00%
BB% (unintentional) /BF	5.71%	—	×1.150	6.57%
HR / BF /BF	0.00%	÷0.964	×1.250	0.00%

Result: FIP 2.62 → 3.00, 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
Ryan Thompson (OGILVIE)	—	—	4.14	17.1%	5.8%	2.5%	—	4.51	16.0%	9.6%	19	+0.37	—	—	—
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	78
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	76
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	75
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	72
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	70
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	69
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	69
Brian Schlitter R 2021 · 4.70 FIP	35	SU	4.70	14.9%	9.1%	3.1%	.318	—	—	—	—	—	3.27	300	68
Spencer Patton R 2023 · 4.33 FIP	35	SU	4.33	18.9%	9.7%	2.9%	.295	—	—	—	—	—	2.79	239	68
Juan Sandoval R 2016 · 3.24 FIP	35	SU	3.24	18.2%	10.2%	0.7%	.288	4.40	16.3%	9.1%	116	+1.16	3.24	225	67
Rudy Gonzalez R 2016 · 3.31 FIP	35	SU	3.31	12.9%	7.7%	0.6%	.250	4.72	15.8%	8.7%	29	+1.41	3.31	119	66
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	66
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	65
Toby Borland R 2004 · 4.28 FIP	35	SU	4.28	20.9%	8.1%	3.5%	.259	—	—	—	—	—	2.92	248	65
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	64
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	63
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	63
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	63
Seunghwan Oh R 2017 · 3.90 FIP	35	SU	3.90	20.5%	2.3%	4.1%	.299	3.45	26.6%	20.5%	87	-0.45	1.87	226	62
Jumbo Diaz R 2019 · 2.98 FIP	35	SU	2.98	25.0%	7.7%	1.8%	.290	—	—	—	—	—	2.80	319	61

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	1.6	36	19.6%	6.5%	0.87	3.73
Adam Cimber ('24)	1.6	54	18.0%	6.5%	0.75	3.75
George Kontos ('18)	1.8	51	19.8%	7.1%	0.96	3.10
Brandon Kintzler ('21)	2.4	60	16.8%	6.5%	0.88	3.50
Tony Castillo ('88-'98, 4 WAR*)	2.6	59	18.5%*	7.3%*	0.98*	3.76*
Ramon Hernandez ('67-'77, 6 WAR*)	2.2	61	19.7%*	7.3%*	0.77*	3.65*
Mike Perez ('90-'97, 3 WAR*)	1.7	58	18.5%*	8.2%*	0.88*	3.86*