2024 Projections

#	Name	Team	G	PA	HR	R	RBI	SB	BB%	K%	ISO	BABIP	AVG	OBP	SLG	wOBA	wRC+	BsR	Off	Def	WAR
1	Juan Soto	NYY	153	665	37	105	100	11	19.1%	16.6%	.265	.287	.279	.419	.543	.408	161	-2.1	47.6	-10.1	6.0
2	Yordan Alvarez	HOU	137	594	38	95	105	1	13.1%	19.5%	.296	.312	.295	.396	.591	.413	168	-1.5	46.9	-12.9	5.4
3	Randy Arozarena	SEA	148	636	25	87	80	25	10.4%	24.2%	.195	.311	.258	.349	.453	.347	120	-0.7	14.6	-9.6	2.7
4	Riley Greene	DET	136	588	17	77	64	10	8.7%	26.4%	.165	.357	.275	.342	.440	.338	115	-0.2	10.5	-4.4	2.6
5	Evan Carter	TEX	136	561	16	72	64	18	11.9%	25.3%	.167	.323	.253	.349	.420	.335	111	-0.8	6.5	-1.4	2.4
6	Chas McCormick	HOU	131	525	20	67	68	16	9.2%	26.0%	.178	.312	.253	.330	.431	.330	111	-0.8	5.8	-0.6	2.3
7	Taylor Ward	LAA	130	552	20	75	70	6	10.1%	20.8%	.187	.304	.264	.347	.451	.345	118	-0.9	11.2	-7.4	2.2
8	Steven Kwan	CLE	140	616	5	79	51	17	9.5%	10.2%	.098	.301	.275	.348	.373	.318	104	0.4	3.3	-1.8	2.2
9	Daulton Varsho	TOR	138	555	22	70	68	16	8.1%	23.3%	.191	.266	.232	.300	.423	.311	98	0.7	-0.4	2.5	2.1
10	Davis Schneider	TOR	98	400	16	50	49	5	11.9%	28.1%	.204	.289	.230	.330	.434	.332	112	-0.7	5.3	0.8	2.0
11	Tyler O'Neill	BOS	121	492	21	67	64	12	9.3%	27.1%	.202	.308	.250	.327	.452	.336	107	0.2	4.6	-4.9	1.6
12	Wyatt Langford	TEX	127	548	19	69	69	15	10.0%	21.9%	.186	.303	.258	.339	.444	.338	113	-0.5	8.2	-10.4	1.6
13	Masataka Yoshida	BOS	135	568	16	70	71	6	8.1%	13.1%	.158	.310	.289	.353	.447	.346	115	-1.7	8.2	-13.7	1.4
14	Alex Verdugo	NYY	124	527	13	65	56	4	7.6%	15.4%	.147	.293	.265	.324	.412	.319	101	-0.6	-0.3	-4.3	1.3
15	Jarren Duran	BOS	128	521	13	70	54	28	7.1%	25.4%	.164	.334	.261	.320	.425	.322	98	1.5	0.2	-4.7	1.3
16	Matt Wallner	MIN	110	439	17	55	56	3	11.0%	33.1%	.197	.321	.230	.332	.426	.329	111	-0.7	4.9	-6.9	1.3
17	MJ Melendez	KCR	133	559	20	70	65	5	11.0%	26.0%	.194	.300	.243	.329	.437	.330	108	-1.5	4.3	-11.7	1.2
18	Seth Brown	OAK	119	463	20	52	62	6	8.2%	27.0%	.201	.277	.230	.297	.432	.312	102	-1.0	0.1	-6.4	0.9
19	Andrew Benintendi	CHW	134	574	8	67	50	11	9.0%	15.3%	.108	.305	.266	.334	.374	.311	95	-0.2	-3.5	-6.6	0.9
20	Luke Raley	SEA	98	390	16	48	47	10	7.2%	31.5%	.185	.304	.230	.308	.415	.314	103	0.0	1.3	-5.4	0.9
21	Mitch Haniger	SEA	113	468	19	55	59	1	7.9%	26.1%	.188	.278	.233	.301	.422	.311	101	-1.1	-0.5	-7.7	0.8
22	Tommy Pham	KCR	88	357	10	45	40	11	10.0%	23.7%	.158	.302	.246	.326	.405	.319	101	0.3	0.5	-7.0	0.6
23	Manuel Margot	MIN	87	339	6	39	37	9	6.5%	16.6%	.120	.300	.260	.312	.380	.302	92	0.0	-3.4	-2.4	0.6
24	Austin Slater	BAL	69	235	6	30	23	6	10.3%	27.5%	.143	.334	.251	.336	.394	.322	102	0.3	1.0	-3.5	0.5
25	Mauricio Dubón	HOU	82	316	6	39	32	5	5.0%	14.6%	.121	.288	.261	.301	.382	.296	87	-0.4	-5.3	0.0	0.5
26	Colton Cowser	BAL	86	329	8	41	33	5	11.2%	29.7%	.133	.323	.233	.330	.366	.309	97	-0.5	-1.5	-4.7	0.5
27	Dairon Blanco	KCR	48	145	2	19	14	16	6.7%	24.5%	.125	.330	.255	.316	.380	.305	91	0.8	-0.8	0.6	0.5
28	Akil Baddoo	DET	65	242	6	30	23	9	10.7%	25.1%	.150	.294	.232	.315	.382	.305	92	0.5	-1.7	-1.9	0.5
29	Dominic Canzone	SEA	90	334	11	39	41	4	6.4%	19.8%	.167	.275	.244	.297	.411	.305	97	-0.7	-2.0	-4.7	0.5
30	Jasson Domínguez	NYY	42	177	5	24	20	7	10.1%	26.4%	.157	.307	.240	.320	.397	.313	96	0.0	-0.8	-1.0	0.4

#	Name	Team	G	PA	HR	R	RBI	SB	BB%	K%	ISO	BABIP	AVG	OBP	SLG	wOBA	wRC+	BsR	Off	Def	WAR
1	Juan Soto	NYY	153	665	37	105	100	11	19.1%	16.6%	.265	.287	.279	.419	.543	.408	161	-2.1	47.6	-10.1	6.0
2	Yordan Alvarez	HOU	137	594	38	95	105	1	13.1%	19.5%	.296	.312	.295	.396	.591	.413	168	-1.5	46.9	-12.9	5.4
3	Randy Arozarena	SEA	148	636	25	87	80	25	10.4%	24.2%	.195	.311	.258	.349	.453	.347	120	-0.7	14.6	-9.6	2.7
4	Riley Greene	DET	136	588	17	77	64	10	8.7%	26.4%	.165	.357	.275	.342	.440	.338	115	-0.2	10.5	-4.4	2.6
5	Evan Carter	TEX	136	561	16	72	64	18	11.9%	25.3%	.167	.323	.253	.349	.420	.335	111	-0.8	6.5	-1.4	2.4
6	Chas McCormick	HOU	131	525	20	67	68	16	9.2%	26.0%	.178	.312	.253	.330	.431	.330	111	-0.8	5.8	-0.6	2.3
7	Taylor Ward	LAA	130	552	20	75	70	6	10.1%	20.8%	.187	.304	.264	.347	.451	.345	118	-0.9	11.2	-7.4	2.2
8	Steven Kwan	CLE	140	616	5	79	51	17	9.5%	10.2%	.098	.301	.275	.348	.373	.318	104	0.4	3.3	-1.8	2.2
9	Daulton Varsho	TOR	138	555	22	70	68	16	8.1%	23.3%	.191	.266	.232	.300	.423	.311	98	0.7	-0.4	2.5	2.1
10	Davis Schneider	TOR	98	400	16	50	49	5	11.9%	28.1%	.204	.289	.230	.330	.434	.332	112	-0.7	5.3	0.8	2.0
11	Tyler O'Neill	BOS	121	492	21	67	64	12	9.3%	27.1%	.202	.308	.250	.327	.452	.336	107	0.2	4.6	-4.9	1.6
12	Wyatt Langford	TEX	127	548	19	69	69	15	10.0%	21.9%	.186	.303	.258	.339	.444	.338	113	-0.5	8.2	-10.4	1.6
13	Masataka Yoshida	BOS	135	568	16	70	71	6	8.1%	13.1%	.158	.310	.289	.353	.447	.346	115	-1.7	8.2	-13.7	1.4
14	Alex Verdugo	NYY	124	527	13	65	56	4	7.6%	15.4%	.147	.293	.265	.324	.412	.319	101	-0.6	-0.3	-4.3	1.3
15	Jarren Duran	BOS	128	521	13	70	54	28	7.1%	25.4%	.164	.334	.261	.320	.425	.322	98	1.5	0.2	-4.7	1.3
16	Matt Wallner	MIN	110	439	17	55	56	3	11.0%	33.1%	.197	.321	.230	.332	.426	.329	111	-0.7	4.9	-6.9	1.3
17	MJ Melendez	KCR	133	559	20	70	65	5	11.0%	26.0%	.194	.300	.243	.329	.437	.330	108	-1.5	4.3	-11.7	1.2
18	Seth Brown	OAK	119	463	20	52	62	6	8.2%	27.0%	.201	.277	.230	.297	.432	.312	102	-1.0	0.1	-6.4	0.9
19	Andrew Benintendi	CHW	134	574	8	67	50	11	9.0%	15.3%	.108	.305	.266	.334	.374	.311	95	-0.2	-3.5	-6.6	0.9
20	Luke Raley	SEA	98	390	16	48	47	10	7.2%	31.5%	.185	.304	.230	.308	.415	.314	103	0.0	1.3	-5.4	0.9
21	Mitch Haniger	SEA	113	468	19	55	59	1	7.9%	26.1%	.188	.278	.233	.301	.422	.311	101	-1.1	-0.5	-7.7	0.8
22	Tommy Pham	KCR	88	357	10	45	40	11	10.0%	23.7%	.158	.302	.246	.326	.405	.319	101	0.3	0.5	-7.0	0.6
23	Manuel Margot	MIN	87	339	6	39	37	9	6.5%	16.6%	.120	.300	.260	.312	.380	.302	92	0.0	-3.4	-2.4	0.6
24	Austin Slater	BAL	69	235	6	30	23	6	10.3%	27.5%	.143	.334	.251	.336	.394	.322	102	0.3	1.0	-3.5	0.5
25	Mauricio Dubón	HOU	82	316	6	39	32	5	5.0%	14.6%	.121	.288	.261	.301	.382	.296	87	-0.4	-5.3	0.0	0.5
26	Colton Cowser	BAL	86	329	8	41	33	5	11.2%	29.7%	.133	.323	.233	.330	.366	.309	97	-0.5	-1.5	-4.7	0.5
27	Dairon Blanco	KCR	48	145	2	19	14	16	6.7%	24.5%	.125	.330	.255	.316	.380	.305	91	0.8	-0.8	0.6	0.5
28	Akil Baddoo	DET	65	242	6	30	23	9	10.7%	25.1%	.150	.294	.232	.315	.382	.305	92	0.5	-1.7	-1.9	0.5
29	Dominic Canzone	SEA	90	334	11	39	41	4	6.4%	19.8%	.167	.275	.244	.297	.411	.305	97	-0.7	-2.0	-4.7	0.5
30	Jasson Domínguez	NYY	42	177	5	24	20	7	10.1%	26.4%	.157	.307	.240	.320	.397	.313	96	0.0	-0.8	-1.0	0.4

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ZiPS:ZiPS Projections courtesy of Dan Szymborski
ZiPS DC:ZiPS Projections pro-rated to Depth Charts playing time
Steamer:Steamer Projections courtesy of steamerprojections.com
Depth Charts:FanGraphs Depth Chart projections are a combination of ZiPS and Steamer projections with playing time allocated by our staff.
ATC:ATC Projections courtesy of Ariel Cohen
THE BAT:THE BAT projections courtesy of Derek Carty. DFS version of THE BAT available at RotoGrinders. Sports betting version of THE BAT available at EV Analytics
THE BAT X:THE BAT X projections courtesy of Derek Carty. DFS version of THE BAT X available at RotoGrinders. Sports betting version of THE BAT X available at EV Analytics

On-Pace - Every Game Played:Please note, these are not projections. They represent a player's current seasons stats pro-rated for the remaining games in the season if they were to play in every single remaining game*. This is not how a player will actually perform the rest of the season, and should not be used for anything other than your own personal amusement. (*Starters pitch every 4.5 days and relievers pitch every 2.5 days.)
On-Pace - Games Played %:Please note, these are not projections. They represent a player's current seasons stats prorated for the remaining games in the season if they were to play the same percentage of total games they have already played this season. This is not how a player will actually perform the rest of the season, and should not be used for anything other than your own personal amusement.
RoS:Rest of Season
Update:Updated In-Season

ADP:ADP data provided courtesy of National Fantasy Baseball Championship
Inter-Projection Standard Deviation (InterSD):The standard deviation of the underlying projections surrounding the ATC average auction value. InterSD describes how much the projections disagree about the value of a player. The larger the InterSD, the more projections differ.
Inter-Projection Skewness (InterSK):The skewness of the underlying projections surrounding the ATC average auction value. InterSK describes the symmetry of the underlying projections. A positive InterSK means that a player’s mean is being pulled to the upside; the majority of projections are lower than the ATC average. A negative InterSK means that a player’s mean is being pulled to the downside; the majority of projections are higher than the ATC average.
Intra-Projection Standard Deviation (IntraSD):The standard deviation of a player’s categorical Z-Scores. IntraSD is a measure of the dimension of a player’s statistical profile. The smaller the IntraSD, the more balanced the individual player’s category contributions are. The larger the IntraSD, the more unbalanced the player’s category contributions are.

ATL	CHC	ARI
MIA	CIN	COL
WSN	MIL	LAD
NYM	PIT	SDP
PHI	STL	SFG