2024 Projections

#	Name	Team	G	PA	HR	R	RBI	SB	BB%	K%	ISO	BABIP	AVG	OBP	SLG	wOBA	wRC+	BsR	Off	Def	WAR
1	Pete Alonso	NYM	152	649	41	89	109	4	10.1%	21.5%	.265	.257	.250	.340	.515	.360	128	-2.3	20.0	-12.5	3.0
2	Matt Olson	ATL	152	661	40	101	111	1	13.1%	22.4%	.267	.288	.265	.366	.532	.379	138	-1.2	29.7	-10.2	4.2
3	Vladimir Guerrero Jr.	TOR	152	659	31	89	96	6	10.1%	15.0%	.217	.292	.282	.361	.499	.366	136	-2.5	26.1	-13.4	3.5
4	Jake Burger	MIA	145	590	31	72	82	1	6.5%	27.3%	.228	.296	.249	.309	.478	.334	109	-1.1	5.4	-3.6	2.2
5	Spencer Torkelson	DET	148	629	29	79	84	3	10.3%	24.0%	.216	.277	.242	.326	.457	.337	114	-0.9	9.7	-14.1	1.7
6	Bryce Harper	PHI	146	631	29	94	91	13	14.1%	21.4%	.233	.325	.282	.388	.515	.383	141	-1.8	30.4	-11.6	4.0
7	Christian Walker	ARI	149	629	28	80	91	7	9.6%	20.3%	.208	.277	.252	.330	.460	.339	112	-0.6	8.8	-8.8	2.1
8	Rhys Hoskins	MIL	137	585	27	75	79	2	11.9%	25.0%	.220	.275	.236	.334	.456	.341	113	-2.0	7.7	-11.4	1.6
9	Christian Encarnacion-Strand	CIN	128	525	27	68	81	3	6.8%	26.7%	.225	.318	.265	.324	.490	.346	112	-1.1	6.6	-11.0	1.3
10	Triston Casas	BOS	142	578	27	75	78	1	13.5%	23.8%	.221	.298	.254	.358	.475	.358	123	-1.8	14.2	-11.8	2.2
11	Freddie Freeman	LAD	153	676	26	109	96	15	11.1%	16.1%	.205	.336	.305	.390	.511	.383	144	0.0	36.3	-11.3	4.8
12	Paul Goldschmidt	STL	147	644	24	87	84	7	12.0%	22.7%	.183	.314	.264	.355	.447	.347	120	-0.6	15.0	-11.3	2.6
13	Cody Bellinger	CHC	138	583	23	81	81	17	8.0%	19.8%	.190	.290	.261	.322	.451	.330	108	0.6	6.4	-2.3	2.4
14	Anthony Rizzo	NYY	126	535	22	67	67	3	9.3%	20.5%	.185	.265	.238	.330	.423	.328	107	-2.4	1.9	-10.1	1.0
15	Ryan Mountcastle	BAL	126	527	22	64	72	4	7.5%	24.0%	.187	.309	.262	.320	.449	.329	112	-0.5	6.8	-11.4	1.3
16	Andrew Vaughn	CHW	139	579	21	65	74	0	6.6%	19.7%	.177	.293	.260	.318	.437	.325	105	-2.3	1.3	-11.1	1.0
17	Josh Naylor	CLE	133	558	21	64	85	8	7.4%	14.5%	.183	.293	.278	.335	.461	.338	118	-1.6	10.2	-12.4	1.7
18	Josh Bell	ARI	143	604	21	69	73	0	10.9%	19.6%	.170	.287	.253	.338	.423	.331	106	-2.7	2.1	-14.7	0.8
19	Vinnie Pasquantino	KCR	132	562	20	68	73	1	10.4%	12.7%	.192	.281	.273	.353	.464	.351	123	-1.9	13.6	-11.6	2.1
20	Spencer Steer	CIN	137	582	20	71	74	10	9.4%	21.5%	.183	.298	.255	.335	.438	.335	105	-0.8	2.6	-6.4	1.6
21	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
22	Joey Gallo	WSN	97	372	19	45	47	2	14.2%	38.7%	.225	.255	.185	.308	.410	.313	95	-0.3	-2.8	-6.0	0.4
23	Rowdy Tellez	PIT	107	419	18	44	58	1	9.7%	21.4%	.194	.261	.236	.315	.430	.319	98	-1.5	-2.7	-8.5	0.3
24	José Abreu		137	585	18	68	79	0	7.9%	20.6%	.156	.296	.255	.324	.411	.319	103	-1.9	0.5	-12.1	0.8
25	Ryan Noda	OAK	126	519	18	62	55	5	13.5%	33.1%	.173	.308	.217	.335	.390	.321	108	-0.9	4.1	-9.0	1.3
26	Nathaniel Lowe	TEX	136	582	18	71	69	2	10.9%	22.9%	.163	.330	.269	.352	.431	.341	115	-2.3	8.2	-10.3	1.8
27	Elehuris Montero	COL	105	414	17	52	57	1	6.5%	28.9%	.197	.318	.251	.308	.448	.324	87	-0.7	-7.2	-8.1	-0.1
28	Patrick Wisdom	CHC	77	295	17	38	43	4	9.6%	35.7%	.237	.270	.210	.295	.447	.318	100	-0.4	-0.5	-2.3	0.7
29	Yandy Díaz	TBR	136	591	17	81	68	1	12.0%	14.6%	.157	.324	.293	.384	.450	.364	131	-2.5	20.2	-9.7	3.1
30	Alec Bohm	PHI	141	594	16	70	76	4	6.8%	17.2%	.145	.306	.272	.325	.417	.321	100	-1.6	-1.6	-2.6	1.6

#	Name	Team	G	PA	HR	R	RBI	SB	BB%	K%	ISO	BABIP	AVG	OBP	SLG	wOBA	wRC+	BsR	Off	Def	WAR
1	Pete Alonso	NYM	152	649	41	89	109	4	10.1%	21.5%	.265	.257	.250	.340	.515	.360	128	-2.3	20.0	-12.5	3.0
2	Matt Olson	ATL	152	661	40	101	111	1	13.1%	22.4%	.267	.288	.265	.366	.532	.379	138	-1.2	29.7	-10.2	4.2
3	Vladimir Guerrero Jr.	TOR	152	659	31	89	96	6	10.1%	15.0%	.217	.292	.282	.361	.499	.366	136	-2.5	26.1	-13.4	3.5
4	Jake Burger	MIA	145	590	31	72	82	1	6.5%	27.3%	.228	.296	.249	.309	.478	.334	109	-1.1	5.4	-3.6	2.2
5	Spencer Torkelson	DET	148	629	29	79	84	3	10.3%	24.0%	.216	.277	.242	.326	.457	.337	114	-0.9	9.7	-14.1	1.7
6	Bryce Harper	PHI	146	631	29	94	91	13	14.1%	21.4%	.233	.325	.282	.388	.515	.383	141	-1.8	30.4	-11.6	4.0
7	Christian Walker	ARI	149	629	28	80	91	7	9.6%	20.3%	.208	.277	.252	.330	.460	.339	112	-0.6	8.8	-8.8	2.1
8	Rhys Hoskins	MIL	137	585	27	75	79	2	11.9%	25.0%	.220	.275	.236	.334	.456	.341	113	-2.0	7.7	-11.4	1.6
9	Christian Encarnacion-Strand	CIN	128	525	27	68	81	3	6.8%	26.7%	.225	.318	.265	.324	.490	.346	112	-1.1	6.6	-11.0	1.3
10	Triston Casas	BOS	142	578	27	75	78	1	13.5%	23.8%	.221	.298	.254	.358	.475	.358	123	-1.8	14.2	-11.8	2.2
11	Freddie Freeman	LAD	153	676	26	109	96	15	11.1%	16.1%	.205	.336	.305	.390	.511	.383	144	0.0	36.3	-11.3	4.8
12	Paul Goldschmidt	STL	147	644	24	87	84	7	12.0%	22.7%	.183	.314	.264	.355	.447	.347	120	-0.6	15.0	-11.3	2.6
13	Cody Bellinger	CHC	138	583	23	81	81	17	8.0%	19.8%	.190	.290	.261	.322	.451	.330	108	0.6	6.4	-2.3	2.4
14	Anthony Rizzo	NYY	126	535	22	67	67	3	9.3%	20.5%	.185	.265	.238	.330	.423	.328	107	-2.4	1.9	-10.1	1.0
15	Ryan Mountcastle	BAL	126	527	22	64	72	4	7.5%	24.0%	.187	.309	.262	.320	.449	.329	112	-0.5	6.8	-11.4	1.3
16	Andrew Vaughn	CHW	139	579	21	65	74	0	6.6%	19.7%	.177	.293	.260	.318	.437	.325	105	-2.3	1.3	-11.1	1.0
17	Josh Naylor	CLE	133	558	21	64	85	8	7.4%	14.5%	.183	.293	.278	.335	.461	.338	118	-1.6	10.2	-12.4	1.7
18	Josh Bell	ARI	143	604	21	69	73	0	10.9%	19.6%	.170	.287	.253	.338	.423	.331	106	-2.7	2.1	-14.7	0.8
19	Vinnie Pasquantino	KCR	132	562	20	68	73	1	10.4%	12.7%	.192	.281	.273	.353	.464	.351	123	-1.9	13.6	-11.6	2.1
20	Spencer Steer	CIN	137	582	20	71	74	10	9.4%	21.5%	.183	.298	.255	.335	.438	.335	105	-0.8	2.6	-6.4	1.6
21	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
22	Joey Gallo	WSN	97	372	19	45	47	2	14.2%	38.7%	.225	.255	.185	.308	.410	.313	95	-0.3	-2.8	-6.0	0.4
23	Rowdy Tellez	PIT	107	419	18	44	58	1	9.7%	21.4%	.194	.261	.236	.315	.430	.319	98	-1.5	-2.7	-8.5	0.3
24	José Abreu		137	585	18	68	79	0	7.9%	20.6%	.156	.296	.255	.324	.411	.319	103	-1.9	0.5	-12.1	0.8
25	Ryan Noda	OAK	126	519	18	62	55	5	13.5%	33.1%	.173	.308	.217	.335	.390	.321	108	-0.9	4.1	-9.0	1.3
26	Nathaniel Lowe	TEX	136	582	18	71	69	2	10.9%	22.9%	.163	.330	.269	.352	.431	.341	115	-2.3	8.2	-10.3	1.8
27	Elehuris Montero	COL	105	414	17	52	57	1	6.5%	28.9%	.197	.318	.251	.308	.448	.324	87	-0.7	-7.2	-8.1	-0.1
28	Patrick Wisdom	CHC	77	295	17	38	43	4	9.6%	35.7%	.237	.270	.210	.295	.447	.318	100	-0.4	-0.5	-2.3	0.7
29	Yandy Díaz	TBR	136	591	17	81	68	1	12.0%	14.6%	.157	.324	.293	.384	.450	.364	131	-2.5	20.2	-9.7	3.1
30	Alec Bohm	PHI	141	594	16	70	76	4	6.8%	17.2%	.145	.306	.272	.325	.417	.321	100	-1.6	-1.6	-2.6	1.6

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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.