Below is the same opening I used for my hitter projections, so if you have already visited those, just skip right on down to the stats. If not, here’s where you can find RW23’s hitter projections.

I’m really excited about this.

For the first time in its two-and-a-half year existence, The First Out At Third is featuring real projections rather than educated guesses like it has in previous years. I’m very excited to announce to finally debut RW23 projections.

RW23 is named after my favorite (and greatest) baseball player of all time, Rickie Weeks. I’ve loved him from the moment he made his Brewers’ debut and I shed many tears during his final game in Miller Park, although he wasn’t even given an at bat. I own a banner of Weeks that used to hang up in the stadium, and his is the only autograph I truly cherish. Naming my projections after him was a no-brainer.

Now, RW23 isn’t a scientific or mathematical, computer-based model. It relies on relatively simple formulas that I entered into Excel. I’d be remiss if I didn’t give Mike Podhorzer and his book “Projecting X 2.0” credit, though, as I purchased his book to aid me. I made a few small changes and added a bit of my own sauce to it, but there’s no way I would’ve been able to do this without Mike’s book.

Below you will find RW23’s projections along with a side-by-side comparison to Steamer and ZiPS — two well-respected projection systems.(Note: ZiPS doesn’t project xFIP.) At the end of the year I’ll compare the three systems to see how RW23 performed in its debut season.

As new players are added to the 25-man roster, I will dedicate an entire post to their projections, but for now, here are the pitcher projections for the 2017 Milwaukee Brewers.

SP Junior Guerra

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	162	17	1.27	.281	7.48	3.25	19.8%	8.6%	3.61	3.99	4.35
Steamer	192	25	1.39	.303	8.24	3.47	21.0%	8.9%	4.43	4.29	4.25
ZiPS	123	18	1.35	.294	8.20	3.66	20.9%	9.3%	4.24	4.54	N/A

SP Zach Davies

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	168	22	1.32	.305	7.75	2.61	20.2%	6.8%	4.13	4.14	3.95
Steamer	174	23	1.36	.306	7.67	2.82	19.7%	7.3%	4.35	4.19	4.11
ZiPS	169	20	1.27	.307	7.76	2.55	20.2%	6.6%	3.99	3.91	N/A

SP Jimmy Nelson

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	181	21	1.35	.296	7.83	3.47	20.1%	8.9%	4.02	4.27	4.16
Steamer	120	15	1.46	.308	7.39	3.64	18.5%	9.1%	4.80	4.57	4.48
ZiPS	170	21	1.38	.307	7.57	3.39	19.2%	8.6%	4.34	4.45	N/A

SP Matt Garza

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	96	11	1.44	.303	6.05	3.18	15.4%	8.1%	4.45	4.46	4.53
Steamer	128	19	1.46	.308	6.54	3.06	16.5%	7.7%	4.89	4.71	4.57
ZiPS	122	18	1.43	.309	6.30	3.04	15.8%	7.6%	5.04	4.76	N/A

SP Wily Peralta

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	125	16	1.42	.310	6.66	2.94	17.0%	7.5%	4.49	4.37	4.09
Steamer	140	18	1.45	.312	6.93	3.12	17.5%	7.9%	4.64	4.43	4.26
ZiPS	149	22	1.43	.312	6.67	3.07	16.7%	7.7%	4.81	4.70	N/A

SP Chase Anderson

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	138	25	1.40	.295	7.37	3.12	18.9%	8.0%	4.82	5.03	4.51
Steamer	133	18	1.37	.301	7.81	2.83	20.0%	7.2%	4.72	4.56	4.43
ZiPS	139	22	1.38	.308	7.28	2.96	18.5%	7.5%	4.64	4.67	N/A

RP Tommy Milone

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	61	7	1.33	.292	6.13	2.68	16.0%	7.0%	4.11	4.32	4.48
Steamer	57	8	1.27	.301	7.96	2.22	20.9%	5.8%	4.10	4.03	3.94
ZiPS	128	21	1.34	.306	7.03	2.46	18.0%	6.3%	4.71	4.61	N/A

RP Jacob Barnes

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	52	4	1.20	.293	9.09	3.12	24.5%	8.4%	3.10	3.18	3.54
Steamer	35	4	1.32	.304	8.98	3.28	23.3%	8.5%	3.94	3.84	3.88
ZiPS	53	5	1.27	.313	9.56	3.35	24.9%	8.7%	3.52	3.46	N/A

RP Corey Knebel

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	63	6	1.22	.297	10.32	3.48	27.6%	9.3%	3.24	3.29	3.43
Steamer	65	7	1.28	.302	10.66	3.77	27.9%	9.9%	3.56	3.49	3.56
ZiPS	54	7	1.27	.316	11.28	3.81	29.3%	9.9%	3.65	3.68	N/A

RP Jhan Marinez

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	53	4	1.33	.300	7.39	3.34	19.0%	8.6%	3.64	3.82	3.99
Steamer	55	6	1.41	.307	8.43	3.89	21.4%	9.9%	4.16	4.12	4.14
ZiPS	68	8	1.34	.307	8.07	3.31	20.7%	8.5%	3.84	4.21	N/A

RP Neftali Feliz

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	61	9	1.19	0.261	9.18	3.37	24.8%	9.1%	3.67	4.28	4.01
Steamer	65	8	1.28	0.295	10.15	3.56	26.5%	9.3%	3.83	3.81	3.88
ZiPS	55	9	1.30	0.299	9.43	3.58	N/A	N/A	4.39	4.41	N/A

RP Carlos Torres

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	73	9	1.28	.285	8.16	3.26	21.5%	8.6%	3.76	4.10	4.08
Steamer	55	7	1.36	.304	8.58	3.33	22.0%	8.6%	4.17	4.09	4.09
ZiPS	80	11	1.33	.301	8.74	3.59	22.4%	9.2%	3.92	4.29	N/A

RP Taylor Jungmann

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	53	6	1.52	.312	7.53	4.23	18.7%	10.5%	4.62	4.52	4.70
Steamer	85	11	1.53	.306	8.02	4.54	19.8%	11.2%	4.91	4.78	4.75
ZiPS	142	19	1.52	.308	8.09	4.78	19.9%	11.7%	4.97	4.88	N/A

RP Jared Hughes

	IP	HR	WHIP	BABIP	K/9	BB/9	K%	BB%	ERA	FIP	xFIP
RW23	62	5	1.38	.292	5.11	2.95	13.0%	7.5%	3.99	4.39	4.43
Steamer	10	1	1.46	.308	6.06	3.41	15.3%	8.6%	4.34	4.40	4.46
ZiPS	63	6	1.41	.303	5.12	2.98	N/A	N/A	3.69	4.52	N/A

Warning: Below is the same opening I used for my hitter projections (lazy is my name), so feel free to skip it and scroll down to the projections.

It’s that time of year again, when projections are being unleashed and the biased trolls of the internet emerge from their caves. I love it.

People say that projections are like throwing darts at a dart board and hoping it sticks where you want it too. Well, if that’s the case, then the dart’s trajectory has been calculated countless of times and the dart board is bigger than the average one. Projection systems, like Steamer and ZiPS, are the most accurate darts we currently have at our disposable. So many components (i.e. park factors, age, injury history, talent) play into their forecasts that it’s asinine not to put at least a little merit in them.

With that being said, my projections are not based on a mathematical model. My brain doesn’t possess the functionality it requires to build one or to even interpret simple mathematical equations. For someone who is so invested in sabermetrics, I don’t know a lick of math. I guess my projections are simply predictions.

On the other hand, my projections are more than just guess work. I’ve poured over each player’s statistical history, taken injuries and age into account, looked at splits, went over other projection systems and basically every other thing I could possibly do to make sure my projections were well-informed.

Here are my pitcher projections for the 2016 Milwaukee Brewers:

Position	Name	ERA	FIP	xFIP	SIERA	HR	K%	BB%	GB%	WAR
SP	Wily Peralta	4.45	4.61	4.11	4.20	18	15.9%	7.6%	52.4%	1.3
SP	Jimmy Nelson	3.88	3.83	3.97	4.01	20	19.2%	8.2%	52.1%	2.6
SP	Matt Garza	4.21	4.40	4.00	4.13	21	16.3%	8.0%	44.5%	0.9
SP	Taylor Jungmann	4.03	4.19	4.25	3.99	15	18.8%	10.5%	47.2%	1.6
SP	Chase Anderson	4.47	4.36	4.08	4.25	19	18.5%	7.3%	44.0%	1.7
RP	Carlos Torres	3.88	3.69	3.80	3.28	6	20.4%	8.2%	47.6%	0.2
RP	Jeremy Jeffress	2.86	3.01	3.12	2.88	6	24.5%	7.5%	59.3%	1.0
RP	Blaine Boyer	4.00	3.94	4.39	4.29	5	13.0%	6.4%	52.5%	0.1
RP	Tyler Thornburg	4.13	4.35	4.22	3.65	8	23.6%	9.7%	35.8%	-0.2
RP	Chris Capuano	3.99	4.02	3.77	3.92	4	19.7%	6.9%	41.7%	0.2
RP	Michael Blazek	3.23	3.52	3.94	3.50	5	22.1%	8.8%	48.1%	0.5
RP	Ariel Pena	4.22	4.09	4.59	4.15	3	23.4%	11.1%	38.8%	0.1
Total		3.95	4.00	4.02	3.85	130	19.6%	8.4%	47.0%	10.0

Quick Hits

• The rotation should be considerably better than a year ago. No Kyle Lohse, and there’s no way Matt Garza can repeat his outrageously horrendous performance, is there?
• Jeremy Jeffress is primed for another fantastic season, especially if he can up his K rate.
• Jimmy Nelson will have the highest WAR and solidify his spot as the best pitcher in the rotation.
• Wily Peralta’s strikeout percentage will continue to be underwhelming.
• The bullpen might struggle, especially if the starters can’t go deep into games.

It’s that time of year again, when projections are being unleashed and the biased trolls of the internet emerge from their caves. I love it.

People say that projections are like throwing darts at a dart board and hoping it sticks where you want it too. Well, if that’s the case, then the dart’s trajectory has been calculated countless of times and the dart board is bigger than the average one. Projection systems, like Steamer and ZiPS, are the most accurate darts we currently have at our disposable. So many components (i.e. park factors, age, injury history, talent) play into their forecasts that it’s asinine not to put at least a little merit in them.

With that being said, my projections are not based on a mathematical model. My brain doesn’t possess the functionality it requires to build one or to even interpret simple mathematical equations. For someone who is so invested in sabermetrics, I don’t know a lick of math. I guess my projections are simply predictions.

On the other hand, my projections are more than just guess work. I’ve poured over each player’s statistical history, taken injuries and age into account, looked at splits, went over other projection systems and basically every other thing I could possibly do to make sure my projections were well-informed.

Here are my hitter projections for the 2016 Milwaukee Brewers:

Position	Name	AVG	HR	wOBA	wRC+	OBP	ISO	K%	BB%	WAR
C	Jonathan Lucroy	.290	10	.331	115	.333	.133	12.4%	9.0%	3.5
1B	Chris Carter	.220	28	.330	116	.311	.235	33.4%	11.1%	1.3
2B	Scooter Gennett	.271	6	.285	81	.299	.125	19.0%	3.6%	0.4
3B	Aaron Hill	.237	7	.296	90	.311	.119	15.2%	7.9%	0.5
SS	Jonathan Villar	.233	5	.289	79	.303	.128	25.1%	6.3%	0.2
OF	Keon Broxton	.255	4	.305	83	.315	.159	33.6%	7.4%	0.5
OF	Domingo Santana	.269	22	.345	118	.330	.208	32.9%	10.8%	2.5
OF	Ryan Braun	.280	23	.352	121	.348	.210	20.5%	9.3%	2.9
C	Martin Maldonado	.236	4	.265	62	.290	.111	26.3%	9.2%	-0.1
OF	Ramon Flores	.266	5	.323	99	.324	.139	16.2%	8.7%	0.6
INF	Yadiel Rivera	.222	2	.261	56	.249	.091	24.7%	3.9%	-0.3
INF	Colin Walsh	.247	4	.297	88	.325	.110	25.0%	10.9%	0.1
OF	Kirk Nieuwenhuis	.233	4	.309	91	.285	.192	31.3%	7.5%	0.3
Total		.251	124	.307	92	.309	.151	24.3%	8.1%	12.4

Quick Hits

• No Brewer will bat .300 or better, and only four will be above-average hitters.
• I expect Jonathan Lucroy to bounce back and re-enter the “best catcher in baseball” discussion.
• I’m excited about Chris Carter. I wouldn’t be surprised if he put up 40 home runs. According exit velocity, nobody hit the ball harder than Carter from Aug. 1 on in 2015. His defense will keep his WAR down.
• Domingo Santana, the most exciting player on the roster, will be an All Star this season. Mark it down.
• Milwaukee’s bench is a sight for sore eyes.