All Free Agent Fantasy Team Update: ZiPS Projections

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Feb 24, 2013; Dunedin, FL, USA; Toronto Blue Jays shortstop Maicer Izturis (3) stretches before a spring training game against the Baltimore Orioles at Florida Auto Exchange Park. Mandatory Credit: Derick E. Hingle-USA TODAY Sports

Spring Training is here, and teams are playing games against each other. My Free Agent Fantasy team has been finished for a while now, so we have been looking at projections. Since the final ZiPS spreadsheet is out, I figured it would be a good time to look at my team through the lens of ZIPs and project how well my team might do. So below is the list of players and their contracts, followed by the WAR ZiPS projects them to have, along with their ERA + if they are a pitcher and their OPS + if they are a hitter (making spreadsheets like this in WordPress is difficult, so it looks like Freddy Garcia is messed up towards the bottom for some reason):

Bartolo ColonSP3 Mil1.495
Oliver PerezRP1.5 Mil -.578
Michael OlmstedRPMiLB .7 115
Tim WoodRPMiLB-.4 77
Ryan ReidRPMiLB -.7 72
Maicer IzturisSS3 Mil6 mil 1.1 91
Hector RondonRPMiLB .1 83
David RossCatcher3.1 Mil3.1 Mil .8 94
Mitch MaierOFMiLB -.2 74
Juan PierreOF1.6 mil .4 84
Melky CabreraOF8 mil8 mil 2.5 113
Scott BakerSP5.5 mil 1.6 100
Neal CottsRPMiLB-.2 78
Carlos TorresRPMiLB .4 84
Tim ByrdakRPMiLB .1 98
Brian BogusevicOFMiLB .1 73
DeWayne WiseOF.7 mil .8 80
Shawn CampRP1.35 mil .4 101
Jeremy GuthrieSP5 mil20 mil. 1.9 93
Hiroki KurodaSP15 mil. 3 100
Ryan MadsonRP3.5 mil .5 119
Mike Fontenot2B/IFMiLB .3 81
Rich ThompsonOFMiLB 1.3 72
John LannanSP2.5 mil 1.1 86
Andres TorresOF2 mil 2.1 94
Bobby WilsonCatcherMiLB .4 78
Jack Hanahan3B2 mil2 mil.7 76
Dan WheelerRPMiLB -.1 83
Jason GrilliRP2.75 mil4 mil .6 116
Ryan LudwickOF7.5 mil7.5 mil 1.1 104
Brandon Allen1BMiLB .3 85
Randy WellsSPMiLB -.1 75
Zach PhillipsRPMiLB 0 88
Jason BourgeoisOFMiLB -.1 68
Nate SchierholtzOF2.25 mil .8 97
Eric Chavez3B3 mil .6 94
Nate MclouthOF2 mil 1 90
Marco Scutaro2B6.66 mil13.33 mil 1.9 91
Jeff Keppinger2B4 mil8 mil 1.6 97
Mike EkstromRPMiLB -.1 85
Bill BrayRPMiLB 0 88
Geovany SotoCatcher2.75 mil 1.5 88
James Loney1B2 mil.9 92
Ryan SadowskiRPMiLB — —
Scott FeldmanSP6 mil 1 92
Travis Ishikawa1BMiLB .2 80
Zach BraddockRPMiLB .2 93
Cody RansomSSMiLB .3 72
Hisanori TakahasiRPMiLB .2 98
Endy ChavezOFMiLB -.2 67
Yorvit TorrealbaCatcherMiLB .9 79
Dan Johnson1BMiLB .9 98
Thomas NealOFMiLB .4 83
Kevin SloweySPMiLB .4 82
Matt Downs2BMiLB 0 89
Chris VolstadSPMiLB .2 77
Kyle McClellanRPMiLB .3 86
Cesar IzturisSSMiLB .2 58
Ryan SweeneyOFMiLB .5 84

Freddy Garcia    SP           MiLB                   1.1 93

Of course, I am going to cut at least 20 players, since I am bringing in 60 players to spring training but can only have 40 on my roster (25 active, 15 inactive). So before adding anything up for this projection, I’ll take out the 20 worst WAR projected players. 10 of my 60 players are projected to be below replacement, so we will take them out. 3 players are projected to be right at replacement, so we will take them out as well as the 3 players that are projected to be worth .1 WAR. 5 players are projected to have a .2 WAR, so we will take out all of them out but Hisanori Takahashi and Zach Braddock because they have the highest ERA + or OPS + (unprojected Ryan Sadowski counts as the 20th player cut in this scenario). These are not necessarily the players I will cut obviously, but it gives us the most optimistic ZIPs projection. The combined WAR of the 40 players left is 37.9. Assuming replacement level is .320 % (it differs from WAR to WAR, but this is Baseball Reference’s method), a replacement team would win 51.84 games, and my team is projected to win approximately 90 games by ZIPs. Of course, 15 of these players will at least start the year as “inactive” (on the DL or in the minors), and projecting WAR means projecting playing time. Since our own projections put the team at about .500 in winning percentage, our ZIPs projection is probably too optimistic. While ERA + has some problems, the fact that ZIPs uses it in the projections allows us to make a better projection against average. By adding up the ERA + and OPS + of our 40 players left on our hypothetical team, we can measure what our team is against average. Of course, it doesn’t weigh defense, but our own projections showed that the team should be roughly average defensively. Adding up the ERA + and OPS + of all 40 players got us about a 92 OPS/ERA +. This means my team is about 8% below average, or about a 75 win team. This is the worst we have seen the team projected at. Of course, while using WAR has a playing time bias, using this method has a no playing time bias, meaning it assumes everyone will play equally. Obviously this isn’t true, as it overrates relievers, and makes utility and backup players weigh down the average. It would seem though that these two metrics point to what we have seen in other projections. My All Free Agent Fantasy team will probably be about an average team.