Jump to content
Jays Centre
  • Create Account

Comx

Verified Member
  • Posts

    165
  • Joined

  • Last visited

 Content Type 

Profiles

Toronto Blue Jays Videos

2026 Toronto Blue Jays Top Prospects Ranking

Toronto Blue Jays Free Agent & Trade Rumors, Notes, & Tidbits

Guides & Resources

2025 Toronto Blue Jays Draft Pick Tracker

News

2026 Toronto Blue Jays Draft Pick Tracker

Forums

Blogs

Events

Store

Downloads

Gallery

Everything posted by Comx

  1. http://www.awesomelyluvvie.com/wp-content/uploads/2013/08/Stay-Classy-San-Diego.gif
  2. Smoke and mirrors distraction - AA should be focusing on trades that will make a significant difference now, not adding depth.
  3. Stick a fork in 'em - they're done!
  4. Good, he'll prob be back up soon enough.
  5. "Mild quad strains usually heal within 10 days. Moderate strains take 10 days to six weeks, and severe strains require three months or longer for recovery."
  6. "Mild quad strains usually heal within 10 days. Moderate strains take 10 days to six weeks, and severe strains require three months or longer for recovery." Looked at least moderate, perhaps severe.
  7. Organization is run by geniuses not little piss ants that don't have a clue.
  8. Gotta love how the Jays handed over a 6 game division lead like it was nothing at all.
  9. Blue jays looking bad at baseball lately, to state the obvious
  10. Let's just say for the purpose of example: Hitter A) Literally only hits singles Hitter Literally only hits home runs Park factor will have almost no impact on hitter A. So multiplying PF * wRC+ is just wrong (you're not going to hit more singles in a hitter-friendly park). While multiplying PF * wRC+ for Hitter B makes sense. This is an extreme example and would be similar to someone like Ben Revere and Adam Dunn. Ben Revere at Coors Field is 80[wRC]+ * 1.3[PF] = 104[wRC+]..... we both know it would be closer to 80 wRC+, so this is wrong. Further more, Adam Dunn at Coors field: 124[wRC+] * 1.3PF = 161[wRC+]... it's more accurate.
  11. I'm not sure because a player who doesn't hit for power wouldn't really be affected much by PF. I just don't know how to account for this, on a player to player basis.
  12. Take for example two hitters, one is a slugger (A) and the other has no power (. Which offensive stat would you multiply park factor by to get an accurate inflated offensive stat in said ballpark? 1) Player A would benefit a lot more being in a hitters park than player B, so how would you equate wRC+ or wOBA to the ball park based on the player type? 2) With regard to a singular stat like HR I think it would be fair to multiple HR * PF to get accurate projection of HR in said ball park, yes? Thoughts?
  13. If you read my post I'm referring to RoS (rest of season) projections, not whole seasons as you said. I'm not expecting projections to be exact, I'm saying with young and old players often have seasons that are defying projection systems altogether, you can basically throw them out completely in some cases. Mike Trout's rookie season is an example, projections would of been way off. And then again his next season would of been way off. Agree on this point. But I'm not sure you're getting my argument: projection systems are better suited for players with a few full seasons in the majors under their belt and 35-37 years old and under, outside of this they are significantly less predictable.
  14. This is basically what I'm referring to with young and old players. Projection systems are late/slow to pick-up on rookies struggling in the majors, and late/slow to pick-up on that age-related decline/drop-off... in both cases the projections are too high.
  15. With the most popular projection systems being ZiPS and Steamer, I'm wondering just how reliable are these formulas? I've found with young and old players the projections can get a bit wonky. These formulas are a best guess using the intelligence and historical data available but nobody would admit them to be near perfect. Here's a three examples of projections that are looking pretty off: Brad Miller - 24 y.o. Great milb stats and performed well in 1/2 of 2013, but has faltered and shown no real signs of improvement in 2014, BABIP is low but consistently. Current 2014 wRC+: 34 Projected 2014 wRC+: 90 and 97 (ZiPS and Steamer RoS, respectively) Alfonso Soriano - 38 y.o. BABIP and other peripheral stats pretty normal, just not performing as well as expected. Current 2014 wRC+: 78 Projected 2014 wRC+: 105 and 90 (ZiPS and Steamer RoS, respectively) Joe Nathan - 39 y.o. K's are down, BB's are up, BABIP is lower than average, velocity down about 1 mph Current 2014 FIP: 4.82 Projected 2014 FIP: 3.42 and 3.19 (ZiPS and Steamer RoS, respectively)
  16. Sanchez has crazy low HR/9 and tends not to give up a lot of hits...... this formula would allow him to walk more than the average pitcher and get away with it.
  17. Can someone sanity check this logic? If a players home park is a hitters park and has a park factor of 130 then his stats will be inflated and his ZIPS projections will be based on those inflated numbers too. So when calculating this players offense at home by park factor it should be 1/2 of 130 (115)... because his numbers are already "half" inflated by playing in his home park half the time; assuming the rest of the time he plays in an average hitting park (100). Further more, if a players home ball park has a park factor of 80 and now he's playing in an away park with a park factor of 130 then you should actually calculate his offense by using a park factor of 130+10 (140); because he plays in a park of 80 and the rest of the time it's 100.... (80 + 100)/2 = 90; since his ZIPS projections would be deflated from playing in a pitchers park "half" the time. Marking things more complicated would be a player that has recently changed teams. I doubt his ZIPS account for the new park factor.
  18. Wanted to say thanks for all the tips and suggestions. Now that I've had a few days to think about it I realized my initial "formula" was pretty rudimentary... though certainly better than using nothing. So with that said I'll try to use as much information as possible. The one thing that I have found truly hard to quantify is the "hot and cold" factor... players who have been "hot" for a short period of games seem to be a better bet... so I'm thinking of creating some kind of rating system for that.
×
×
  • Create New...