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WKO+ Performance Manager Chart

I was hoping you could look at my performance manager chart and tell me if this is where you expect a member to be following the EN plans.

Thanks,  Ed Croucher

Comments

  • @Ed, thanks for posting. For clarification purposes, this chart includes:

    * Your 14 week OS
    * The current Get Fast Plan

    Were there any other breaks during your year thus far? Swim camp? When are you due to transition to the IM Plan?
  • This is great stuff so I'll just add my PM-Chart too here.

    Included is swim, bike and run but sTSS is more or less an edjucated guess most of the time.

  • It's so hard to make comments on someone else's PMC. Meaning, the one thing that can't be placed on the chart is how you feel during those data points. I love making the ATL/CTL climb, climb, climb! And, making that TSB dive, dive, dive! I can also look back on it and almost pinpoint where I got hurt for the last 4 injuries (over the last 2 seasons). Unfortunately, after the fact. That's my goal this year...to pay attention to that PMC combined with that 'dead' leg fatigue that seems to hit me right before an injury and back off before re-injury. Seems to be working at this point. I am still amazed at how solid/accurate/predicting this stuff is.

    Obviously, for the newcomers peeking, critical is making sure that all workouts/data is entered for this to be as accurate as we're describing here. As Stefan mentioned, entering the swim data is a bit of an art and everyone may perceive the stress from a swim a bit differently. I, personally, give my swims very little TSS due to the fact that I'm usually drilling & working on form so swims are usually more recovery based for me.

    Ed- I see consistent training in the early months that have enough breaks to recover from ATL, thus keeping the chart from the steady inclines. But, more recently, like starting in FEB, your training seems to be more back to back to back ATL stuff that accumulates, building the CTL, dropping the TSB, in longer, steadier slopes. I would assume this is due to the two different plans tho I have to comment that my OS tracking seems to look more like the second half of your's even with the small volume/hi intensity/with rest day stuff that's built into the OS.

    Stefan- for some reason, with your's, I see the ocean with satellite imagery picking up debris, I must be watching the news too much.
  • During the time shown on this PMC, I had the 14 week OS, 2 week Swim camp, Run Focus plan and now the GF plan. I am scheduled to transition into the IM plan on May 5th. The 2 final weeks in December I had a torn calf muscle which caused rise in my TSB. The swim workouts are calculated as described in Hunter's book. I haven't done a swim TT in a while so I may be a bit high, but not much. I know that when I record an hour swim workout and the calculations say 70 sTss, my body feels like I did a 70 Tss workout run or bike. I know that training philosophies are different and that Friel & Allen profess more periodization than EN type training. This is my first season with EN and the intensity of the program is way higher than anything I had followed in the past. I feel strong. However, the lack of recovery within the plans do not provide for optimal test results. My big concern is getting into over training. I am still hitting my training zones for my workouts.

  • @Ed, thanks for clarifying. I am not worried about the lack of recovery for testing purposes....for me as long as you are hitting your numbers within your workouts, life is good. This chart is really good to look at NEXT YEAR when you can look back and say where am I now vs where I was. I am curious to see if you hit the same #s as your OS at the end of the GF plan...but so far, so good!

    Remember, if you _need_ to rest, do it and we can triage you on the other side!!!
  • Ed--  Take why Coach P said seriously.  If you need to insert a few rest days, do that.  do not follow the plan into a wall, but since your blue line is steadily moving up and to the right, you are good as long as you are not breaking down.  But there is a fine line between the two, so be cognizant of the numbers, but listen to your body FIRST!

  • With that said, I'll play along with mine as well.   Mine has been a little crazy as of late because I'm still technically in my hacked OS, and near finishing a 28-day consecutive run block (Run Durability hack), and also had a big 3 day bike camp thrown in there...   So I actually saw a -71.4 TSB on the back of a 173.2 ATL.   I was at this CTL number (~101 in June of last yr so I'm way ahead for that point by ~20pts).  And on top of that, my legs actually feel really good, so hopefully I can keep it up.

      

  • BTW, it is important to recognise that the constants in the PMC (short term and long term) are set as averages, and are not specific to each person.
    That is, unless you have specifically changed them based a few years experience.
  • Peter- can you expand on that? It takes me a bit longer to absorb all of this stuff so you really gotta spell it out to me. What do you 'not specific to each person'?
  • Hi Chris
    Sorry for being too cryptic! My Bad.
    The point I was trying to make was that the way the PMC is setup by default uses 7 days for the short term constant and 42 days as the long term constant.
    These constants define over what periods CTL and ATL are calculated. With the long term constant of 42 days, means that CTL is defined as the sum of TSS/day over the last 3 months. The short term constant of 7 days means that ATL is defined as the sum of TSS/day over the last 14 days.
    If the constants are changed, then CTL and ATL would be redefined with different periods from the default 14 days and 3 months.
    For example, this model assumes that training done more than 3 months ago will not impact on your form or fitness. The question is how each athlete responds to training and whether the default periods accurately describe the athlete.
    This was the point I was trying to make.
    Pages 148 - 160 (about) in Allen and Coggan, Training and Racing with a Power Meter cover this ground in some detail.
  • re: "this model assumes that training done more than 3 months ago will not impact on your form or fitness. The question is how each athlete responds to training and whether the default periods accurately describe the athlete. "



    never thought about this obvious point, thanks. But, how in the world would one know how to customize that? Trial and error?

    I have the book. I'll refresh myself on those pages, thanks for the reference.

  • My question for Peter is do you set your PMC with shorter time constant as a long-distant triathlete, or slightly longer as a masters athlete? I have chosen to leave my time constants at the 7/42. There is no doubt my training that was 4 months ago has had an impact on my current training. I just figure that Cogen set it up to fit the most athletes.

  • @ Chris — yes, trial and error.
    @ Edwin — I don't change the constants but always keep in mind that the PMC just attempts to model an athlete's response to doses of training. So I don't get too caught up in what the PMC is showing on any particular day.
    BTW, I have faith in the EN plans so I follow them as written, but make efforts not to follow them into a brick wall.
  • Been following this thread... some really good stuff in here ... Picking up new stuff and Always learning... My thoughts are to NOT change the constants they need to be consistent... It is important to keep your power and paces updated though .... But just like everything else DO NOT compare your PMC  to someone else's .... Just learn what works for you... IOW look at the CTL, ATL, TSB before, during, and after your races and correlate with how you felt and performed... Then over time you can track multiple races, multiple distances and year over year... And then with enough data you may attempt builds and tapers based on your PMC....For instance I am tracking my 2014 IMTX vs. 2013 IMTX .... I only have data starting from beginning of 2013...



    After watching and tracking my PMC for a little over a year now.... My take away is ... I dont need some  -47 TSB or 188 ATL to tell me I'm fried after a big week, then a long bike/brick session....  What I do find interesting and useful is the CTL.... This moves very slow and takes time to build it up showing fitness building with consistency and hard work over time ...



    MY comps for IMTX build.  January to today both years.   ATL and TSB were the highest and lowest in that period.  CTL first week in April. Pretty interesting how close they are.

    2013               2014

    ATL 187        ATL 188

    CTL 137        CTL 146

    TSB -52        TSB -47
  • @Peter & @Tim, Guys, thank you for your insight here. I have been using the WKO+ for 3 years. However, this is my first year with an actual training program. Before last fall, I did workouts as I thought they would fit. My training was not completely blind, I did read Hunter Allen & Joe Friel. The EN program is significantly more detailed and in depth than what I was doing. My body is acutely aware of the difference. I currently have 2 PMC's running, the current year and the previous year. I have been tracking the differences also. Last year, the low for my TSB was -25.9 but it averaged around the single digits. The chart this year is very different. My average is in the negative teens since February 16th. What I find really interesting is that last year when I had a TSB in the negative teens, I was gassed. This year, I am still hitting the workouts.

  • Thanks for the discussion. This has been really helpful. I've been using Training Peaks since 2010 and I went back and looked at my PMC since then. I did IMCDA in 2010, the full Vineman in '11 and '12, two HIMs last year and I'm doing the full Vineman again this year. I started with EN in the fall and did the NOS, then swim camp, bike focus with a big bike week, and now just started get faster. Here's my long view chart.

    <img alt="" width="863" height="339" 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

  • All this is good stuff IMO — one of the reasons I love EN!

    This post is just a recap on the conceptual model underlying the PMC and associated concepts.

    The main idea is that there exists a "dose-response" element to training.

    When an athlete does a workout, they incur both a positive training effect (ie more fitness) and a negative training effect (fatigue). The change in the training effect as well as the change in the fatigue are specific to each athlete and depend on a range of factors including genetics, volume/intensity/frequency of the wkos etc, rest/sleep, carbohydrate intake etc.

    For example, the day after an FTP interval set you are fitter than you were, but because of fatigue from that wko, you probably wouldn't be able to improve your performance in an FTP test. The rate at which fatigue falls is quicker than the decline in fitness following a wko — as a result, (usually) you get the maximum benefit from a wko with a few days rest after that wko.

    Now that example was for a single wko. However, fitness and fatigue add up over time with multiple wkos — in other words fitness today is the result of fitness yesterday (which has faded slightly because of the passage of one day), plus the fitness gained from a wko today. The same idea applies to fatigue. The fatigue you feel today is the fatigue you had yesterday, less a small amount as a result of the passing on a day, plus the fatigue you incurred in today's wko.

    Now back to the PCM. It tries to incorporate the different rates of change in fitness and fatigue with the passage of time to assist in answering questions like: "how long should I taper before my A race?" and "how many hard days in a row can I do before I need some easy days?" or "how many easy days do I need between epic wkos?".

    The constants are just a guess at how each of us respond to training, and in the absence of any better information (eg experience over a number of years) are the way to go.

    It is just important to keep that in mind when you see something in the PMC.  For example, a TSB of -55 might be a big danger sign, but it might not be. It just depends on the circumstances.

    As WSM Tim Cronk reminds us, you must not compare your PMC with anyone else's PMC — they just are so different!
  • Well said, Peter.

    I agree with Coach Ps comment...PMC is a good retrospective analytic tool, not very useful as a predictive tool. I've found that the nadir of TSB will usually show up about 24 hours after I have already decided to back off due to incipient over training assoicated with fatigue, based on my own internal readings of things like sleep, weight loss, grouchiness, deep fatigue, etc. I look at the PMC the next day and say, "Yeah, that's why I felt that way."

    The one prospective use I have found is in the last ten days before an A race ironman. Over the years, i have learned what my TSB and CTL should be doing during that time for good results. EG, a TSB of about 22-26 is my sweet spot; higher or lower, I don't do so well. I havent really found a pattern for other races, either non-A, or shorter distances.

    Again, NB...YMMV, dont use my numbers for yourself.
  • This has been a great topic. I am impressed by the information that is out there among all of you. I like the perspective that exist here with the experienced athletes that differ from Friel & Allen. I find the work in their books great. However, I feel stronger under the EN plan than I did under my past training.

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