While I slowly am beginning to understand how these indicators can be used to predict movement, I am still not certain about predicting the length of a move - ie, I guess this would be identificotion of Resistance and Support points (and others??).
"Prediction" is strong anathema to me. Athena Starwoman and Carlotta Tarotta make predictions. What T/A allows me to do is plan for two or more possible evolutions; and with the benefit of experience, it can also provide a rough idea about which of several outcomes has the higher probability.
If by "length" you mean the time that a chart maintains its trend, I suggest extra caution. It's hard enough to determine likely support, resistance, and turning points on a chart. Trying to guess the timing as well would add an unnecessary extra level of complication to the process.
Yes, I know that puts me at odds with disciples of Gann and Elliott. A dear late friend of mine was convinced he could find Gann cycles in his charts. And to some extent he could - mainly using historic charts over appropriate time frames: months or weeks or days, also varying whether weekends counted as days or not.
The crux with these cycles lies in the fact that they're most clearly visible when retro-fitted: "Look! Here we have 144 days between this Low and that High! And there is another proof: 144 weeks between a High and a Low!" Sorry, but those are not cycles. I have run scores of tests over decades of datasets with all imaginable periods. If there really were a periodicity between Lows and Highs, patterns of such cycles should show. But they don't.
Some obvious exceptions: If you have a stock that pays a good dividend every 3 or 6 months, you will find increased activity between their ex-div dates. For such stocks, if nothing else affects their trade performance, it will be rather easy to fit 13-week cycles over the 4 quarters of a year. And 13 is even a Fibonacci Number!
Conclusion: While price is frequently determined by historic support, resistance, and trend lines, the timing of breakouts and breakdowns is dependent on a vast number of different, company-specific causes. Some of these may well be cyclic: Quarterly reports, annual or bi-annual dividend payments, monthly RBA meetings and ABS releases, ... But the effects of external events: FX fluctuations, weather events, political worries, are overlaying such cycles and combine to a rather random distribution over time.