Humans are remarkably susceptible to confirmation bias.
https://en.wikipedia.org/wiki/Confirmation_bias

This is why the scientific method was developed so that cognitive biases can be reduced as far as possible.
You make an observation, form a hypothesis, seek to prove that hypothesis and then publish your findings and methods so that others can analyse your data and repeat your experiments/observations. This is then peer reviewed and any discrepancies can be found.

Only when it becomes the general consensus of the scientific community is it then accepted as a valid theory.

[iWe have a rota for going out to the field to collect data. My turn is Tuesday. It seems that whenever I go, it rains. After checking the weather data I confirmed that it had rained on 5 out of the last 6 Tuesday afternoons. The next week it also rained on Tuesday. (Although it was just 10 minutes of light drizzle just before I left).



What can I extrapolate from this?
It nearly always rains on a Tuesday?
It rains more often on a Tuesday?
There is a conspiracy against me by the rain gods to make it rain when I'm out in the field?

By looking more closely and dispassionately at the data I find that it actually rained [uevery[/u Friday for the last 6 weeks and looking at the annual picture, rainfall is equally likely on every day of the week.
[/i

So, back to the refs.
If you see that James Child is the ref and you 'know' he is a bad ref with a grudge against Wakefield you will be looking out for every perceived error he makes which disadvantages Wakefield. You probably won't notice the errors he makes in their favour.

So, what can we do? If we studied a Wakefield game/games reffed by James Child and went through every decision or non-decision minute-by-minute, preferably by multiple independent people, then compared results, maybe we could start to make a judgement.

Pick a game, let's do it



Or, we could rely on the stats available.

[i[u[size=150Wakefield versus Castleford 2010 - 2020[/size[/u[/i

[iAll Referees:[/i
Played 30
Won 7
Lost 23
Win Rate: 23.3%

[iJames Child:[/i
Played 9
Won 2
Lost 7
Win Rate: 22.2%

You could say that we've only won 6 out of the last 30 games with James Child in charge (20%), but that is cherry picking data and we're back to cognitive bias. It doesn't take into account which teams we were playing or the relative form/injuries of the two teams at the time.

I could also say that from the beginning of Super League until 2010 we won 86% of all our games reffed by James Child (this is true).

If one ref only reffed us against top 4 sides would his record show that he was biased against us?

[i[size=200Show me some evidence[/size[/i

Humans are remarkably susceptible to confirmation bias.
https://en.wikipedia.org/wiki/Confirmation_bias

This is why the scientific method was developed so that cognitive biases can be reduced as far as possible.
You make an observation, form a hypothesis, seek to prove that hypothesis and then publish your findings and methods so that others can analyse your data and repeat your experiments/observations. This is then peer reviewed and any discrepancies can be found.

Only when it becomes the general consensus of the scientific community is it then accepted as a valid theory.

[iWe have a rota for going out to the field to collect data. My turn is Tuesday. It seems that whenever I go, it rains. After checking the weather data I confirmed that it had rained on 5 out of the last 6 Tuesday afternoons. The next week it also rained on Tuesday. (Although it was just 10 minutes of light drizzle just before I left).



What can I extrapolate from this?
It nearly always rains on a Tuesday?
It rains more often on a Tuesday?
There is a conspiracy against me by the rain gods to make it rain when I'm out in the field?

By looking more closely and dispassionately at the data I find that it actually rained [uevery[/u Friday for the last 6 weeks and looking at the annual picture, rainfall is equally likely on every day of the week.
[/i

So, back to the refs.
If you see that James Child is the ref and you 'know' he is a bad ref with a grudge against Wakefield you will be looking out for every perceived error he makes which disadvantages Wakefield. You probably won't notice the errors he makes in their favour.

So, what can we do? If we studied a Wakefield game/games reffed by James Child and went through every decision or non-decision minute-by-minute, preferably by multiple independent people, then compared results, maybe we could start to make a judgement.

Pick a game, let's do it



Or, we could rely on the stats available.

[i[u[size=150Wakefield versus Castleford 2010 - 2020[/size[/u[/i

[iAll Referees:[/i
Played 30
Won 7
Lost 23
Win Rate: 23.3%

[iJames Child:[/i
Played 9
Won 2
Lost 7
Win Rate: 22.2%

You could say that we've only won 6 out of the last 30 games with James Child in charge (20%), but that is cherry picking data and we're back to cognitive bias. It doesn't take into account which teams we were playing or the relative form/injuries of the two teams at the time.

I could also say that from the beginning of Super League until 2010 we won 86% of all our games reffed by James Child (this is true).

If one ref only reffed us against top 4 sides would his record show that he was biased against us?

[i[size=200Show me some evidence[/size[/i